Oct 9, 2016 · The HxW subrectable is always smaller than the original NxN array. So for example given an 5x5 array, find the subarray sized 2x2 that has the biggest sum of elements - therefore I can't look for subarrays sized 5x5, it has to be the HxW size, not smaller, not bigger.

Nov 13, 2020 · Output: x and y coords of HxW subarray which has the most ones within itself Similar question was answered before: Maximum subarray of size HxW within a 2D matrix but in my problem is a bit more complicated since N is huge, in …

Dec 24, 2012 · I have a MySQL table of photos and store their dimensions in a single varchar field, ie. "1024x768". Is there way to select photos above or equal to the given dimensions without having to modify the

Oct 31, 2018 · I believe it's height first. A bunch of these image processing libraries/functions use (number of channels, height, width) as their image input format.

Dec 25, 2016 · Question I want to check the ways of tiling a HxW grid with tatami mats (1x2 tiles)? But tatami filling has a special rule, which it is prohibited to make a cross with the border of the tatami ma...

The function torch.nn.functional.softmax takes two parameters: input and dim. According to its documentation, the softmax operation is applied to all slices of input along the specified dim, and w...

It is actually quite simple to create a ROI from a frame, and basically you already wrote it there at the end (ROI = frame[100:200 , 100:200]). Lets assume this is your hand with your ROI after you did the code above (image from the internet): Now if you want what it is inside the ROI as another image, you can use: ROI = frame[100:400, 200:500] # …

For example: image1 is 64x200 (HxW), while image2 is 200x64. Resizing with resize (32, ..) (image) will yield out_image1 of size 32x100, and out_image2 of size 100x32.

Aug 18, 2020 · I want to apply the mask to the image to result in a HxW (or HxWx1) tensor V where V [i,j]='the matching R\G\B value according to the mask'. Using Problem applying binary mask to an RGB image with numpy I was able to achieve the following:

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