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Source  : 0048fe6
Branch  : main
Author  : Toby Hodges <tobyhodges@carpentries.org>
Time    : 2023-12-08 14:46:42 +0000
Message : Merge pull request #309 from bear-rsg/minor-typos

Minor typos and suggestions

Author: actions-user

02-image-basics.md

@@ -960,7 +960,7 @@ the images may be of sufficient quality for your work.
 It all depends on how much quality you need,
 and what restrictions you have on image storage space.
 Another consideration may be *where* the images are stored.
-For example,if your images are stored in the cloud and therefore
+For example, if your images are stored in the cloud and therefore
 must be downloaded to your system before you use them,
 you may wish to use a compressed image format to speed up file transfer time.
 

03-skimage-images.md

@@ -54,7 +54,7 @@ chair = iio.imread(uri="data/chair.jpg")
 
 We use the `iio.imread()` function to read a JPEG image entitled **chair.jpg**.
 Imageio reads the image, converts it from JPEG into a NumPy array,
-and returns the array; we save the array in a variable named `image`.
+and returns the array; we save the array in a variable named `chair`.
 
 Next, we will do something with the image:
 
@@ -459,9 +459,10 @@ red box that is drawn around the words.
 
 ![](data/board.jpg){alt='Whiteboard image'}
 
-Using the same display technique we have used throughout this course,
+Using `matplotlib.pyplot.imshow` 
 we can determine the coordinates of the corners of the area we wish to extract
-by hovering the mouse near the points of interest and noting the coordinates.
+by hovering the mouse near the points of interest and noting the coordinates 
+(remember to run `%matplotlib widget` first if you haven't already).
 If we do that, we might settle on a rectangular
 area with an upper-left coordinate of *(135, 60)*
 and a lower-right coordinate of *(480, 150)*,
@@ -470,7 +471,7 @@ as shown in this version of the whiteboard picture:
 ![](fig/board-coordinates.jpg){alt='Whiteboard coordinates'}
 
 Note that the coordinates in the preceding image are specified in *(cx, ry)* order.
-Now if our entire whiteboard image is stored as an scikit-image image named `image`,
+Now if our entire whiteboard image is stored as a NumPy array named `image`,
 we can create a new image of the selected region with a statement like this:
 
 `clip = image[60:151, 135:481, :]`
@@ -553,14 +554,13 @@ maize_roots = iio.imread(uri="data/maize-root-cluster.jpg")
 fig, ax = plt.subplots()
 plt.imshow(maize_roots)
 
-# extract, display, and save sub-image
-# WRITE YOUR CODE TO SELECT THE SUBIMAGE NAME clip HERE:
+# extract and display sub-image
 clipped_maize = maize_roots[0:400, 275:550, :]
 fig, ax = plt.subplots()
 plt.imshow(clipped_maize)
 
 
-# WRITE YOUR CODE TO SAVE clip HERE
+# save sub-image
 iio.imwrite(uri="data/clipped_maize.jpg", image=clipped_maize)
 ```
 
@@ -571,11 +571,11 @@ iio.imwrite(uri="data/clipped_maize.jpg", image=clipped_maize)
 :::::::::::::::::::::::::::::::::::::::: keypoints
 
 - Images are read from disk with the `iio.imread()` function.
-- We create a window that automatically scales the displayed image with Matplotlib and calling `show()` on the global figure object.
+- We create a window that automatically scales the displayed image with Matplotlib and calling `imshow()` on the global figure object.
 - Colour images can be transformed to grayscale using `ski.color.rgb2gray()` or, in many cases, be read as grayscale directly by passing the argument `mode="L"` to `iio.imread()`.
 - We can resize images with the `ski.transform.resize()` function.
 - NumPy array commands, such as `image[image < 128] = 0`, can be used to manipulate the pixels of an image.
 - Array slicing can be used to extract sub-images or modify areas of images, e.g., `clip = image[60:150, 135:480, :]`.
-- Metadata is not retained when images are loaded as scikit-image images.
+- Metadata is not retained when images are loaded as NumPy arrays using `iio.imread()`.
 
 ::::::::::::::::::::::::::::::::::::::::::::::::::

md5sum.txt

@@ -4,8 +4,8 @@
 "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" "37de5915c4fc80cc12af44d98c31321b" "site/built/02-image-basics.md" "2023-11-24"
-"episodes/03-skimage-images.md" "eb0da8ebdea3bf84510b22581b790e67" "site/built/03-skimage-images.md" "2023-10-13"
+"episodes/02-image-basics.md" "30630cc141643700495c2038f2cc9f68" "site/built/02-image-basics.md" "2023-12-08"
+"episodes/03-skimage-images.md" "063fa4bb5032702c0196b0d953d94474" "site/built/03-skimage-images.md" "2023-12-08"
 "episodes/04-drawing.md" "9d78a765f5e9747ffc2aa43a4a5a414d" "site/built/04-drawing.md" "2023-09-05"
 "episodes/05-creating-histograms.md" "bdcf983127c242eb995605038598d09f" "site/built/05-creating-histograms.md" "2023-09-18"
 "episodes/06-blurring.md" "008ba23277efaed038691178e99c135b" "site/built/06-blurring.md" "2023-09-05"