pls

main.py

@@ -11,6 +11,9 @@ import os
 import heapq
 import math
 from datetime import datetime
+import sys
+
+np.set_printoptions(threshold=sys.maxsize)
 
 pieces = ['rook', 'knight']
 #pieces = ['rook', 'knight']
@@ -405,16 +408,13 @@ def load_classifier(filename):
     return joblib.load(filename)
 
 
-
-
 if __name__ == '__main__':
 
-    board = cv2.imread("whole_boards/boards_for_empty/board_1554288951.972197_.png")
+    board = cv2.imread("whole_boards/boards_for_empty/board_1554286488.605142_.png")
     warped = runner.warp_board(board)
 
     empty = 0
 
-
     files = "ABCDEFGH"
     ranks = [1, 2, 3, 4, 5, 6, 7, 8]
 
@@ -423,24 +423,58 @@ if __name__ == '__main__':
 
     for file in files:
         for rank in ranks:
+            counter = 0
+
             src = runner.get_square(warped, file, rank)
-            #src = cv2.GaussianBlur(src, (5, 5), 0)
+            width, height, _ = src.shape
-            segmentator = cv2.ximgproc.segmentation.createGraphSegmentation(sigma=0.75, k=175, min_size=750)
+            src = src[width//25:, height//25:]
+            # src = src[:-width//200, :-height//200]
+            segmentator = cv2.ximgproc.segmentation.createGraphSegmentation(sigma=0.8, k=150, min_size=700)
             segment = segmentator.processImage(src)
+
             mask = segment.reshape(list(segment.shape) + [1]).repeat(3, axis=2)
             masked = np.ma.masked_array(src, fill_value=0)
+            pls = []
             for i in range(np.max(segment)):
                 masked.mask = mask != i
+
                 y, x = np.where(segment == i)
+
                 top, bottom, left, right = min(y), max(y), min(x), max(x)
+
                 dst = masked.filled()[top: bottom + 1, left: right + 1]
+                lel = (bottom - top) * (right - left)
+                #print(f"this is lel: {lel} ")
+                #print(f"this is meh: {np.sum(mask[:,:,0])} ")
+                if f"{file}{rank}" == "H7":
+                    print("--"*20)
+                    print("H7")
+                    print(lel)
+                    print(len(y))
+                    print(np.max(segment))
+#                    print(lel)
+#                    print(np.sum(mask[:, :, 0]))
+                    print("--"*20)
+
+
+                pls.append(len(y))
+                if len(y) < (164**2)*0.65:
+                    counter += 1
+
                 cv2.imwrite(f"segment_test/segment_{datetime.utcnow().timestamp()}_{file}{rank}.jpg", dst)
 
-            if np.max(segment) >= 2:
+
+
+
+
+            if np.max(segment) > 0 and not np.all([x < (164**2)*0.2 for x in pls]) and (np.max(segment) >= 3 or np.all([x < (164**2)*0.942 for x in pls])):
                 print(f"{file}{rank} is nonempty")
                 non_empties.append([f"{file}{rank}", src])
+                print(counter)
                 print(np.max(segment))
                 empty += 1
+    print("++"*20)
+    print(counter)
     print(64-empty)
 
     for non_empty in non_empties: