python - Finding a subimage inside a Numpy image -

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i have 2 numpy arrays (3-dimensional uint8) converted pil images.

i want find if first image contains second image, , if so, find out coordinates of top-left pixel inside first image match is.

is there way purely in numpy, in fast enough way, rather using (4! slow) pure python loops?

2d example:

a = numpy.array([     [0, 1,  2,  3],     [4, 5,  6,  7],     [8, 9, 10, 11] ]) b = numpy.array([     [2, 3],     [6, 7] ])

how this?

position = a.find(b)

position (0, 2).

this can done using scipy's correlate2d , using argmax find peak in cross-correlation.

here's more complete explanation of math , ideas, , examples.

if want stay in pure numpy , not use scipy, or if images large, you'd best using fft based approach cross-correlations.

edit: question asked pure numpy solution. if can use opencv, or other image processing tools, it's easier use 1 of these. example of such given piquer below, i'd recommend if can use it.


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