Create image_processor.py

image_processor.py

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+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
+