Update apps/gradio_app.py

apps/gradio_app.py

@@ -1,187 +1,187 @@
-import os
-import subprocess
-import gradio as gr
-import random
-from gradio_app.inference import run_inference
-from gradio_app.examples import load_examples, select_example
-from gradio_app.project_info import (
-    NAME, 
-    CONTENT_DESCRIPTION, 
-    CONTENT_IN_1, 
-    CONTENT_OUT_1
-)
-
-def run_setup_script():
-    setup_script = os.path.join(os.path.dirname(__file__), "gradio_app", "setup_scripts.py")
-    try:
-        result = subprocess.run(["python", setup_script], capture_output=True, text=True, check=True)
-        return result.stdout
-    except subprocess.CalledProcessError as e:
-        print(f"Setup script failed with error: {e.stderr}")
-        return f"Setup script failed: {e.stderr}"
-
-def stop_app():
-    """Function to stop the Gradio app."""
-    try:
-        gr.Interface.close_all()  # Attempt to close all running Gradio interfaces
-        return "Application stopped successfully."
-    except Exception as e:
-        return f"Error stopping application: {str(e)}"
-
-def create_gui():
-    try:
-        custom_css = open("apps/gradio_app/static/style.css").read()
-    except FileNotFoundError:
-        print("Error: style.css not found at gradio_app/static/style.css")
-        custom_css = ""  # Fallback to empty CSS if file is missing
-
-    with gr.Blocks(css=custom_css) as demo:
-        gr.Markdown(NAME)
-        gr.HTML(CONTENT_DESCRIPTION)
-        gr.HTML(CONTENT_IN_1)
-
-        with gr.Row():
-            with gr.Column(scale=2):
-                input_image = gr.Image(type="filepath", label="Input Image")
-                prompt = gr.Textbox(
-                    label="Prompt",
-                    value="a man is doing yoga"
-                )
-                negative_prompt = gr.Textbox(
-                    label="Negative Prompt",
-                    value="monochrome, lowres, bad anatomy, worst quality, low quality"
-                )
-                
-                with gr.Row():
-                    width = gr.Slider(
-                        minimum=256,
-                        maximum=1024,
-                        value=512,
-                        step=64,
-                        label="Width"
-                    )
-                    height = gr.Slider(
-                        minimum=256,
-                        maximum=1024,
-                        value=512,
-                        step=64,
-                        label="Height"
-                    )
-                
-                with gr.Accordion("Advanced Settings", open=False):
-                    num_steps = gr.Slider(
-                        minimum=1,
-                        maximum=100,
-                        value=30,
-                        step=1,
-                        label="Number of Inference Steps"
-                    )
-                    use_random_seed = gr.Checkbox(label="Use Random Seed", value=False)
-                    seed = gr.Slider(
-                        minimum=0,
-                        maximum=2**32 - 1,
-                        value=42,
-                        step=1,
-                        label="Random Seed",
-                        visible=True
-                    )
-                    
-                    guidance_scale = gr.Slider(
-                        minimum=1.0,
-                        maximum=20.0,
-                        value=7.5,
-                        step=0.1,
-                        label="Guidance Scale"
-                    )
-                    controlnet_conditioning_scale = gr.Slider(
-                        minimum=0.0,
-                        maximum=1.0,
-                        value=1.0,
-                        step=0.1,
-                        label="ControlNet Conditioning Scale"
-                    )  
-                    
-            with gr.Column(scale=3):
-                output_images = gr.Image(label="Generated Images")
-                output_message = gr.Textbox(label="Status")
-                
-                submit_button = gr.Button("Generate Images", elem_classes="submit-btn")
-                stop_button = gr.Button("Stop Application", elem_classes="stop-btn")
-
-        def update_seed_visibility(use_random):
-            return gr.update(visible=not use_random)
-        
-        use_random_seed.change(
-            fn=update_seed_visibility,
-            inputs=use_random_seed,
-            outputs=seed
-        )
-        
-        # Load examples
-        examples_data = load_examples(os.path.join("apps", "gradio_app", 
-            "assets", "examples", "Stable-Diffusion-2.1-Openpose-ControlNet"))
-        examples_component = gr.Examples(
-            examples=examples_data,
-            inputs=[
-                input_image,
-                prompt,
-                negative_prompt,
-                output_images,
-                num_steps,
-                seed,
-                width,
-                height,
-                guidance_scale,
-                controlnet_conditioning_scale,
-                use_random_seed
-            ],
-            outputs=[
-                input_image,
-                prompt,
-                negative_prompt,
-                output_images,
-                num_steps,
-                seed,
-                width,
-                height,
-                guidance_scale,
-                controlnet_conditioning_scale,
-                use_random_seed,
-                output_message
-            ],
-            fn=select_example,
-            cache_examples=False,
-            label="Examples: Yoga Poses"
-        )
-        
-        submit_button.click(
-            fn=run_inference,
-            inputs=[
-                input_image,
-                prompt,
-                negative_prompt,
-                num_steps,
-                seed,
-                width,
-                height,
-                guidance_scale,
-                controlnet_conditioning_scale,
-                use_random_seed,
-            ],
-            outputs=[output_images, output_message]
-        )
-        
-        stop_button.click(
-            fn=stop_app,
-            inputs=[],
-            outputs=[output_message]
-        )
-        
-        gr.HTML(CONTENT_OUT_1)
-        
-    return demo
-
-if __name__ == "__main__":
-    run_setup_script()
-    demo = create_gui()
-    demo.launch(share=True)
+import os
+import subprocess
+import gradio as gr
+import random
+from gradio_app.inference import run_inference
+from gradio_app.examples import load_examples, select_example
+from gradio_app.project_info import (
+    NAME, 
+    CONTENT_DESCRIPTION, 
+    CONTENT_IN_1, 
+    CONTENT_OUT_1
+)
+
+def run_setup_script():
+    setup_script = os.path.join(os.path.dirname(__file__), "gradio_app", "setup_scripts.py")
+    try:
+        result = subprocess.run(["python", setup_script], capture_output=True, text=True, check=True)
+        return result.stdout
+    except subprocess.CalledProcessError as e:
+        print(f"Setup script failed with error: {e.stderr}")
+        return f"Setup script failed: {e.stderr}"
+
+def stop_app():
+    """Function to stop the Gradio app."""
+    try:
+        gr.Interface.close_all()  # Attempt to close all running Gradio interfaces
+        return "Application stopped successfully."
+    except Exception as e:
+        return f"Error stopping application: {str(e)}"
+
+def create_gui():
+    try:
+        custom_css = open("apps/gradio_app/static/style.css").read()
+    except FileNotFoundError:
+        print("Error: style.css not found at gradio_app/static/style.css")
+        custom_css = ""  # Fallback to empty CSS if file is missing
+
+    with gr.Blocks(css=custom_css) as demo:
+        gr.Markdown(NAME)
+        gr.HTML(CONTENT_DESCRIPTION)
+        gr.HTML(CONTENT_IN_1)
+
+        with gr.Row():
+            with gr.Column(scale=2):
+                input_image = gr.Image(type="filepath", label="Input Image")
+                prompt = gr.Textbox(
+                    label="Prompt",
+                    value="a man is doing yoga"
+                )
+                negative_prompt = gr.Textbox(
+                    label="Negative Prompt",
+                    value="monochrome, lowres, bad anatomy, worst quality, low quality"
+                )
+                
+                with gr.Row():
+                    width = gr.Slider(
+                        minimum=256,
+                        maximum=1024,
+                        value=512,
+                        step=64,
+                        label="Width"
+                    )
+                    height = gr.Slider(
+                        minimum=256,
+                        maximum=1024,
+                        value=512,
+                        step=64,
+                        label="Height"
+                    )
+                
+                with gr.Accordion("Advanced Settings", open=False):
+                    num_steps = gr.Slider(
+                        minimum=1,
+                        maximum=100,
+                        value=30,
+                        step=1,
+                        label="Number of Inference Steps"
+                    )
+                    use_random_seed = gr.Checkbox(label="Use Random Seed", value=False)
+                    seed = gr.Slider(
+                        minimum=0,
+                        maximum=2**32 - 1,
+                        value=42,
+                        step=1,
+                        label="Random Seed",
+                        visible=True
+                    )
+                    
+                    guidance_scale = gr.Slider(
+                        minimum=1.0,
+                        maximum=20.0,
+                        value=7.5,
+                        step=0.1,
+                        label="Guidance Scale"
+                    )
+                    controlnet_conditioning_scale = gr.Slider(
+                        minimum=0.0,
+                        maximum=1.0,
+                        value=1.0,
+                        step=0.1,
+                        label="ControlNet Conditioning Scale"
+                    )  
+                    
+            with gr.Column(scale=3):
+                output_images = gr.Image(label="Generated Images")
+                output_message = gr.Textbox(label="Status")
+                
+                submit_button = gr.Button("Generate Images", elem_classes="submit-btn")
+                stop_button = gr.Button("Stop Application", elem_classes="stop-btn")
+
+        def update_seed_visibility(use_random):
+            return gr.update(visible=not use_random)
+        
+        use_random_seed.change(
+            fn=update_seed_visibility,
+            inputs=use_random_seed,
+            outputs=seed
+        )
+        
+        # Load examples
+        examples_data = load_examples(os.path.join("apps", "gradio_app", 
+            "assets", "examples", "Stable-Diffusion-2.1-Openpose-ControlNet"))
+        examples_component = gr.Examples(
+            examples=examples_data,
+            inputs=[
+                input_image,
+                prompt,
+                negative_prompt,
+                output_images,
+                num_steps,
+                seed,
+                width,
+                height,
+                guidance_scale,
+                controlnet_conditioning_scale,
+                use_random_seed
+            ],
+            outputs=[
+                input_image,
+                prompt,
+                negative_prompt,
+                output_images,
+                num_steps,
+                seed,
+                width,
+                height,
+                guidance_scale,
+                controlnet_conditioning_scale,
+                use_random_seed,
+                output_message
+            ],
+            fn=select_example,
+            cache_examples=False,
+            label="Examples: Yoga Poses"
+        )
+        
+        submit_button.click(
+            fn=run_inference,
+            inputs=[
+                input_image,
+                prompt,
+                negative_prompt,
+                num_steps,
+                seed,
+                width,
+                height,
+                guidance_scale,
+                controlnet_conditioning_scale,
+                use_random_seed,
+            ],
+            outputs=[output_images, output_message]
+        )
+        
+        stop_button.click(
+            fn=stop_app,
+            inputs=[],
+            outputs=[output_message]
+        )
+        
+        gr.HTML(CONTENT_OUT_1)
+        
+    return demo
+
+if __name__ == "__main__":
+    run_setup_script()
+    demo = create_gui()
+    demo.launch()