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https://github.com/qurator-spk/eynollah.git
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remove unused find_features_of_contours
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parent
823592126e
commit
e2ae6dbd44
3 changed files with 13 additions and 14 deletions
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@ -33,7 +33,6 @@ from .utils.contour import (
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filter_contours_area_of_image_tables,
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filter_contours_area_of_image_tables,
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filter_contours_area_of_image,
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filter_contours_area_of_image,
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find_contours_mean_y_diff,
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find_contours_mean_y_diff,
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find_features_of_contours,
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find_new_features_of_contoures,
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find_new_features_of_contoures,
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get_text_region_boxes_by_given_contours,
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get_text_region_boxes_by_given_contours,
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get_textregion_contours_in_org_image,
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get_textregion_contours_in_org_image,
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@ -3057,3 +3057,16 @@ def return_bonding_box_of_contours(cnts):
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boxes_tot.append(box)
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boxes_tot.append(box)
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return boxes_tot
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return boxes_tot
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def find_features_of_contours(contours_main):
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areas_main = np.array([cv2.contourArea(contours_main[j]) for j in range(len(contours_main))])
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M_main = [cv2.moments(contours_main[j]) for j in range(len(contours_main))]
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cx_main = [(M_main[j]["m10"] / (M_main[j]["m00"] + 1e-32)) for j in range(len(M_main))]
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cy_main = [(M_main[j]["m01"] / (M_main[j]["m00"] + 1e-32)) for j in range(len(M_main))]
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x_min_main = np.array([np.min(contours_main[j][:, 0, 0]) for j in range(len(contours_main))])
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x_max_main = np.array([np.max(contours_main[j][:, 0, 0]) for j in range(len(contours_main))])
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y_min_main = np.array([np.min(contours_main[j][:, 0, 1]) for j in range(len(contours_main))])
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y_max_main = np.array([np.max(contours_main[j][:, 0, 1]) for j in range(len(contours_main))])
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return y_min_main, y_max_main, areas_main
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@ -26,19 +26,6 @@ def find_contours_mean_y_diff(contours_main):
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cy_main = [(M_main[j]["m01"] / (M_main[j]["m00"] + 1e-32)) for j in range(len(M_main))]
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cy_main = [(M_main[j]["m01"] / (M_main[j]["m00"] + 1e-32)) for j in range(len(M_main))]
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return np.mean(np.diff(np.sort(np.array(cy_main))))
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return np.mean(np.diff(np.sort(np.array(cy_main))))
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def find_features_of_contours(contours_main):
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areas_main = np.array([cv2.contourArea(contours_main[j]) for j in range(len(contours_main))])
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M_main = [cv2.moments(contours_main[j]) for j in range(len(contours_main))]
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cx_main = [(M_main[j]["m10"] / (M_main[j]["m00"] + 1e-32)) for j in range(len(M_main))]
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cy_main = [(M_main[j]["m01"] / (M_main[j]["m00"] + 1e-32)) for j in range(len(M_main))]
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x_min_main = np.array([np.min(contours_main[j][:, 0, 0]) for j in range(len(contours_main))])
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x_max_main = np.array([np.max(contours_main[j][:, 0, 0]) for j in range(len(contours_main))])
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y_min_main = np.array([np.min(contours_main[j][:, 0, 1]) for j in range(len(contours_main))])
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y_max_main = np.array([np.max(contours_main[j][:, 0, 1]) for j in range(len(contours_main))])
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return y_min_main, y_max_main, areas_main
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def get_text_region_boxes_by_given_contours(contours):
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def get_text_region_boxes_by_given_contours(contours):
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