Update app.py

app.py

@@ -493,141 +493,63 @@ print("Preloading finished (check logs above for errors).")
 # --- Gradio Interface Definition ---
 # (Your Gradio Blocks code remains largely the same, but ensure the outputs match the function returns)
 
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
+# --- Gradio Interface ---
+# ... (imports and functions) ...
+
+with gr.Blocks(theme=gr.themes.Soft()) as demo: # START of the block
     gr.Markdown("# CLIP & FastSAM Demo")
-    gr.Markdown("Explore Zero-Shot Classification, 'Segment Everything', and Text-Prompted Segmentation.")
+    # ... other UI elements ...
 
     with gr.Tabs():
-        # --- CLIP Tab ---
         with gr.TabItem("CLIP Zero-Shot Classification"):
-            # ... (CLIP UI definition - seems ok) ...
+            gr.Markdown("Upload an image and provide comma-separated labels...")
+            with gr.Row():
+                with gr.Column(scale=1):
+                    clip_input_image = gr.Image(type="pil", label="Input Image")
+                    clip_text_labels = gr.Textbox(label="Comma-Separated Labels", ...)
+                    # DEFINE the button
+                    clip_button = gr.Button("Run CLIP Classification", variant="primary")
+                with gr.Column(scale=1):
+                    clip_output_label = gr.Label(label="Classification Probabilities")
+                    clip_output_image_display = gr.Image(type="pil", label="Input Image Preview")
+
+            # ATTACH the click handler *inside* the block, after the button is defined
             clip_button.click(
                 run_clip_zero_shot,
                 inputs=[clip_input_image, clip_text_labels],
-                # Output matches: Label (dict/str), Image (PIL/None)
                 outputs=[clip_output_label, clip_output_image_display]
             )
-            # ... (CLIP Examples - seems ok) ...
-
+            # ... CLIP examples ...
 
-        # --- FastSAM Everything Tab ---
         with gr.TabItem("FastSAM Segment Everything"):
-            gr.Markdown("Upload an image to segment all objects/regions.")
-            with gr.Row():
-                with gr.Column(scale=1):
-                    fastsam_input_image_all = gr.Image(type="pil", label="Input Image")
-                    with gr.Row():
-                        fastsam_conf_all = gr.Slider(minimum=0.1, maximum=1.0, value=0.4, step=0.05, label="Confidence Threshold")
-                        fastsam_iou_all = gr.Slider(minimum=0.1, maximum=1.0, value=0.9, step=0.05, label="IoU Threshold")
-                    fastsam_button_all = gr.Button("Run FastSAM Segmentation", variant="primary")
-                with gr.Column(scale=1):
-                    # Output for the image
-                    fastsam_output_image_all = gr.Image(type="pil", label="Segmented Image")
-                    # Add a Textbox for status messages/errors
-                    fastsam_status_all = gr.Textbox(label="Status", interactive=False)
+            # ... FastSAM Everything UI elements ...
+            fastsam_button_all = gr.Button(...) # Define button
 
+            # Attach click handler *inside* the block
             fastsam_button_all.click(
                 run_fastsam_segmentation,
-                inputs=[fastsam_input_image_all, fastsam_conf_all, fastsam_iou_all],
-                # Outputs: Image (PIL/None), Status (str)
-                outputs=[fastsam_output_image_all, fastsam_status_all] # Updated outputs
+                inputs=[...],
+                outputs=[...]
             )
-            # Update examples if needed to match new output structure (add None/str for status)
-            # Note: Examples might need adjustment if they expect only image output
-            gr.Examples(
-                 examples=[
-                     ["examples/dogs.jpg", 0.4, 0.9],
-                     ["examples/fruits.jpg", 0.5, 0.8],
-                     ["examples/lion.jpg", 0.45, 0.9],
-                 ],
-                 inputs=[fastsam_input_image_all, fastsam_conf_all, fastsam_iou_all],
-                 # Need to adjust outputs for examples if function signature changed
-                 # This might require a wrapper if examples expect single output
-                 # For now, comment out example outputs or adjust function signature for examples
-                 outputs=[fastsam_output_image_all, fastsam_status_all],
-                 fn=run_fastsam_segmentation,
-                 cache_examples=False, # Keep False for debugging
-             )
-
-        # --- Text-Prompted Segmentation Tab ---
+            # ... FastSAM Everything examples ...
+
         with gr.TabItem("Text-Prompted Segmentation"):
-            gr.Markdown("Upload an image and provide comma-separated prompts (e.g., 'person, dog').")
-            with gr.Row():
-                with gr.Column(scale=1):
-                    prompt_input_image = gr.Image(type="pil", label="Input Image")
-                    prompt_text_input = gr.Textbox(label="Comma-Separated Text Prompts", placeholder="e.g., glasses, watch")
-                    with gr.Row():
-                        prompt_conf = gr.Slider(minimum=0.1, maximum=1.0, value=0.4, step=0.05, label="Confidence Threshold")
-                        prompt_iou = gr.Slider(minimum=0.1, maximum=1.0, value=0.9, step=0.05, label="IoU Threshold")
-                    prompt_button = gr.Button("Segment by Text", variant="primary")
-                with gr.Column(scale=1):
-                    # Output Image
-                    prompt_output_image = gr.Image(type="pil", label="Text-Prompted Segmentation")
-                    # Status Textbox (already exists, correctly)
-                    prompt_status_message = gr.Textbox(label="Status", interactive=False)
+            # ... Text-Prompted UI elements ...
+            prompt_button = gr.Button(...) # Define button
 
+            # Attach click handler *inside* the block
             prompt_button.click(
                 run_text_prompted_segmentation,
-                inputs=[prompt_input_image, prompt_text_input, prompt_conf, prompt_iou],
-                # Outputs: Image (PIL/None), Status (str) - Matches function
-                outputs=[prompt_output_image, prompt_status_message]
+                inputs=[...],
+                outputs=[...]
             )
-            # Update examples similarly if needed
-            gr.Examples(
-                 examples=[
-                     ["examples/dog_bike.jpg", "person, bicycle", 0.4, 0.9],
-                     ["examples/astronaut.jpg", "person, helmet", 0.35, 0.9],
-                     ["examples/dogs.jpg", "dog", 0.4, 0.9],
-                     ["examples/fruits.jpg", "banana, apple", 0.5, 0.8],
-                     ["examples/teacher.jpg", "person, glasses", 0.4, 0.9],
-                 ],
-                 inputs=[prompt_input_image, prompt_text_input, prompt_conf, prompt_iou],
-                 outputs=[prompt_output_image, prompt_status_message],
-                 fn=run_text_prompted_segmentation,
-                 cache_examples=False, # Keep False for debugging
-             )
-
-
-    # --- Example File Download ---
-    # (Download logic seems okay, ensure 'wget' is installed: pip install wget)
-    if not os.path.exists("examples"):
-        os.makedirs("examples")
-        print("Created 'examples' directory.")
-    example_files = {
-        "astronaut.jpg": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/d1/Astronaut_-_St._Jean_Bay.jpg/640px-Astronaut_-_St._Jean_Bay.jpg",
-        "dog_bike.jpg": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/gradio/outputs_multimodal.jpg",
-        "clip_logo.png": "https://raw.githubusercontent.com/openai/CLIP/main/CLIP.png",
-        "dogs.jpg": "https://raw.githubusercontent.com/ultralytics/assets/main/im/image8.jpg",
-        "fruits.jpg": "https://raw.githubusercontent.com/ultralytics/assets/main/im/image9.jpg",
-        "lion.jpg": "https://huggingface.co/spaces/gradio/image-segmentation/resolve/main/images/lion.jpg",
-        "teacher.jpg": "https://images.pexels.com/photos/848117/pexels-photo-848117.jpeg?auto=compress&cs=tinysrgb&w=600"
-    }
-    def download_example_file(filename, url, retries=3):
-        filepath = os.path.join("examples", filename)
-        if not os.path.exists(filepath):
-            print(f"Attempting to download {filename}...")
-            for attempt in range(retries):
-                try:
-                    wget.download(url, filepath)
-                    print(f"Downloaded {filename} successfully.")
-                    return # Exit function on success
-                except Exception as e:
-                    print(f"Download attempt {attempt + 1}/{retries} for {filename} failed: {e}")
-                    if os.path.exists(filepath): # Clean up partial download
-                        try: os.remove(filepath)
-                        except OSError: pass
-                    if attempt + 1 == retries:
-                        print(f"Failed to download {filename} after {retries} attempts.")
-        else:
-             print(f"Example file {filename} already exists.")
-
-    # Trigger downloads
-    for filename, url in example_files.items():
-        download_example_file(filename, url)
-    print("Example file check/download complete.")
+            # ... Text-Prompted examples ...
 
+# The `with` block ends here.
+# --- Example File Download (This is correctly outside the block) ---
+# ... download logic ...
 
-# --- Launch App ---
+# --- Launch App (This is correctly outside the block) ---
 if __name__ == "__main__":
     print("Launching Gradio Demo...")
-    demo.launch(debug=True) # Keep debug=True
+    demo.launch(debug=True)