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fix typos and link (episode 4)
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episodes/04-drawing.md

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@@ -108,7 +108,7 @@ Thus, even though we use `np.ones()` to create the mask,
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its pixel values are in fact not `1` but `True`.
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You could check this, e.g., by `print(mask[0, 0])`.
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Next, we draw a filled, rectangle on the mask:
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Next, we draw a filled rectangle on the mask:
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```python
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# Draw filled rectangle on the mask image
@@ -132,7 +132,7 @@ The function returns the rectangle as row (`rr`) and column (`cc`) coordinate ar
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## Check the documentation!
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When using an scikit-image function for the first time - or the fifth time -
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When using a scikit-image function for the first time - or the fifth time -
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it is wise to check how the function is used, via
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[the scikit-image documentation](https://scikit-image.org/docs/dev/user_guide)
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or other usage examples on programming-related sites such as
@@ -153,7 +153,7 @@ that the functions your program uses are behaving in the manner you intend.
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You may have wondered why we called the return values of the rectangle function
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`rr` and `cc`?!
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You may have guessed that `r` is short for `row` and `c` is short for `column`.
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However, the rectangle function returns mutiple rows and columns;
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However, the rectangle function returns multiple rows and columns;
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thus we used a convention of doubling the letter `r` to `rr` (and `c` to `cc`)
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to indicate that those are multiple values.
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In fact it may have even been clearer to name those variables `rows` and `columns`;
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First let's make an empty, black image with a size of 800x600 pixels.
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Recall that a colour image has three channels for the colours red, green, and blue
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(RGB, cf. [Image Basics](03-skimage-images.md)).
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(RGB, cf. [Image Basics](02-image-basics.md)).
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Hence we need to create a 3D array of shape `(600, 800, 3)` where the last dimension represents the RGB colour channels.
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```python

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