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import argparse
import chess
import chess.pgn
from board_detector import find_board
from board_detector import find_pieces
from board_detector import init_show_cv
import color_analyzer
import move_translator
import cv2
import os
import time
from picamera2 import Picamera2, Preview
class ChessGame:
def __init__(self, difficulty, show_cv, show_cam, calibrate, test_img = None):
self.board = chess.Board()
self.difficulty = difficulty
self.show_cv = show_cv
self.test_img = test_img
self.left_cut = 30
self.right_cut = 290
self.top_cut = 0
self.bottom_cut = 290
def start_game(self):
print(f"Starting chess game (difficulty: {self.difficulty})")
# TODO - call initialize board in board_detector, initialize colors for color analysis,
# then loop until checkmate. also handle illegal moves (writing to screen if we end up doing that or just LEDs)
init_show_cv(self.show_cv)
preview_config = self.picam2.create_preview_configuration(main={"size": (2464, 2464)})
self.picam2.configure(preview_config)
if (self.show_cam):
self.picam2.start_preview(Preview.QTGL)
self.picam2.start()
input("Press enter to continue.")
else:
self.picam2.start()
if (self.test_img):
img_path = os.path.join('test_images', self.test_img)
orig_img = cv2.imread(img_path)
else:
# orig_img = cv2.imread('test_images/board1.jpg') # TODO - CHANGE TO MAKE IT RECEIVE INPUT FROM CAMERA
h,w,c = orig_img.shape
# w_cut = 30
# h_cut = 100
cropped_img = orig_img[self.top_cut:h-self.bottom_cut, self.left_cut:w-self.right_cut]
# cropped_img = orig_img
img = cv2.resize(cropped_img, (512, 512))
# img = orig_img
if (self.show_cv):
display_img([orig_img, img])
warped_img, sorted_warped_points = find_board(img)
if (warped_img is None):
return
color_grid = find_pieces(warped_img, sorted_warped_points)
while(1): # game loop
self.player_turn()
# handle cheating
if self.board.is_checkmate():
break
quit() # TODO - REMOVE
self.ai_turn()
if self.board.is_checkmate():
break
# game is over
def player_turn(self):
# TODO - wait for user button, then check for valid move. loop until a valid move has been made
pass
def ai_turn(self):
# TODO
# 1. use detect_pieces in color_analyzer
# 2. update internal representation of board
# 3. give to python-chess and get best move
# 4. call move_translator with argument of best move
pass
self.img_idx += 1
time.sleep(2)
img_txt = 'board' + str(self.img_idx) + '.jpg'
# print(img_txt)
img_path = os.path.join('game_images', img_txt)
metadata = self.picam2.capture_file(img_path)
return cv2.imread(img_path)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="AI Chess Robot with Computer Vision")
parser.add_argument("--difficulty", choices=["easy", "medium", "hard"],
default="medium", help="Chess AI difficulty (how far it looks ahead)")
parser.add_argument("--show_cv", action="store_true", help="Show opencv images as processing occurs during game")
parser.add_argument("--show_cam", action="store_true", help="Show persistent camera view")
parser.add_argument("--calibrate", action="store_true", help="Loop showing camera with cutoff lines first, then start game")
parser.add_argument("--test_img", help="If specified, will use said image in test_images folder rather than camera input")
args = parser.parse_args()
game = ChessGame(args.difficulty, args.show_cv, args.show_cam, args.calibrate, args.test_img)
game.start_game()