relative paths

code/chessboard_detection.py

@@ -126,4 +126,3 @@ def find_chessboard_from_image(img):
         maxY = y + h if y + h > maxY else maxY
 
     return True, img, minX, minY, maxX, maxY, img
-

code/game_state_classes.py

@@ -44,7 +44,7 @@ def __init__(self):
         self.expected_move_to_detect = "" #This variable stores the move we should see next, if we don't see the right one in the next iteration, we wait and try again. This solves the slow transition problem: for instance, starting with e2e4, the screenshot can happen when the pawn is on e3, that is a possible position. We always have to double check that the move is done.
         self.previous_chessboard_image = [] #Storing the chessboard image from previous iteration
         self.executed_moves = [] #Store the move detected on san format
-        self.engine = chess.engine.SimpleEngine.popen_uci("/Users/sebastiankoch/OnlineChessBot/engine/stockfish-10-64")
+        self.engine = chess.engine.SimpleEngine.popen_uci("engine/stockfish-11-64")
         self.board = chess.Board() #This object comes from the "chess" package, the moves are stored inside it (and it has other cool features such as showing all the "legal moves")
         self.board_position_on_screen = []
         self.sct = mss.mss()
@@ -152,12 +152,16 @@ def register_move_if_needed(self):
         diff = cv2.absdiff(new_board, old_board)
         if diff.mean() == 0:
             return False, ([], []), (old_board, new_board)
-        cv2.waitKey(50)
+        cv2.waitKey(100)
         new_board2 = chessboard_detection.get_chessboard(self)
-        while cv2.absdiff(new_board,new_board2).mean()>0:
+        # cv2.waitKey(10)
+        # new_board3 = chessboard_detection.get_chessboard(self)
+        while cv2.absdiff(new_board,new_board2).mean()>0:# or cv2.absdiff(new_board,new_board3).mean()>0:
             new_board = chessboard_detection.get_chessboard(self)
-            cv2.waitKey(50)
+            cv2.waitKey(100)
             new_board2 = chessboard_detection.get_chessboard(self)
+            # cv2.waitKey(10)
+            # new_board3 = chessboard_detection.get_chessboard(self)
 
 
 
@@ -236,13 +240,13 @@ def play_next_move(self,factor,strength,variance):
             else:
                 print('depth_mode')
                 move_time = time.time()
-                engine_process = self.engine.play(self.board, chess.engine.Limit(depth=20))
+                engine_process = self.engine.play(self.board, chess.engine.Limit(depth=26))
                 move_time = time.time() - move_time
                 # engine_process = self.engine.go(depth=25)#
         except EngineTerminatedError:
             print('restart')
-            # self.engine = chess.uci.popen_engine("/Users/sebastiankoch/OnlineChessBot/engine/stockfish-10-64")
-            self.engine = chess.engine.SimpleEngine.popen_uci("/Users/sebastiankoch/OnlineChessBot/engine/stockfish-10-64")
+            # self.engine = chess.uci.popen_engine("engine/stockfish-11-64")
+            self.engine = chess.engine.SimpleEngine.popen_uci("engine/stockfish-11-64")
             return 0,0
 
         postthink = time.time()
@@ -269,8 +273,7 @@ def play_next_move(self,factor,strength,variance):
         # Having the positions we can drag the piece:
         pyautogui.moveTo(int(centerXOrigin), int(centerYOrigin), 0.0001)
         # pyautogui.click(clicks=2,button='left')
-        pyautogui.dragTo(int(centerXOrigin), int(centerYOrigin) + 1, button='left',
-                         duration=0.0001)  # This small click is used to get the focus back on the browser window
+        pyautogui.dragTo(int(centerXOrigin), int(centerYOrigin) + 1, button='left', duration=0.2)  # This small click is used to get the focus back on the browser window
 
         pyautogui.dragTo(int(centerXDest), int(centerYDest), button='left', duration=0.11)
         # print(f"mousetime: {time.time()-mousetime}")
@@ -326,7 +329,7 @@ def build_fen(self,we_are_white,rochade = 'KQkq' ):
 
         self.moves_to_detect_before_use_engine = 0  # if v.get() else 1
 
-        pieces = sorted(os.listdir('/Users/sebastiankoch/OnlineChessBot/pieces'))
+        pieces = sorted(os.listdir('pieces'))
 
         vis_glob = np.array([])
         piece_notation = ['b', 'k', 'n', 'p', 'q', 'r', '*', 'B', 'K', 'N', 'P', 'Q', 'R']
@@ -342,7 +345,7 @@ def build_fen(self,we_are_white,rochade = 'KQkq' ):
             image_list = [get_square_image(i, j, position_detection) for j in (range(8) if we_are_white else reversed(range(8)))]
             answers = piece_on_square_list(image_list)
             for answer in answers:
-                im = cv2.imread(os.path.join('/Users/sebastiankoch/OnlineChessBot/pieces', pieces[answer]))
+                im = cv2.imread(os.path.join('pieces', pieces[answer]))
                 if vis.size == 0:
                     vis = im
                     fen_str += piece_notation[answer]
@@ -430,7 +433,7 @@ def our_side(self):
     #     position_detection = chessboard_detection.get_chessboard(self, (800, 800))
     #     piece_notation = ['b', 'k', 'n', 'p', 'q', 'r', '*', 'B', 'K', 'N', 'P', 'Q', 'R']
     #
-    #     pieces = sorted(os.listdir('/Users/sebastiankoch/OnlineChessBot/pieces'))
+    #     pieces = sorted(os.listdir('pieces'))
     #
     #     vis_glob = np.array([])
     #
@@ -457,7 +460,7 @@ def our_side(self):
     #         if (mod_i)%8==0 and mod_i!=0:
     #             fen_str += '/'
     #
-    #         im = cv2.imread(os.path.join('/Users/sebastiankoch/OnlineChessBot/pieces', pieces[answer]))
+    #         im = cv2.imread(os.path.join('pieces', pieces[answer]))
     #         im_list.append(im)
     #         fen_str += piece_notation[answer]
     #
@@ -507,10 +510,10 @@ def build_fen_guess_side(self):
         self.moves_to_detect_before_use_engine = 0  # if v.get() else 1
 
         fen_str = ''
-        position_detection = chessboard_detection.get_chessboard(self, (800, 800))
+        position_detection = chessboard_detection.get_chessboard(self, (1024, 1024))
         piece_notation = ['b', 'k', 'n', 'p', 'q', 'r', '*', 'B', 'K', 'N', 'P', 'Q', 'R']
 
-        pieces = sorted(os.listdir('/Users/sebastiankoch/OnlineChessBot/pieces'))
+        pieces = sorted(os.listdir('pieces'))
 
         vis_glob = np.array([])
 
@@ -533,7 +536,7 @@ def build_fen_guess_side(self):
                 if piece_notation.index('K') == answer:
                     white_king_position = i*8+j
 
-                im = cv2.imread(os.path.join('/Users/sebastiankoch/OnlineChessBot/pieces', pieces[answer]))
+                im = cv2.imread(os.path.join('pieces', pieces[answer]))
                 im_list.append(im)
                 fen_str += piece_notation[answer]
 
@@ -543,7 +546,7 @@ def build_fen_guess_side(self):
 
         print(f"-->Prediction: {prediction_time}")
 
-        if  white_king_position ==-1or  black_king_position==-1:
+        if  white_king_position ==-1 or  black_king_position==-1:
             raise NoValidPosition
         if black_king_position < white_king_position:
 

code/generate_trainset.py

@@ -21,5 +21,5 @@
     for i in range(8):
         for j in range(8):
             image =board_basics.get_square_image(i,j,resized_chessboard)
-            cv2.imwrite(f"/Users/sebastiankoch/OnlineChessBot/pieces/{i}{j}.png", image)
+            cv2.imwrite(f"pieces/{i}{j}.png", image)
 

code/ml_model.py

@@ -1,19 +1,19 @@
 
 from tensorflow.keras.models import Sequential, load_model
 def init_binary():
-    model_path = '/Users/sebastiankoch/OnlineChessBot/model_binary/binarymodel.h5'
-    model_weights_path = '/Users/sebastiankoch/OnlineChessBot/model_binary/binaryweights.hdf5'
-    # model_path = '/Users/sebastiankoch/OnlineChessBot/model_binary/modelmnis.h5'
-    # model_weights_path = '/Users/sebastiankoch/OnlineChessBot/model_binary/weightsmnist.hdf5'
+    model_path = 'model_binary/binarymodel.h5'
+    model_weights_path = 'model_binary/binaryweights.hdf5'
+    # model_path = 'model_binary/modelmnis.h5'
+    # model_weights_path = 'model_binary/weightsmnist.hdf5'
     global binary_model
     binary_model = load_model(model_path)
     binary_model.load_weights(model_weights_path)
     # from tensorflow.keras.utils import plot_model
     # plot_model(model, to_file='model.png')
 
 def init_class():
-    model_path = '/Users/sebastiankoch/OnlineChessBot/model_class/model128.h5'
-    model_weights_path = '/Users/sebastiankoch/OnlineChessBot/model_class/weights128.hdf5'
+    model_path = 'model_class/model128.h5'
+    model_weights_path = 'model_class/weights128.hdf5'
     global class_model
     class_model = load_model(model_path)
     class_model.load_weights(model_weights_path)

code/rebuildBoard.py

@@ -23,7 +23,7 @@
     resized_chessboard = chessboard_detection.get_chessboard(game_state,resolution=(800,800))
     # cv2.imshow('test',resized_chessboard)
     # cv2.waitKey(0)
-    pieces = sorted(os.listdir('/Users/sebastiankoch/OnlineChessBot/pieces'))
+    pieces = sorted(os.listdir('pieces'))
     vis = np.array([])
     vis_glob = np.array([])
     piece_notation =['b','k','n','p','q','r','*','B','K','N','P','Q','R']
@@ -44,7 +44,7 @@
         for j in order2:
             image = board_basics.get_square_image(i,j,resized_chessboard)
             answer = board_basics.piece_on_square(image)
-            im = cv2.imread(os.path.join('/Users/sebastiankoch/OnlineChessBot/pieces',pieces[answer]))
+            im = cv2.imread(os.path.join('pieces',pieces[answer]))
             if vis.size==0:
                 vis=im
                 fen_str+=piece_notation[answer]

code/test_mlmodel.py

@@ -8,9 +8,9 @@
 if __name__ == '__main__':
 
     ml_model.init_binary()
-    squares=os.listdir('/Users/sebastiankoch/OnlineChessBot/pieces')
+    squares=os.listdir('pieces')
     for name in squares:
-        square= cv2.imread(os.path.join('/Users/sebastiankoch/OnlineChessBot/pieces',name),0)
+        square= cv2.imread(os.path.join('pieces',name),0)
         # square = cv2.resize(square,(32,32))
         square = cv2.resize(square,(32,32))