Hi Surya, Yes, test images would be helpful. My intuition without having test data is that you have some underflow errors in the numpy call, which cv2 avoids with some preprocessing:
In [1]: im0 = np.array([64], dtype=np.uint8) In [2]: im1 = np.array([65], dtype=np.uint8) In [3]: np.abs(im0 - im1) Out[3]: array([255], dtype=uint8) This is the correct implementation in NumPy: In [6]: np.maximum(im0, im1) - np.minimum(im0, im1) Out[6]: array([1], dtype=uint8) Juan. On 21 Apr 2017, 9:12 AM +1000, Surya Kasturi <sur...@udel.edu>, wrote: > I’m sorry, > > Its > > >> np.abs(im1 - im2) > > > Surya > > > > > > > > On Apr 20, 2017, at 7:10 PM, Surya Kasturi <sur...@udel.edu> wrote: > > > > Hey, > > > > I’m doing absolute difference between two images and found that the results > > from opencv and scikit-image are different > > > > >> im1 = imread(“file1.jpg”) > > >> im2 = imread(“file2.jpg”) > > >> > > >> cv2.absdiff(im1, im2) > > >> np.abs(im1, im2) > > > > I was expecting exactly same result.. could anyone please let me know why > > I’m observing slightly different results. > > > > (I could post images if you’d like) > > > > Thanks > > Surya > > > > _______________________________________________ > scikit-image mailing list > scikit-image@python.org > https://mail.python.org/mailman/listinfo/scikit-image
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