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Fix: commented thresholding, now using model

This commit is contained in:
Emilio Martinez 2023-10-09 17:18:46 -03:00
parent f7616c16dd
commit 51410a1fd3
1 changed files with 8 additions and 8 deletions
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16
KAIR/main_test_drunet_captures.py
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@ -149,23 +149,23 @@ def main(json_path='options/train_drunet_finetuning.json'):
# Inference
## With abs value/max-entropy thresholding
L_visual = test_data['L']
L_img = util.tensor2uint(L_visual)
# L_visual = test_data['L']
# L_img = util.tensor2uint(L_visual)
# E_img = np.abs(L_img[:,:,0] + 1j*L_img[:,:,1])
# E_img = (255 * (E_img/np.max(E_img))).astype("uint8")
E_img = util.max_entropy_init(L_img) # using global thresholding
# E_img = util.max_entropy_init(L_img) # using global thresholding
H_visual = test_data['H']
H_img = util.tensor2uint(H_visual)
## With drunet
# With drunet
# Load image
# E_visual = model(test_data['L'].cuda())
# E_img = util.tensor2uint(E_visual)
E_visual = model(test_data['L'].cuda())
E_img = util.tensor2uint(E_visual)
# H_visual = test_data['H']
# H_img = util.tensor2uint(H_visual)
H_visual = test_data['H']
H_img = util.tensor2uint(H_visual)
# -----------------------
# save estimated image E