class VisualProcessingAGI:
    def __init__(self):
        self.low_level_features = {}
        self.middle_level_features = {}
        self.high_level_features = {}
        
    def preprocess_image(self, image_data):
        # Simple preprocessing: convert to grayscale and normalize
        gray_image = self._convert_to_grayscale(image_data)
        normalized_image = self._normalize_image(gray_image)
        return normalized_image
    
    def _convert_to_grayscale(self, image_data):
        # Placeholder for actual conversion logic
        pass
    
    def _normalize_image(self, gray_image):
        # Placeholder for normalization logic
        pass
    
    def extract_low_level_features(self, preprocessed_image):
        self.low_level_features = {
            'edges': self._edge_detection(preprocessed_image),
            'colors': self._color_histogram(preprocessed_image)
        }
    
    def _edge_detection(self, image_data):
        # Placeholder for edge detection logic
        pass
    
    def _color_histogram(self, image_data):
        # Placeholder for color histogram calculation
        pass
    
    def extract_middle_level_features(self, preprocessed_image):
        self.middle_level_features = {
            'saliency_map': self._calculate_saliency(preprocessed_image),
            'texture': self._extract_texture(preprocessed_image)
        }
    
    def _calculate_saliency(self, image_data):
        # Placeholder for saliency map calculation
        pass
    
    def _extract_texture(self, image_data):
        # Placeholder for texture extraction logic
        pass
    
    def extract_high_level_features(self, preprocessed_image):
        self.high_level_features = {
            'object_detection': self._detect_objects(preprocessed_image),
            'contextual_information': self._gather_contextual_info(preprocessed_image)
        }
    
    def _detect_objects(self, image_data):
        # Placeholder for object detection logic
        pass
    
    def _gather_contextual_info(self, image_data):
        # Placeholder for contextual information gathering
        pass
    
    def integrate_features(self):
        combined_features = {}
        combined_features.update(self.low_level_features)
        combined_features.update(self.middle_level_features)
        combined_features.update(self.high_level_features)
        
        return combined_features
    
    def process_image(self, image_data):
        preprocessed_image = self.preprocess_image(image_data)
        self.extract_low_level_features(preprocessed_image)
        self.extract_middle_level_features(preprocessed_image)
        self.extract_high_level_features(preprocessed_image)
        return self.integrate_features()

# Example usage
if __name__ == "__main__":
    # Mock image data for demonstration purposes
    mock_image_data = "Example image data"
    
    visual_agi = VisualProcessingAGI()
    features = visual_agi.process_image(mock_image_data)
    print(features)