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 <suryak@udel.edu>, wrote:

I’m sorry,

Its

...

...

np.abs(im1 - im2)

Surya

...

On Apr 20, 2017, at 7:10 PM, Surya Kasturi <suryak@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