import hashlib
import time

class VisionProcessor:
    """
    Law XII Component: The Algebraic Eye (Vision Processor)
    Maps visual data (pixels/binary) to Fiber 3 (Aesthetics).
    Uses topological gradients (local differences) to find stable coordinates.
    """
    def __init__(self, m=256, k=4):
        self.m = m
        self.k = k

    def _get_coord(self, data, target_fiber=3):
        h = hashlib.sha256(data if isinstance(data, bytes) else data.encode()).digest()
        coords = [h[i % len(h)] % self.m for i in range(self.k - 1)]
        w = (target_fiber - sum(coords)) % self.m
        return tuple(coords + [w])

    def process_image_to_manifold(self, filename, image_data):
        """
        Shatters an image into topological atoms by scanning pixel 'gradients'.
        Simulates the Algebraic Eye built yesterday.
        """
        print(f"\n--- [LAW XII]: Vision Processor (Algebraic Eye) ---")
        print(f"Processing '{filename}'... size: {len(image_data)} bytes")
        
        atoms = []
        # Simulate scanning chunks of the image for 'gradients'
        # In a real system, this would be Sobel/Canny-like operations on pixels
        chunk_size = 32
        for i in range(0, len(image_data), chunk_size):
            chunk = image_data[i:i+chunk_size]
            # Calculate a 'gradient' coordinate
            coord = self._get_coord(chunk, target_fiber=3)
            atoms.append({
                "data": chunk,
                "fiber": 3,
                "coord": coord,
                "type": "visual_atom"
            })
            
        print(f"[✓] VISION SECURED: {len(atoms)} visual atoms mapped to Fiber 3.")
        return atoms

if __name__ == "__main__":
    processor = VisionProcessor()
    mock_img = b'\x89PNG\r\n\x1a\n' + b'\x00' * 120 # Mock small PNG
    atoms = processor.process_image_to_manifold("eye.png", mock_img)
    for a in atoms[:3]:
        print(f"      Visual Atom @ {a['coord']}")