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Parametrize OCR for handling curved lines
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parent
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commit
928a548b70
2 changed files with 6 additions and 6 deletions
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@ -5353,7 +5353,7 @@ class Eynollah_ocr:
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self.b_s = int(batch_size)
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self.b_s = int(batch_size)
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else:
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else:
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self.model_ocr_dir = dir_models + "/model_step_1150000_ocr"#"/model_step_125000_ocr"#"/model_step_25000_ocr"#"/model_step_1050000_ocr"#"/model_0_ocr_cnnrnn"#"/model_23_ocr_cnnrnn"
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self.model_ocr_dir = dir_models + "/model_step_1225000_ocr"#"/model_step_125000_ocr"#"/model_step_25000_ocr"#"/model_step_1050000_ocr"#"/model_0_ocr_cnnrnn"#"/model_23_ocr_cnnrnn"
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model_ocr = load_model(self.model_ocr_dir , compile=False)
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model_ocr = load_model(self.model_ocr_dir , compile=False)
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self.prediction_model = tf.keras.models.Model(
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self.prediction_model = tf.keras.models.Model(
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@ -5642,7 +5642,7 @@ class Eynollah_ocr:
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if self.draw_texts_on_image:
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if self.draw_texts_on_image:
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total_bb_coordinates.append([x,y,w,h])
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total_bb_coordinates.append([x,y,w,h])
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w_scaled = w * image_height/float(h)
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w_scaled = w * image_height/float(h)
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img_poly_on_img = np.copy(img)
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img_poly_on_img = np.copy(img)
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@ -5684,7 +5684,7 @@ class Eynollah_ocr:
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img_crop_bin = img_crop_bin[y_n:y_n+h_n, x_n:x_n+w_n, :]
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img_crop_bin = img_crop_bin[y_n:y_n+h_n, x_n:x_n+w_n, :]
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img_crop_bin[mask_poly==0] = 255
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img_crop_bin[mask_poly==0] = 255
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if mask_poly[:,:,0].sum() /float(w_n*h_n) < 0.50 and w_scaled > 100:
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if mask_poly[:,:,0].sum() /float(w_n*h_n) < 0.50 and w_scaled > 90:
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if self.prediction_with_both_of_rgb_and_bin:
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if self.prediction_with_both_of_rgb_and_bin:
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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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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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else:
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@ -5698,7 +5698,7 @@ class Eynollah_ocr:
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if type_textregion=='drop-capital':
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if type_textregion=='drop-capital':
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pass
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pass
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else:
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else:
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if mask_poly[:,:,0].sum() /float(w*h) < 0.50 and w_scaled > 100:
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if mask_poly[:,:,0].sum() /float(w*h) < 0.50 and w_scaled > 90:
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if self.prediction_with_both_of_rgb_and_bin:
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if self.prediction_with_both_of_rgb_and_bin:
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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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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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else:
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@ -5708,7 +5708,7 @@ class Eynollah_ocr:
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if not self.export_textline_images_and_text:
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if not self.export_textline_images_and_text:
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if w_scaled < 640:#1.5*image_width:
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if w_scaled < 530:#640:#1.5*image_width:
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img_fin = preprocess_and_resize_image_for_ocrcnn_model(img_crop, image_height, image_width)
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img_fin = preprocess_and_resize_image_for_ocrcnn_model(img_crop, image_height, image_width)
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cropped_lines.append(img_fin)
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cropped_lines.append(img_fin)
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if angle_degrees > 15:
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if angle_degrees > 15:
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@ -241,7 +241,7 @@ def return_splitting_point_of_image(image_to_spliited):
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peaks_real = peaks_real[(peaks_real<width2) & (peaks_real>width1)]
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peaks_real = peaks_real[(peaks_real<width2) & (peaks_real>width1)]
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arg_sort = np.argsort(sum_smoothed[peaks_real])
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arg_sort = np.argsort(sum_smoothed[peaks_real])
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peaks_sort_4 = peaks_real[arg_sort][::-1][:4]
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peaks_sort_4 = peaks_real[arg_sort][::-1][:3]
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return np.sort(peaks_sort_4)
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return np.sort(peaks_sort_4)
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