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This fixes the size of the score array which will later be interpolated to create the final saliency map. #3

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This fixes the size of the score array which will later be interpolated to create the final saliency map. #3

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2 changes: 1 addition & 1 deletion saliency.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ def score_frame(model, history, ix, r, d, interp_func, mode='actor'):
# if d==2 then every other, which is 25% of total pixels for a 2D image)
assert mode in ['actor', 'critic'], 'mode must be either "actor" or "critic"'
L = run_through_model(model, history, ix, interp_func, mask=None, mode=mode)
scores = np.zeros((int(80/d)+1,int(80/d)+1)) # saliency scores S(t,i,j)
scores = np.zeros((int(79/d)+1,int(79/d)+1)) # saliency scores S(t,i,j)
for i in range(0,80,d):
for j in range(0,80,d):
mask = get_mask(center=[i,j], size=[80,80], r=r)
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