remove unused find_features_of_contours

sbb_newspapers_org_image/eynollah.py

@@ -33,7 +33,6 @@ from .utils.contour import (
     filter_contours_area_of_image_tables,
     filter_contours_area_of_image,
     find_contours_mean_y_diff,
-    find_features_of_contours,
     find_new_features_of_contoures,
     get_text_region_boxes_by_given_contours,
     get_textregion_contours_in_org_image,

sbb_newspapers_org_image/unused.py

@@ -3057,3 +3057,16 @@ def return_bonding_box_of_contours(cnts):
         boxes_tot.append(box)
     return boxes_tot
 
+def find_features_of_contours(contours_main):
+
+    areas_main = np.array([cv2.contourArea(contours_main[j]) for j in range(len(contours_main))])
+    M_main = [cv2.moments(contours_main[j]) for j in range(len(contours_main))]
+    cx_main = [(M_main[j]["m10"] / (M_main[j]["m00"] + 1e-32)) for j in range(len(M_main))]
+    cy_main = [(M_main[j]["m01"] / (M_main[j]["m00"] + 1e-32)) for j in range(len(M_main))]
+    x_min_main = np.array([np.min(contours_main[j][:, 0, 0]) for j in range(len(contours_main))])
+    x_max_main = np.array([np.max(contours_main[j][:, 0, 0]) for j in range(len(contours_main))])
+
+    y_min_main = np.array([np.min(contours_main[j][:, 0, 1]) for j in range(len(contours_main))])
+    y_max_main = np.array([np.max(contours_main[j][:, 0, 1]) for j in range(len(contours_main))])
+
+    return y_min_main, y_max_main, areas_main

sbb_newspapers_org_image/utils/contour.py

@@ -26,19 +26,6 @@ def find_contours_mean_y_diff(contours_main):
     cy_main = [(M_main[j]["m01"] / (M_main[j]["m00"] + 1e-32)) for j in range(len(M_main))]
     return np.mean(np.diff(np.sort(np.array(cy_main))))
 
-def find_features_of_contours(contours_main):
-
-    areas_main = np.array([cv2.contourArea(contours_main[j]) for j in range(len(contours_main))])
-    M_main = [cv2.moments(contours_main[j]) for j in range(len(contours_main))]
-    cx_main = [(M_main[j]["m10"] / (M_main[j]["m00"] + 1e-32)) for j in range(len(M_main))]
-    cy_main = [(M_main[j]["m01"] / (M_main[j]["m00"] + 1e-32)) for j in range(len(M_main))]
-    x_min_main = np.array([np.min(contours_main[j][:, 0, 0]) for j in range(len(contours_main))])
-    x_max_main = np.array([np.max(contours_main[j][:, 0, 0]) for j in range(len(contours_main))])
-
-    y_min_main = np.array([np.min(contours_main[j][:, 0, 1]) for j in range(len(contours_main))])
-    y_max_main = np.array([np.max(contours_main[j][:, 0, 1]) for j in range(len(contours_main))])
-
-    return y_min_main, y_max_main, areas_main
 
 def get_text_region_boxes_by_given_contours(contours):