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ocr: make sure that image height or width is not zero
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59ea493803
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2 changed files with 20 additions and 18 deletions
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@ -5435,7 +5435,6 @@ class Eynollah_ocr:
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mask_poly = mask_poly[y:y+h, x:x+w, :]
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img_crop = img_poly_on_img[y:y+h, x:x+w, :]
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#print(file_name, angle_degrees,w*h , mask_poly[:,:,0].sum(), mask_poly[:,:,0].sum() /float(w*h) , 'didi')
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if not self.do_not_mask_with_textline_contour:
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@ -5482,9 +5481,6 @@ class Eynollah_ocr:
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img_crop, img_crop_bin = break_curved_line_into_small_pieces_and_then_merge(img_crop, mask_poly, img_crop_bin)
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else:
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img_crop, _ = break_curved_line_into_small_pieces_and_then_merge(img_crop, mask_poly)
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if not self.export_textline_images_and_text:
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if w_scaled < 750:#1.5*image_width:
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@ -124,23 +124,26 @@ def return_textlines_split_if_needed(textline_image, textline_image_bin, predict
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else:
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return None, None
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def preprocess_and_resize_image_for_ocrcnn_model(img, image_height, image_width):
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ratio = image_height /float(img.shape[0])
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w_ratio = int(ratio * img.shape[1])
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if w_ratio <= image_width:
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width_new = w_ratio
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if img.shape[0]==0 or img.shape[1]==0:
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img_fin = np.ones((image_height, image_width, 3))
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else:
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width_new = image_width
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ratio = image_height /float(img.shape[0])
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w_ratio = int(ratio * img.shape[1])
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if width_new == 0:
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width_new = img.shape[1]
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if w_ratio <= image_width:
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width_new = w_ratio
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else:
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width_new = image_width
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if width_new == 0:
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width_new = img.shape[1]
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img = resize_image(img, image_height, width_new)
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img_fin = np.ones((image_height, image_width, 3))*255
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img = resize_image(img, image_height, width_new)
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img_fin = np.ones((image_height, image_width, 3))*255
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img_fin[:,:width_new,:] = img[:,:,:]
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img_fin = img_fin / 255.
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img_fin[:,:width_new,:] = img[:,:,:]
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img_fin = img_fin / 255.
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return img_fin
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def get_deskewed_contour_and_bb_and_image(contour, image, deskew_angle):
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@ -188,7 +191,10 @@ def rotate_image_with_padding(image, angle, border_value=(0,0,0)):
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rotation_matrix[1, 2] += (new_h / 2) - center[1]
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# Perform the rotation
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rotated_image = cv2.warpAffine(image, rotation_matrix, (new_w, new_h), borderValue=border_value)
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try:
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rotated_image = cv2.warpAffine(image, rotation_matrix, (new_w, new_h), borderValue=border_value)
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except:
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rotated_image = np.copy(image)
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return rotated_image
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