Open Hugo-cell111 opened 9 months ago
Hi @Hugo-cell111
For the features, at each spatial location, fetch the 8 neighboring features (so 3 x 3 window) and compute the average of the L2 distances between the center and the 8 neighboring features, so for each feature, you will get a scalar representing the distance between it and its neighboors; then normalize them and plot them.
Same for the images, just this time, instead of a single vector of features (1xC), you'll have an 8x8 patch of RBG values
Hope this helps.
Hi! In the caption of Figure 2, you have mentioned "the average euclidean distance between each patch of size 20 × 20 centered at a given spatial location extracted from the input images, and its 8 neighboring patches", could you please give a more detailed illustration? Or could you provide the code? Thanks!