Update app.py

app.py

@@ -300,31 +300,13 @@ def generate_images(label_str, num_images, progress=gr.Progress()):
             
         processed_images = []
         for img in images:
-            # Convert to numpy and remove channel dimension (3,128,128 -> 128,128)
+            # Convert to grayscale (X-rays are naturally grayscale)
+            # Take the mean across RGB channels and convert to uint8
             img_np = img.cpu().permute(1, 2, 0).mean(dim=-1).numpy()
-            
-            # Normalize to 0-255
             img_np = (img_np * 255).clip(0, 255).astype(np.uint8)
             
-            # Apply bone colormap approximation (without matplotlib)
-            # This is a simplified version of the bone colormap
-            bone_cmap = np.array([
-                [0, 0, 0],       # Black
-                [25, 25, 51],     # Dark blue-gray
-                [50, 50, 102],    # Medium blue-gray
-                [76, 76, 153],    # Blue-gray
-                [101, 101, 204],  # Light blue-gray
-                [127, 127, 255],  # Very light blue
-                [153, 178, 255],  # Blue-white
-                [178, 204, 255],  # Light blue-white
-                [204, 229, 255],  # Very light blue-white
-                [229, 255, 255],  # Almost white
-                [255, 255, 255]   # White
-            ], dtype=np.uint8)
-            
-            # Apply colormap
-            colored = bone_cmap[(img_np * (len(bone_cmap)-1) / 255].astype(np.uint8)
-            pil_img = Image.fromarray(colored)
+            # Create PIL image in grayscale mode
+            pil_img = Image.fromarray(img_np, mode='L')
             
             processed_images.append(pil_img)