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I took a quick peek at the stitcher API

it appears that you can run estimateTransform() separately from composePanorama(), with different images. give it a try.

you would split your 5-channel image into its planes (numpy slice, img[..., 0] for first channel plane; if the api complains, try making a copy of the plane to make it contiguous in memory), run them through the composition method, then reassemble them (np.dstack)

I took a quick peek at the stitcher API

it recommends that you familiarize yourself with its pipeline

it appears that you can run estimateTransform() separately from composePanorama(), with different images. give it a try.

you would split your 5-channel image into its planes (numpy slice, img[..., 0] for first channel plane; if the api complains, try making a copy of the plane to make it contiguous in memory), run them through the composition method, then reassemble them (np.dstack)

I took a quick peek at the stitcher API

it recommends that you familiarize yourself with its pipeline

it appears that you can run estimateTransform() separately from composePanorama(), with different images. give it a try.

you would split your 5-channel image into its planes (numpy slice, literally img[..., 0] 0] for first channel plane; if the api complains, try making a copy of the plane to make it contiguous in memory), run them through the composition method, then reassemble them (np.dstack)

I took a quick peek at the stitcher API

it recommends that you familiarize yourself with its pipeline

it appears that you can run estimateTransform() separately from composePanorama(), with different images. give it a try.

you would split your 5-channel image into its planes (numpy slice, literally img[..., 0]img[:,:,0] for first channel plane; if the api complains, try making a copy of the plane to make it contiguous in memory), run them through the composition method, then reassemble them (np.dstack)