added imutils to requirements

few changes in table_parsig.py bc of a pull

requirements.txt

@@ -2,3 +2,4 @@ opencv-python~=4.5.5.62
 numpy~=1.22.1
 pdf2image~=1.16.0
 matplotlib~=3.5.1
+imutils~=0.5.4

table_parsing/table_parsig.py

@@ -1,14 +1,13 @@
 from itertools import count
 
 import cv2
+import imutils
 import numpy as np
 import pdf2image
 from matplotlib import pyplot as plt
-import imutils
 
 
 def parse(image: np.array):
-
     gray_scale = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
     blurred = cv2.GaussianBlur(gray_scale, (5, 5), 1)
     thresh = cv2.threshold(blurred, 253, 255, cv2.THRESH_BINARY)[1]
@@ -30,10 +29,93 @@ def parse(image: np.array):
         approx = cv2.approxPolyDP(c, 0.04 * peri, True)
         yield cv2.boundingRect(approx)
 
+def parse_tables(image: np.array, rectangle):
+    gray_scale = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    th1, img_bin = cv2.threshold(gray_scale, 200, 255, cv2.THRESH_BINARY)
+    img_bin = ~img_bin
+
+    line_min_width = 5
+    kernel_h = np.ones((1, line_min_width), np.uint8)
+    kernel_v = np.ones((line_min_width, 1), np.uint8)
+
+    img_bin_h = cv2.morphologyEx(img_bin, cv2.MORPH_OPEN, kernel_h)
+    img_bin_v = cv2.morphologyEx(img_bin, cv2.MORPH_OPEN, kernel_v)
+    # find_and_close_internal_gaps(img_bin_v)
+    img_bin_final = img_bin_h | img_bin_v
+    plt.imshow(img_bin_final)
+    # find_and_close_internal_gaps(img_bin_final)
+    # find_and_close_edges(img_bin_final)
+
+    _, labels, stats, _ = cv2.connectedComponentsWithStats(~img_bin_final, connectivity=8, ltype=cv2.CV_32S)
+    return labels, stats
+
+
+def filter_unconnected_cells(stats):
+    filtered_cells = []
+    # print(stats)
+    for left, middle, right in zip(stats[0:], stats[1:],
+                                   list(stats[2:]) + [np.array([None, None, None, None, None])]):
+        x, y, w, h, area = middle
+        if w > 35 and h > 13 and area > 500:
+            if right[1] is None:
+                if y == left[1] or x == left[0]:
+                    filtered_cells.append(middle)
+            else:
+                if y == left[1] or y == right[1] or x == left[0] or x == right[0]:
+                    filtered_cells.append(middle)
+    return filtered_cells
+
+def find_and_close_edges(img_bin_final):
+    contours, hierarchy = cv2.findContours(img_bin_final, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+    for cnt in contours:
+        missing_external_edges = True
+        left = tuple(cnt[cnt[:, :, 0].argmin()][0])
+        right = tuple(cnt[cnt[:, :, 0].argmax()][0])
+        top = tuple(cnt[cnt[:, :, 1].argmin()][0])
+        bottom = tuple(cnt[cnt[:, :, 1].argmax()][0])
+        topleft = [left[0], top[1]]
+        bottomright = [right[0], bottom[1]]
+        for arr in cnt:
+            if np.array_equal(arr, np.array([bottomright])) or np.array_equal(arr, np.array([topleft])):
+                missing_external_edges = False
+                break
+
+        if missing_external_edges and (bottomright[0] - topleft[0]) * (bottomright[1] - topleft[1]) >= 50000:
+            cv2.rectangle(img_bin_final, tuple(topleft), tuple(bottomright), (255, 255, 255), 2)
+            # print("missing cell detectet rectangle drawn")
+
+    return img_bin_final
+
+def annotate_image(image, stats):
+    stats = filter_unconnected_cells(stats)
+    for stat in stats:
+        x, y, w, h, area = stat
+        cv2.rectangle(image, (x, y), (x + w, y + h), (255, 0, 255), 2)
+        for i, (s, v) in enumerate(zip(["x", "y", "w", "h"], [x, y, w, h])):
+            anno = f"{s} = {v}"
+            xann = int(x + 5)
+            yann = int(y + h - (20 * (i + 1)))
+            cv2.putText(image, anno, (xann, yann), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 0, 255), 2)
+
+    return image
 
 def parse_tables_in_pdf(pages):
     return zip(map(parse, pages), count())
 
+# def annotate_tables_in_pdf(pdf_path, page_index=1):
+#     # timeit()
+#     page = pdf2image.convert_from_path(pdf_path, first_page=page_index + 1, last_page=page_index + 1)[0]
+#     page = np.array(page)
+#
+#     _, stats = parse(page)
+#     page = annotate_image(page, stats)
+#     # print(timeit())
+#     fig, ax = plt.subplots(1, 1)
+#     fig.set_size_inches(20, 20)
+#     ax.imshow(page)
+#     plt.show()
+
 
 def annotate_boxes(image, rects):
     for rect in rects:
@@ -44,7 +126,6 @@ def annotate_boxes(image, rects):
 
 
 def annotate_tables_in_pdf(pdf_path, page_index=1):
-
     page = pdf2image.convert_from_path(pdf_path, first_page=page_index + 1, last_page=page_index + 1)[0]
     page = np.array(page)
 
@@ -54,4 +135,4 @@ def annotate_tables_in_pdf(pdf_path, page_index=1):
     fig, ax = plt.subplots(1, 1)
     fig.set_size_inches(20, 20)
     ax.imshow(page)
-    plt.show()
+    plt.show()