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| 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']}") | |