Use numpy to mask an image with a pattern?
image-processing, numpy, python
Solution
idx=(mask==0)
image[idx]=chex[idx]
Note that `image` has shape (800,600,3), while `idx` has shape (800,600). The rules for indexing state
if the selection tuple is smaller than n, then as many : objects as needed are added to the end of the selection tuple so that the modified selection tuple has length N.
Thus indexing arrays have a sort of broadcasting ability of their own. `idx`'s shape gets promoted to (800,600,:)
Problem
I'm using numpy to build pixel arrays. An 800x600 image is an 3-dimensional array of uint8, 800x600x3. I also have a similar array with a fixed pattern (a checkerboard, see here). I have another array, 800x600 of mask values. Where the mask is zero, I want to copy the pattern pixel to the image pixel. Where the mask is not zero, I want to leave the image pixel alone. ``` >>> image.shape (800, 600, 3) >>> chex.shape (800, 600, 3) >>> mask.shape (800, 600) ``` This feels like it should work: ``` image[mask == 0,...] = chex ``` but gives "ValueError: array is not broadcastable to correct shape". What do I use to copy chex pixels to image pixels where mask is zero?