refactoring

vidocp/figure_detection.py

@@ -3,16 +3,7 @@ import numpy as np
 from pdf2image import pdf2image
 
 from vidocp.utils import show_mpl, draw_rectangles, remove_included, remove_primary_text_regions, \
-    __detect_large_coherent_structures
-
-
-def is_large_enough(cont, min_area=10000):
-    return cv2.contourArea(cont, False) > min_area
-
-
-def has_acceptable_format(cont, max_width_to_hight_ratio=6):
-    _, _, w, h = cv2.boundingRect(cont)
-    return max_width_to_hight_ratio >= w / h >= (1 / max_width_to_hight_ratio)
+    __detect_large_coherent_structures, is_large_enough, has_acceptable_format
 
 
 def is_likely_figure(cont, min_area=5000, max_width_to_hight_ratio=6):

vidocp/redaction_detection.py

@@ -5,22 +5,7 @@ import numpy as np
 import pdf2image
 from iteration_utilities import starfilter, first
 
-from vidocp.utils import show_mpl, draw_contours
-
-
-def is_filled(hierarchy):
-    # See https://stackoverflow.com/questions/60095520/how-to-distinguish-filled-circle-contour-and-unfilled-circle-contour-in-opencv
-    return hierarchy[3] <= 0 and hierarchy[2] == -1
-
-
-def is_boxy(contour):
-    epsilon = 0.01 * cv2.arcLength(contour, True)
-    approx = cv2.approxPolyDP(contour, epsilon, True)
-    return len(approx) <= 10
-
-
-def is_large_enough(contour, min_area):
-    return cv2.contourArea(contour, False) > min_area
+from vidocp.utils import show_mpl, draw_contours, is_large_enough, is_filled, is_boxy
 
 
 def is_likely_redaction(contour, hierarchy, min_area):

vidocp/table_parsing.py

@@ -2,7 +2,7 @@ import cv2
 import numpy as np
 from pdf2image import pdf2image
 
-from vidocp.utils import show_cv2, draw_stats
+from vidocp.utils import draw_stats, show_mpl
 
 
 def add_external_contours(image, img):
@@ -52,4 +52,4 @@ def annotate_tables_in_pdf(pdf_path, page_index=1):
     stats = parse_table(page)
     page = draw_stats(page, stats)
 
-    show_cv2(page)
+    show_mpl(page)

vidocp/utils.py

@@ -202,4 +202,24 @@ def __detect_large_coherent_structures(image: np.array):
 
     cnts, _ = cv2.findContours(close, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
 
-    return cnts
+    return cnts
+
+
+def is_large_enough(cont, min_area):
+    return cv2.contourArea(cont, False) > min_area
+
+
+def has_acceptable_format(cont, max_width_to_hight_ratio):
+    _, _, w, h = cv2.boundingRect(cont)
+    return max_width_to_hight_ratio >= w / h >= (1 / max_width_to_hight_ratio)
+
+
+def is_filled(hierarchy):
+    # See https://stackoverflow.com/questions/60095520/how-to-distinguish-filled-circle-contour-and-unfilled-circle-contour-in-opencv
+    return hierarchy[3] <= 0 and hierarchy[2] == -1
+
+
+def is_boxy(contour):
+    epsilon = 0.01 * cv2.arcLength(contour, True)
+    approx = cv2.approxPolyDP(contour, epsilon, True)
+    return len(approx) <= 10