|
|
|
@ -452,6 +452,9 @@ class Eynollah:
|
|
|
|
|
if label_p_pred[0][int(num_col - 1)] < 0.9 and img_w_new < width_early:
|
|
|
|
|
img_new = np.copy(img)
|
|
|
|
|
num_column_is_classified = False
|
|
|
|
|
elif label_p_pred[0][int(num_col - 1)] < 0.8 and img_h_new >= 8000:
|
|
|
|
|
img_new = np.copy(img)
|
|
|
|
|
num_column_is_classified = False
|
|
|
|
|
else:
|
|
|
|
|
img_new = resize_image(img, img_h_new, img_w_new)
|
|
|
|
|
num_column_is_classified = True
|
|
|
|
@ -2831,7 +2834,7 @@ class Eynollah:
|
|
|
|
|
self.reset_file_name_dir(os.path.join(self.dir_in,img_name))
|
|
|
|
|
|
|
|
|
|
img_res, is_image_enhanced, num_col_classifier, num_column_is_classified = self.run_enhancement(self.light_version)
|
|
|
|
|
|
|
|
|
|
print(img_res.shape)
|
|
|
|
|
self.logger.info("Enhancing took %.1fs ", time.time() - t0)
|
|
|
|
|
|
|
|
|
|
t1 = time.time()
|
|
|
|
|