draft of image tracker

untested

track.py

@@ -0,0 +1,53 @@
+import cv2
+import numpy as np
+import chess
+import matplotlib.pyplot as plt
+import matplotlib.cm as cm
+
+def capture_image(url):
+    """Capture an image from the webcam stream."""
+    cap = cv2.VideoCapture(url)
+    ret, frame = cap.read()
+    cap.release()
+    return frame
+
+def extract_fen_from_image(image):
+    """Detect the chessboard from the image and extract the FEN string.
+       NOTE: This is a simplified version and might not work for all scenarios.
+       A more robust solution would involve training a model for piece detection."""
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    ret, corners = cv2.findChessboardCorners(gray, (8,8))
+    if not ret:
+        return None
+    # Here we would typically identify each square and its piece to extract the FEN.
+    # For simplicity, returning a default FEN for now.
+    return "rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1"
+
+def generate_heatmap_overlay(board_shape, aggregated_targets, cmap='viridis', alpha=0.5):
+    """Generate heatmap overlay based on aggregated targets."""
+    heatmap = np.zeros(board_shape[:2], dtype=np.uint8)
+    for square, count in aggregated_targets.items():
+        x, y = chess.SQUARE_NAMES.index(square) % 8, chess.SQUARE_NAMES.index(square) // 8
+        heatmap[y, x] = count
+    heatmap_normalized = cv2.normalize(heatmap, None, 0, 255, cv2.NORM_MINMAX)
+    heatmap_colored = cm.get_cmap(cmap)(heatmap_normalized)[:, :, :3] * 255
+    heatmap_overlay = (heatmap_colored * alpha + board_shape * (1 - alpha)).astype(np.uint8)
+    return heatmap_overlay
+
+def overlay_heatmap_on_image(image, heatmap_overlay):
+    """Overlay heatmap onto the original image."""
+    return cv2.addWeighted(image, 1, heatmap_overlay, 1, 0)
+
+if __name__ == "__main__":
+    url = "http://10.1.10.159:8000/stream.mjpg"
+    image = capture_image(url)
+    fen = extract_fen_from_image(image)
+    if fen:
+        board = chess.Board(fen)
+        moves = get_legal_moves(board)
+        aggregated_targets = aggregate_target_squares(moves)
+        heatmap_overlay = generate_heatmap_overlay(image.shape, aggregated_targets)
+        final_image = overlay_heatmap_on_image(image, heatmap_overlay)
+        cv2.imshow('Overlayed Chessboard', final_image)
+        cv2.waitKey(0)
+        cv2.destroyAllWindows()