Image Basics
-Last updated on 2024-06-07 | +
Last updated on 2024-06-18 | Edit this page
@@ -358,6 +358,20 @@Objectives
real world. Before we begin to learn how to process images with Python programs, we need to spend some time understanding how these abstractions work. +Callout +
+Feel free to make use of the available cheat-sheet as a guide for +the rest of the course material. View it online, share it, or print the +PDF!
+Pixels
It is important to realise that images are stored as rectangular @@ -1524,7 +1538,7 @@
Key PointsOUTPUT<
-
+
- 5
@@ -507,7 +507,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -649,7 +649,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -755,7 +755,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -869,7 +869,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -923,7 +923,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1014,7 +1014,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1120,7 +1120,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/aio.html b/aio.html
index 241c70f69..46c96a2d9 100644
--- a/aio.html
+++ b/aio.html
@@ -490,7 +490,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -541,6 +541,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5085,7 +5099,7 @@ OUTPUT<
-
+
- 5
@@ -5117,7 +5131,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5262,7 +5276,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5368,7 +5382,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5485,7 +5499,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5541,7 +5555,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
- 5
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
- 5
@@ -5163,7 +5177,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5308,7 +5322,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
- 5
Object counting (optional, not included in
-
+
- 2
@@ -649,7 +649,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -755,7 +755,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -869,7 +869,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -923,7 +923,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1014,7 +1014,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1120,7 +1120,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/aio.html b/aio.html
index 241c70f69..46c96a2d9 100644
--- a/aio.html
+++ b/aio.html
@@ -490,7 +490,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -541,6 +541,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5085,7 +5099,7 @@ OUTPUT<
-
+
- 5
@@ -5117,7 +5131,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5262,7 +5276,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5368,7 +5382,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5485,7 +5499,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5541,7 +5555,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
- 5
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
- 5
@@ -5163,7 +5177,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5308,7 +5322,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
- 2
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -755,7 +755,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -869,7 +869,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -923,7 +923,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1014,7 +1014,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1120,7 +1120,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/aio.html b/aio.html
index 241c70f69..46c96a2d9 100644
--- a/aio.html
+++ b/aio.html
@@ -490,7 +490,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -541,6 +541,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5085,7 +5099,7 @@ OUTPUT<
-
+
- 5
@@ -5117,7 +5131,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5262,7 +5276,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5368,7 +5382,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5485,7 +5499,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5541,7 +5555,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
- 5
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
- 5
@@ -5163,7 +5177,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5308,7 +5322,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
If you are using an older version of Matplotlib you might get a warning @@ -755,7 +755,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -869,7 +869,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -923,7 +923,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1014,7 +1014,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1120,7 +1120,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/aio.html b/aio.html
index 241c70f69..46c96a2d9 100644
--- a/aio.html
+++ b/aio.html
@@ -490,7 +490,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -541,6 +541,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5085,7 +5099,7 @@ OUTPUT<
-
+
- 5
@@ -5117,7 +5131,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5262,7 +5276,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5368,7 +5382,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5485,7 +5499,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5541,7 +5555,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
- 5
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
- 5
@@ -5163,7 +5177,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5308,7 +5322,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -869,7 +869,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -923,7 +923,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1014,7 +1014,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1120,7 +1120,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/aio.html b/aio.html
index 241c70f69..46c96a2d9 100644
--- a/aio.html
+++ b/aio.html
@@ -490,7 +490,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -541,6 +541,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5085,7 +5099,7 @@ OUTPUT<
-
+
- 5
@@ -5117,7 +5131,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5262,7 +5276,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5368,7 +5382,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5485,7 +5499,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5541,7 +5555,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
- 5
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
- 5
@@ -5163,7 +5177,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5308,7 +5322,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
The histogram can be plotted with
Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1014,7 +1014,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1120,7 +1120,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/aio.html b/aio.html
index 241c70f69..46c96a2d9 100644
--- a/aio.html
+++ b/aio.html
@@ -490,7 +490,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -541,6 +541,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5085,7 +5099,7 @@ OUTPUT<
-
+
- 5
@@ -5117,7 +5131,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5262,7 +5276,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5368,7 +5382,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5485,7 +5499,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5541,7 +5555,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
- 5
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
- 5
@@ -5163,7 +5177,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5308,7 +5322,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
One way to count only objects above a certain area is to first create a list of those objects, and then take the length of that list as the @@ -1014,7 +1014,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1120,7 +1120,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/aio.html b/aio.html
index 241c70f69..46c96a2d9 100644
--- a/aio.html
+++ b/aio.html
@@ -490,7 +490,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -541,6 +541,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5085,7 +5099,7 @@ OUTPUT<
-
+
- 5
@@ -5117,7 +5131,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5262,7 +5276,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5368,7 +5382,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5485,7 +5499,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5541,7 +5555,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
- 5
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
- 5
@@ -5163,7 +5177,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5308,7 +5322,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
To remove the small objects from the labeled image, we change the value of all pixels that belong to the small objects to the background @@ -1120,7 +1120,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/aio.html b/aio.html
index 241c70f69..46c96a2d9 100644
--- a/aio.html
+++ b/aio.html
@@ -490,7 +490,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -541,6 +541,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5085,7 +5099,7 @@ OUTPUT<
-
+
- 5
@@ -5117,7 +5131,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5262,7 +5276,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5368,7 +5382,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5485,7 +5499,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5541,7 +5555,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
- 5
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
- 5
@@ -5163,7 +5177,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5308,7 +5322,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/aio.html b/aio.html
index 241c70f69..46c96a2d9 100644
--- a/aio.html
+++ b/aio.html
@@ -490,7 +490,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -541,6 +541,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5085,7 +5099,7 @@ OUTPUT<
-
+
- 5
@@ -5117,7 +5131,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5262,7 +5276,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5368,7 +5382,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5485,7 +5499,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5541,7 +5555,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
- 5
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
- 5
@@ -5163,7 +5177,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5308,7 +5322,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
Objectives
real world. Before we begin to learn how to process images with Python programs, we need to spend some time understanding how these abstractions work. +Callout +
+Feel free to make use of the available cheat-sheet as a guide for +the rest of the course material. View it online, share it, or print the +PDF!
+Pixels
@@ -5085,7 +5099,7 @@
OUTPUT<
-
+
- 5
@@ -5117,7 +5131,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5262,7 +5276,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5368,7 +5382,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5485,7 +5499,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5541,7 +5555,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
- 5
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
- 5
@@ -5163,7 +5177,7 @@ Object counting (optional, not included in
-
+
- 2
@@ -5308,7 +5322,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+- A cheat-sheet with graphics illustrating some concepts in this
+lesson is available:
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
- 5 @@ -5117,7 +5131,7 @@
- 2 @@ -5262,7 +5276,7 @@
- A cheat-sheet with graphics illustrating some concepts in this +lesson is available: + +
- 5
- 2
- 5 @@ -5163,7 +5177,7 @@
- 2 @@ -5308,7 +5322,7 @@
- A cheat-sheet with graphics illustrating some concepts in this +lesson is available: + +
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5368,7 +5382,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5485,7 +5499,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5541,7 +5555,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
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-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
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"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
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"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5368,7 +5382,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5485,7 +5499,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5541,7 +5555,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
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"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
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"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
If you are using an older version of Matplotlib you might get a warning @@ -5368,7 +5382,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5485,7 +5499,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5541,7 +5555,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
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-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
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"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
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"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5485,7 +5499,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5541,7 +5555,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
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"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
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"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
The histogram can be plotted with
Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
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"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
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+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
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"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
One way to count only objects above a certain area is to first create a list of those objects, and then take the length of that list as the @@ -5634,7 +5648,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
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"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
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"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
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"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
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"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
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"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
To remove the small objects from the labeled image, we change the value of all pixels that belong to the small objects to the background @@ -5740,7 +5754,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
+image-processing-python-cheatsheet.html
+
+
+
+
+
+
+
diff --git a/files/cheatsheet.pdf b/files/cheatsheet.pdf
new file mode 100644
index 000000000..9d8250f9e
Binary files /dev/null and b/files/cheatsheet.pdf differ
diff --git a/instructor-notes.html b/instructor-notes.html
index f7d3ffcb8..ad5e29bfa 100644
--- a/instructor-notes.html
+++ b/instructor-notes.html
@@ -404,6 +404,20 @@ Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html
index 9c7e6a2d9..6c46cf358 100644
--- a/instructor/02-image-basics.html
+++ b/instructor/02-image-basics.html
@@ -305,7 +305,7 @@
Image Basics
- Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
@@ -360,6 +360,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
It is important to realise that images are stored as rectangular
@@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
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@@ -12,7 +12,7 @@
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"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/files/assets/dc-logo-white.svg b/files/assets/dc-logo-white.svg
new file mode 100644
index 000000000..7336a5d28
--- /dev/null
+++ b/files/assets/dc-logo-white.svg
@@ -0,0 +1,34 @@
+
+
+
+
diff --git a/files/assets/fixed_cells_masked.png b/files/assets/fixed_cells_masked.png
new file mode 100644
index 000000000..fc7272a3c
Binary files /dev/null and b/files/assets/fixed_cells_masked.png differ
diff --git a/files/cheatsheet.html b/files/cheatsheet.html
new file mode 100644
index 000000000..e79d9acb9
--- /dev/null
+++ b/files/cheatsheet.html
@@ -0,0 +1,12 @@
+
+
+
+
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources +
++
-
+
Questions from Learners
diff --git a/instructor/02-image-basics.html b/instructor/02-image-basics.html index 9c7e6a2d9..6c46cf358 100644 --- a/instructor/02-image-basics.html +++ b/instructor/02-image-basics.html @@ -305,7 +305,7 @@
Image Basics
-Last updated on 2024-06-07 | +
Last updated on 2024-06-18 | Edit this page
@@ -360,6 +360,20 @@Objectives
real world. Before we begin to learn how to process images with Python programs, we need to spend some time understanding how these abstractions work. +Callout +
+Feel free to make use of the available cheat-sheet as a guide for +the rest of the course material. View it online, share it, or print the +PDF!
+Pixels
It is important to realise that images are stored as rectangular @@ -1526,7 +1540,7 @@
Key PointsOUTPUT<
-
+
@@ -509,7 +509,7 @@ Object counting (optional, not included in
-
+
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
Object counting (optional, not included in
-
+
@@ -651,7 +651,7 @@ PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
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"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
If you are using an older version of Matplotlib you might get a warning @@ -757,7 +757,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
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"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -871,7 +871,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -925,7 +925,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
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"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
The histogram can be plotted with
Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
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"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
One way to count only objects above a certain area is to first create a list of those objects, and then take the length of that list as the @@ -1016,7 +1016,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
To remove the small objects from the labeled image, we change the value of all pixels that belong to the small objects to the background @@ -1122,7 +1122,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/aio.html b/instructor/aio.html
index 9395dd60a..e55cfbf5b 100644
--- a/instructor/aio.html
+++ b/instructor/aio.html
@@ -493,7 +493,7 @@
Key PointsContent from Image Basics
-Last updated on 2024-06-07 |
+
Last updated on 2024-06-18 |
Edit this page
Estimated time: 25 minutes
@@ -545,6 +545,20 @@ Objectives
real world. Before we begin to learn how to process images with Python
programs, we need to spend some time understanding how these
abstractions work.
+
+
+
+
+
+Callout
+
+
+Feel free to make use of the available cheat-sheet as a guide for
+the rest of the course material. View it online, share it, or print the
+PDF!
+
+
+
Pixels
@@ -5131,7 +5145,7 @@ OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
Callout +
+Feel free to make use of the available cheat-sheet as a guide for +the rest of the course material. View it online, share it, or print the +PDF!
+Pixels
@@ -5131,7 +5145,7 @@
OUTPUT<
-
+
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
Object counting (optional, not included in
-
+
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
PYTHON<
Do you see an empty image?
-
+
If you are using an older version of Matplotlib you might get a
warning
@@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
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"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
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"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
If you are using an older version of Matplotlib you might get a warning @@ -5414,7 +5428,7 @@
How many objects are in that image (15
-
+
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
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"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
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"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
As you might have guessed, the return value count
already contains the number of objects found in the image. So it can
@@ -5531,7 +5545,7 @@
Plot a histogram of the object area
-
+
The histogram can be plotted with
@@ -5587,7 +5601,7 @@ Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
The histogram can be plotted with
Filter objects by area (10 min)
Show me the solution
-
+
One way to count only objects above a certain area is to first create
a list of those objects, and then take the length of that list as the
@@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
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"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
One way to count only objects above a certain area is to first create a list of those objects, and then take the length of that list as the @@ -5680,7 +5694,7 @@
Remove small objects (20 min)
Show me the solution
-
+
To remove the small objects from the labeled image, we change the
value of all pixels that belong to the small objects to the background
@@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
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"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
To remove the small objects from the labeled image, we change the value of all pixels that belong to the small objects to the background @@ -5786,7 +5800,7 @@
Colour objects by area (optional, not included
-
+
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources
+
+
+
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt
index f9c1ccfd6..82616e867 100644
--- a/md5sum.txt
+++ b/md5sum.txt
@@ -4,7 +4,7 @@
"config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25"
"index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26"
"episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26"
-"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07"
+"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18"
"episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07"
"episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07"
"episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14"
@@ -12,7 +12,7 @@
"episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12"
"episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12"
"episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12"
-"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12"
+"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18"
"learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26"
"learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16"
"learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26"
diff --git a/pkgdown.yml b/pkgdown.yml
index ad69cf4d7..e9e416352 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,5 +2,5 @@ pandoc: 3.1.11
pkgdown: 2.0.9
pkgdown_sha: ~
articles: {}
-last_built: 2024-06-18T09:13Z
+last_built: 2024-06-18T14:12Z
diff --git a/sitemap.xml b/sitemap.xml
index 465dc98ec..88df8002c 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -45,6 +45,9 @@
https://datacarpentry.github.io/image-processing/edge-detection.html
+
+ https://datacarpentry.github.io/image-processing/files/cheatsheet.html
+
https://datacarpentry.github.io/image-processing/images.html
We already know how to get the areas of the objects from the
regionprops. We just need to insert a zero area value for
diff --git a/instructor/instructor-notes.html b/instructor/instructor-notes.html
index 2daa59415..d5da68a7a 100644
--- a/instructor/instructor-notes.html
+++ b/instructor/instructor-notes.html
@@ -406,6 +406,20 @@
Instructor Notes
plt.imshow is called without the vmax
parameter. A detailed explanation is given in the Plotting single
channel images (cmap, vmin, vmax) callout box.
+Additional resources +
++
-
+
Questions from Learners
diff --git a/md5sum.txt b/md5sum.txt index f9c1ccfd6..82616e867 100644 --- a/md5sum.txt +++ b/md5sum.txt @@ -4,7 +4,7 @@ "config.yaml" "101b3ac4b679126bb1f437306eb1b836" "site/built/config.yaml" "2023-04-25" "index.md" "6e80c662708984307918adfad711e15f" "site/built/index.md" "2023-07-26" "episodes/01-introduction.md" "9755639c515fdbf752422e2e59128f63" "site/built/01-introduction.md" "2023-07-26" -"episodes/02-image-basics.md" "d7e49ef016b308d80ae19d6a461855a8" "site/built/02-image-basics.md" "2024-06-07" +"episodes/02-image-basics.md" "b23ed3c7907f4c944ab0b1d11d6a92a2" "site/built/02-image-basics.md" "2024-06-18" "episodes/03-skimage-images.md" "d7890de460222e8cdf461c76cba37692" "site/built/03-skimage-images.md" "2024-06-07" "episodes/04-drawing.md" "48b42ee384b5b907d9f9b93ad0e98ce8" "site/built/04-drawing.md" "2024-06-07" "episodes/05-creating-histograms.md" "4abbd123ba97d63c795398be6f6b7621" "site/built/05-creating-histograms.md" "2024-03-14" @@ -12,7 +12,7 @@ "episodes/07-thresholding.md" "4d34b89c8cd33cb6bb54103f805a39b9" "site/built/07-thresholding.md" "2024-03-12" "episodes/08-connected-components.md" "79495641132337de72f9df87ce5a2d21" "site/built/08-connected-components.md" "2024-03-12" "episodes/09-challenges.md" "3e95485b1bae2c37538830225ea26598" "site/built/09-challenges.md" "2024-03-12" -"instructors/instructor-notes.md" "b1c166a544eb4b9b91f3ac8f2dafd549" "site/built/instructor-notes.md" "2023-05-12" +"instructors/instructor-notes.md" "e8e378a5dfaec7b2873d788be85003ce" "site/built/instructor-notes.md" "2024-06-18" "learners/discuss.md" "ad762c335f99400dc2cd1a8aad36bdbd" "site/built/discuss.md" "2023-07-26" "learners/edge-detection.md" "fdbcee7436e104e6587e1cb40cd37d18" "site/built/edge-detection.md" "2023-08-16" "learners/prereqs.md" "7ca883d3d01d18c98ce7524ed297e56c" "site/built/prereqs.md" "2023-07-26" diff --git a/pkgdown.yml b/pkgdown.yml index ad69cf4d7..e9e416352 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -2,5 +2,5 @@ pandoc: 3.1.11 pkgdown: 2.0.9 pkgdown_sha: ~ articles: {} -last_built: 2024-06-18T09:13Z +last_built: 2024-06-18T14:12Z diff --git a/sitemap.xml b/sitemap.xml index 465dc98ec..88df8002c 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -45,6 +45,9 @@