How to convert padded border of transformed image to black

[Ryan-Lima]

Is there a simple way to make it so the padded border that is added on a registered image which is smaller than the reference image is black instead of some unpredictable grey/brown color. I trained a neural network on thousands of images with black borders (from rectification) and I am worried about what will happen when I start predicting on images with brown/gray borders.

images come out like this:

but I need them to be like this:

One issue is that the border images vary in pixel values from image to image and arent even homogenous within a single image. Which ruined my attempt at the following:
border = np.where((timg[:,:,0] ==114 ) & (timg[:,:,1]==101) & (timg[:,:,2] ==86) )
timg[border] = (0,0,0)

[matejak]

Hello, the _similarity function accepts bgval as argument, but similarity doesn't, so you can make a PR that propagates it upwards, possibly to the cli.