Add project files with proper Git LFS tracking for binary files

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1,24 @@
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Python cache
+__pycache__/
+*.py[cod]
+*.pyo
+*.pyd
+.Python
+# Byte-compiled / optimized / DLL files
+*.pyc
+*.pyo
+*.pyd
+# C extensions
+*.so            
+
+# OS generated files
+.DS_Store

README.md

@@ -9,6 +9,16 @@ app_file: app.py
 pinned: false
 license: cc-by-nc-sa-4.0
 short_description: MCP Server of Virtual Try On
+tags:
+    - mcp-server-track
+    - viton
+    - OOTDiffusion
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# Virtual Try-On
+
+Virtual try-on application powered by [OOTDiffusion](https://github.com/levihsu/OOTDiffusion) that allows users to virtually try on garments using AI. This project includes both a Gradio web interface and Model Context Protocol (MCP) server capabilities for seamless integration with other AI assistants
+
+Developed by [Haizad](https://huggingface.co/haizad) & [Hazel](https://huggingface.co/hazxxel)

app.py

@@ -0,0 +1,117 @@
+import gradio as gr
+import os
+from PIL import Image
+import requests
+import base64
+import io
+from dotenv import load_dotenv
+
+load_dotenv()
+
+example_path = os.path.join(os.path.dirname(__file__), 'examples')
+
+def image_to_base64(image_path):  # Remove 'self'
+    """Convert image file to base64 string"""
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode()
+
+def base64_to_image(base64_str, output_path):  # Remove 'self'
+    """Convert base64 string to image file"""
+    image_data = base64.b64decode(base64_str)
+    image = Image.open(io.BytesIO(image_data))
+    image.save(output_path)
+    return image
+
+def run_viton(model_image_path, garment_image_path, 
+                n_steps=20, image_scale=2.0, seed=-1):
+    try:
+        api_url = os.environ.get("SERVER_URL")
+        print(f"Using API URL: {api_url}")  # Add this to debug
+        
+        # Convert images to base64 (remove 'self.')
+        model_b64 = image_to_base64(model_image_path)
+        garment_b64 = image_to_base64(garment_image_path)
+
+        # Prepare request
+        request_data = {
+            "model_image_base64": model_b64,
+            "garment_image_base64": garment_b64,
+            "n_samples": 1,
+            "n_steps": n_steps,
+            "image_scale": image_scale,
+            "seed": seed
+        }
+                
+        # Send request
+        response = requests.post(f"{api_url}/viton", 
+                                json=request_data, 
+                                timeout=300)
+        
+        print(f"Request sent to {api_url}/viton")
+        print(f"Response status code: {response.status_code}")
+        
+        if response.status_code == 200:
+            result = response.json()
+            if result.get("error"):
+                print(f"Error: {result['error']}")
+                return []
+            
+            generated_images = []
+            for i, img_b64 in enumerate(result.get("images_base64", [])):
+                output_path = f"ootd_output_{i}.png"
+                img = base64_to_image(img_b64, output_path)  # Remove 'self.'
+                generated_images.append(img)
+            
+            print(f"Successfully generated {len(generated_images)} images")
+            return generated_images
+        else:
+            print(f"Request failed with status code: {response.status_code}")
+            return []  # Fix: was missing 'return'
+            
+    except Exception as e:
+        print(f"Exception occurred: {str(e)}")  # Add this
+        return []  # Fix: should return list, not dict for gallery
+
+block = gr.Blocks().queue()
+default_model = os.path.join(example_path, 'model/model_8.png')
+default_garment = os.path.join(example_path, 'garment/00055_00.jpg')
+with block:
+    with gr.Row():
+        gr.Markdown("# Virtual Try-On")
+    with gr.Row():
+        with gr.Column():
+            vton_img = gr.Image(label="Model", sources=['upload', 'webcam'], type="filepath", height=384, value=default_model)
+            example = gr.Examples(
+                inputs=vton_img,
+                examples_per_page=5,
+                examples=[
+                    os.path.join(example_path, 'model/model_8.png'),
+                    os.path.join(example_path, 'model/model_2.png'),
+                    os.path.join(example_path, 'model/model_7.png'),
+                    os.path.join(example_path, 'model/model_4.png'),
+                    os.path.join(example_path, 'model/model_5.png'),
+                ])
+        with gr.Column():
+            garm_img = gr.Image(label="Garment", sources=['upload', 'webcam'], type="filepath", height=384, value=default_garment)
+            example = gr.Examples(
+                inputs=garm_img,
+                examples_per_page=5,
+                examples=[
+                    os.path.join(example_path, 'garment/00055_00.jpg'),
+                    os.path.join(example_path, 'garment/07764_00.jpg'),
+                    os.path.join(example_path, 'garment/03032_00.jpg'),
+                    os.path.join(example_path, 'garment/048554_1.jpg'),
+                    os.path.join(example_path, 'garment/049805_1.jpg'),
+                ])
+        with gr.Column():
+            result_gallery = gr.Gallery(label='Output', show_label=False, elem_id="gallery", preview=True, scale=1)   
+    with gr.Column():
+        run_button = gr.Button(value="Run")
+        n_steps = gr.Slider(label="Steps", minimum=20, maximum=40, value=20, step=1)
+        image_scale = gr.Slider(label="Guidance scale", minimum=1.0, maximum=5.0, value=2.0, step=0.1)
+        seed = gr.Slider(label="Seed", minimum=-1, maximum=2147483647, step=1, value=-1)
+        
+    ips = [vton_img, garm_img, n_steps, image_scale, seed]
+    run_button.click(fn=run_viton, inputs=ips, outputs=result_gallery)
+
+block.launch(server_name='0.0.0.0', server_port=7865, mcp_server=True)

requirements.txt

@@ -0,0 +1,4 @@
+pillow==9.4.0
+gradio[mcp]==5.33.0
+requests==2.32.3
+python-dotenv==1.1.0