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fso_vision_processor.py

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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']}")