Final changes on 4/3. First test images using camera of mini board and first...

Final changes on 4/3. First test images using camera of mini board and first images of chess pieces. Take more tests tomorrow

board_detector.py

@@ -104,12 +104,6 @@ def filter_lines(lines, min_distance):
 def find_board(img):
     vertical_lines, horizontal_lines = find_longest_lines(img)
 
-    if (len(vertical_lines) != 9 or len(horizontal_lines) != 9):
-        print("Error: Grid does not match expected 9x9")
-        print("# of Vertical:",len(vertical_lines))
-        print("# of Horizontal:",len(horizontal_lines))
-        return None, None
-
     # create bitmasks for vert and horiz so we can get lines and intersections
     height, width, _ = img.shape
     vertical_mask = np.zeros((height, width), dtype=np.uint8)
@@ -156,6 +150,12 @@ def find_board(img):
         # cv2.destroyAllWindows()
         display_img([board_lines_img])
 
+    if (len(vertical_lines) != 9 or len(horizontal_lines) != 9):
+        print("Error: Grid does not match expected 9x9")
+        print("# of Vertical:",len(vertical_lines))
+        print("# of Horizontal:",len(horizontal_lines))
+        return None, None
+
     # find largest contour and get rid of it because it contains weird edges from lines
     max_area = 100000 # we're assuming board is going to be big (hopefully to speed up computation on raspberry pi)
     largest = -1

game.py

@@ -32,7 +32,7 @@ class ChessGame:
         init_show_cv(self.show_cv)
 
 
-        preview_config = self.picam2.create_preview_configuration(main={"size": (512, 512)})
+        preview_config = self.picam2.create_preview_configuration(main={"size": (2000, 2000)})
         self.picam2.configure(preview_config)
         if (self.show_cam):
             self.picam2.start_preview(Preview.QTGL)
@@ -50,14 +50,15 @@ class ChessGame:
             # orig_img = cv2.imread('test_images/board1.jpg') # TODO - CHANGE TO MAKE IT RECEIVE INPUT FROM CAMERA
             orig_img = self.take_pic()
         h,w,c = orig_img.shape
-        cropped_img = orig_img[0:h, int(w/2 - h/2 - 60):int(w/2 + h/2 + 100)]
+        cropped_img = orig_img[0:h-100, 0:w-100]
         img = cv2.resize(cropped_img, (512, 512))
+        # img = orig_img
 
         if (self.show_cv):
             # cv2.imshow('Original Image Before Processing', img)
             # cv2.waitKey(0)
             # cv2.destroyAllWindows()
-            display_img([img])
+            display_img([orig_img, img])
 
         warped_img, sorted_warped_points = find_board(img)
 
@@ -96,7 +97,7 @@ class ChessGame:
         self.img_idx += 1
         time.sleep(2)
         img_txt = 'board' + str(self.img_idx) + '.jpg'
-        print(img_txt)
+        # print(img_txt)
         img_path = os.path.join('game_images', img_txt)
         metadata = self.picam2.capture_file(img_path)
         return cv2.imread(img_path)