image_processor.py

import cv2
import numpy as np
from scipy import ndimage

class ImageProcessor:
    def __init__(self):
        pass

    def preprocess_image(self, image):
        """Preprocess the input image"""
        # Convert to grayscale
        if len(image.shape) == 3:
            gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        else:
            gray = image
        
        # Apply Gaussian blur
        blurred = cv2.GaussianBlur(gray, (5, 5), 0)
        
        return blurred

    def generate_depth_map(self, image):
        """Generate a depth map from the image"""
        # Preprocess the image
        processed = self.preprocess_image(image)
        
        # Use Sobel operators to detect edges
        sobel_x = cv2.Sobel(processed, cv2.CV_64F, 1, 0, ksize=3)
        sobel_y = cv2.Sobel(processed, cv2.CV_64F, 0, 1, ksize=3)
        
        # Combine the gradients
        gradient_magnitude = np.sqrt(sobel_x**2 + sobel_y**2)
        
        # Normalize the depth map
        depth_map = cv2.normalize(gradient_magnitude, None, 0, 1, cv2.NORM_MINMAX)
        
        return depth_map