Update app.py

app.py

@@ -3,7 +3,7 @@ from transformers import DPTFeatureExtractor, DPTForDepthEstimation
 from diffusers import StableDiffusionPipeline
 import torch
 import numpy as np
-import cv2
+# import cv2
 from PIL import Image, ImageEnhance
 import open3d as o3d
 
@@ -22,12 +22,26 @@ feature_extractor = DPTFeatureExtractor.from_pretrained("Intel/dpt-large")
 depth_model = DPTForDepthEstimation.from_pretrained("Intel/dpt-large")
 
 def enhance_depth_map(depth_map):
-    """ Apply filters to enhance depth details """
-    depth_map = cv2.GaussianBlur(depth_map, (5, 5), 0)  # Smooth the depth map
-    depth_map = cv2.bilateralFilter(depth_map, 9, 75, 75)  # Preserve edges
-    depth_map = cv2.convertScaleAbs(depth_map, alpha=1.2, beta=10)  # Increase contrast
-    depth_map = cv2.Laplacian(depth_map, cv2.CV_8U)  # Sharpen details
-    return depth_map
+#    """ Apply filters to enhance depth details """
+#    depth_map = cv2.GaussianBlur(depth_map, (5, 5), 0)  # Smooth the depth map
+#    depth_map = cv2.bilateralFilter(depth_map, 9, 75, 75)  # Preserve edges
+#    depth_map = cv2.convertScaleAbs(depth_map, alpha=1.2, beta=10)  # Increase contrast
+#    depth_map = cv2.Laplacian(depth_map, cv2.CV_8U)  # Sharpen details
+
+    """ Apply alternative filters to enhance depth details without OpenCV """
+    depth_image_pil = Image.fromarray(depth_map)
+
+    # Increase contrast
+    enhancer = ImageEnhance.Contrast(depth_image_pil)
+    depth_image_pil = enhancer.enhance(1.5)
+
+    # Sharpen the depth map
+    enhancer = ImageEnhance.Sharpness(depth_image_pil)
+    depth_image_pil = enhancer.enhance(2.0)
+
+    return np.array(depth_image_pil)
+  
+#    return depth_map
 
 def generate_3d_from_text(prompt):
     # Step 1: Generate Image from Text Prompt