True.

adapter.py

@@ -10,24 +10,23 @@ from runner import find_homography, warp_board
 # Load base64 encoded image from stdin
 from tensor_classifier import predict_board
 
-stdin = sys.stdin.readline()
-stdin_decoded = base64.b64decode(stdin)
-img_array = np.frombuffer(stdin_decoded, dtype=np.uint8)
-camera_img = cv2.imdecode(img_array, flags=cv2.COLOR_BGR2RGB)
-camera_img = cv2.cvtColor(camera_img, cv2.COLOR_BGR2RGB)
+while True:
+    stdin = sys.stdin.readline()
+    stdin_decoded = base64.b64decode(stdin)
+    img_array = np.frombuffer(stdin_decoded, dtype=np.uint8)
+    camera_img = cv2.imdecode(img_array, flags=cv2.COLOR_BGR2RGB)
+    camera_img = cv2.cvtColor(camera_img, cv2.COLOR_BGR2RGB)
 
+    # def do_everything:
+    homography = find_homography(camera_img)
+    warped_board = warp_board(camera_img, homography)
+    occupied_squares = find_occupied_squares(warped_board)
+    board = predict_board(occupied_squares)
 
-# def do_everything:
-homography = find_homography(camera_img)
-warped_board = warp_board(camera_img, homography)
-occupied_squares = find_occupied_squares(warped_board)
-board = predict_board(occupied_squares)
+    # Finally, output to stdout for unity to read
+    result = {
+        "homography": homography.tolist(),
+        "board": board.to_array,
+    }
 
-
-# Finally, output to stdout for unity to read
-result = {
-    "homography": homography.tolist(),
-    "board": board.to_array,
-}
-
-print(json.dumps(result))
+    print(json.dumps(result))