updates

app.py

@@ -19,7 +19,7 @@ model, transform = depth_pro.create_model_and_transforms()
 model = model.to(device)
 model.eval()
 
-def resize_image(image_path, max_size=1024):
+def resize_image(image_path, max_size=1536):
     with Image.open(image_path) as img:
         # Calculate the new size while maintaining aspect ratio
         ratio = max_size / max(img.size)
@@ -67,7 +67,7 @@ def predict_depth(input_image):
         inverse_depth_clipped = np.clip(inverse_depth, 0, 10)
 
         # Create a color map
-        plt.figure(figsize=(10, 10))
+        plt.figure(figsize=(15.36, 15.36), dpi=100)  # Set figure size to 1536x1536 pixels
         plt.imshow(inverse_depth_clipped, cmap='viridis')
         plt.colorbar(label='Inverse Depth')
         plt.title('Predicted Inverse Depth Map')
@@ -75,7 +75,7 @@ def predict_depth(input_image):
         
         # Save the plot to a file
         output_path = "inverse_depth_map.png"
-        plt.savefig(output_path)
+        plt.savefig(output_path, dpi=100, bbox_inches='tight', pad_inches=0)
         plt.close()
 
         return output_path, f"Focal length: {focallength_px:.2f} pixels"
@@ -90,9 +90,12 @@ def predict_depth(input_image):
 iface = gr.Interface(
     fn=predict_depth,
     inputs=gr.Image(type="filepath"),
-    outputs=[gr.Image(type="filepath", label="Inverse Depth Map"), gr.Textbox(label="Focal Length or Error Message")],
+    outputs=[
+        gr.Image(type="filepath", label="Inverse Depth Map", height=768, width=768),  # Set a reasonable display size
+        gr.Textbox(label="Focal Length or Error Message")
+    ],
     title="DepthPro Demo",
-    description="[DepthPro](https://huggingface.co/apple/DepthPro) is a fast metric depth prediction model. Simply upload an image to predict its inverse depth map and focal length. Large images will be automatically resized."
+    description="[DepthPro](https://huggingface.co/apple/DepthPro) is a fast metric depth prediction model. Simply upload an image to predict its inverse depth map and focal length. Large images will be automatically resized to 1536x1536 pixels."
 )
 
 # Launch the interface