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	Update app.py
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        app.py
    CHANGED
    
    | @@ -9,46 +9,54 @@ import asyncio | |
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            import requests
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            import base64
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            import gradio as gr
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            -
            # from IPython import embed
         | 
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|  | |
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            machine_number = 0
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            -
            model = os.path.join(os.path.dirname(__file__), "models | 
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            MODEL_MAP = {
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            -
                "AI Model Rouyan_0":  | 
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                "AI Model Rouyan_1":  | 
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                "AI Model Rouyan_2":  | 
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                "AI Model Eva_0":  | 
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                "AI Model Eva_1":  | 
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            -
                "AI Model Simon_0":  | 
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                "AI Model Simon_1":  | 
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                "AI Model Xuanxuan_0":  | 
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            -
                "AI Model Xuanxuan_1":  | 
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            -
                "AI Model Xuanxuan_2":  | 
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                "AI Model Yaqi_0":  | 
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                "AI Model Yaqi_1":  | 
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                "AI Model Yaqi_2":  | 
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                "AI Model Yaqi_3":  | 
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                "AI Model Yifeng_0":  | 
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            -
                "AI Model Yifeng_1":  | 
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                "AI Model Yifeng_2":  | 
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                "AI Model Yifeng_3":  | 
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            }
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            def add_waterprint(img):
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            -
             | 
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                h, w, _ = img.shape
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                img = cv2.putText(img, 'Powered by OutfitAnyone', (int(0.3*w), h-20), cv2.FONT_HERSHEY_PLAIN, 2, (128, 128, 128), 2, cv2.LINE_AA)
         | 
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            -
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                return img
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            -
             | 
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            def get_tryon_result(model_name, garment1, garment2, seed=1234):
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                #  | 
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                 | 
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                 | 
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                encoded_garment1 = cv2.imencode('.jpg', garment1)[1].tobytes()
         | 
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                encoded_garment1 = base64.b64encode(encoded_garment1).decode('utf-8')
         | 
| 54 |  | 
| @@ -58,134 +66,102 @@ def get_tryon_result(model_name, garment1, garment2, seed=1234): | |
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                else:
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                    encoded_garment2 = ''
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            -
                 | 
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                headers = {'Content-Type': 'application/json'}
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                seed = random.randint(0, 1222222222)
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                data = {
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                    "garment1": encoded_garment1,
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                    "garment2": encoded_garment2,
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                    "model_name": model_name,
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                    "seed": seed
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                }
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                response = requests.post(url, headers=headers, data=json.dumps(data))
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                print("response code", response.status_code)
         | 
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                if response.status_code == 200:
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                    result = response.json()
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                    result = base64.b64decode(result['images'][0])
         | 
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                    result_np = np.frombuffer(result, np.uint8)
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                    result_img = cv2.imdecode(result_np, cv2.IMREAD_UNCHANGED)
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                else:
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                    print(' | 
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            -
                
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                final_img = add_waterprint(result_img)
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                return final_img
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                #  | 
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                gr.HTML(
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                    """
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                    <div style=" | 
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             | 
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                    <div>
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                        <h1 >Outfit Anyone: Ultra-high quality virtual try-on for Any Clothing and Any Person</h1>
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                        <h4 >v0.9</h4>
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                        <h5 style="margin: 0;">If you like our project, please give us a star  on Github to stay updated with the latest developments.</h5>
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                        <div style="display: flex; justify-content: center; align-items: center; text-align: center;>
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                            <a href="https://arxiv.org/abs/2407.16224"><img src="https://img.shields.io/badge/Arxiv-2407.16224-red"></a>
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                            <a href='https://humanaigc.github.io/outfit-anyone/'><img src='https://img.shields.io/badge/Project_Page-OutfitAnyone-green' alt='Project Page'></a>
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                            <a href='https://github.com/HumanAIGC/OutfitAnyone'><img src='https://img.shields.io/badge/Github-Repo-blue'></a>
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                        </div>
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                    </div>
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                     | 
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             | 
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                with gr.Row():
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                    with gr.Column():
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            -
                         | 
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                        example = gr.Examples(inputs=init_image,
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                                              examples_per_page=4,
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                                              examples=[os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Rouyan_0')) | 
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            -
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                                                        os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Eva_0')),
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                                                        os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Simon_1')),
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                                                        os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Eva_1')),
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                                                        os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Simon_0')),
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                                                        os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Xuanxuan_0')),
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                                                        os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Xuanxuan_2')),
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                                                        os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yaqi_1')),
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                                                        os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yifeng_0')),
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                                                        os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yifeng_3')),
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                                                        os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Rouyan_1')),
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                                                        os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yifeng_2')),
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                                                        os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yaqi_0')),
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            -
                                                        ])
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                    with gr.Column():
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                        gr. | 
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                            """
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                            <div>
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                                <h3>Models are fixed and cannot be uploaded or modified; we only support users uploading their own garments.</h3>
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                                <h4 style="margin: 0;">For a one-piece dress or coat, you only need to upload the image to the 'top garment' section and leave the 'lower garment' section empty.</h4>
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                            </div>
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                            </div>
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                            """)
         | 
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                        with gr.Row():
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                            garment_top = gr.Image(sources='upload', type="numpy", label=" | 
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                            example_top = gr.Examples(inputs=garment_top,
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                                                      examples_per_page=5,
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                                                      examples=[os.path.join(os.path.dirname(__file__), "garments | 
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                                                                os.path.join(os.path.dirname(__file__), "garments/dress1.png"),
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                                                                os.path.join(os.path.dirname(__file__), "garments/dress2.png"),
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                                                                        ])
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                            garment_down = gr.Image(sources='upload', type="numpy", label="lower garment")
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                            example_down = gr.Examples(inputs=garment_down,
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                                                       examples_per_page=5,
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                                                       examples=[os.path.join(os.path.dirname(__file__), "garments | 
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                                                                 os.path.join(os.path.dirname(__file__), "garments/bottom5.png"),
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                                                                        ])
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                        run_button = gr.Button(value="Run")
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                    with gr.Column():
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                        gallery = gr.Image()
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                        run_button.click(fn=get_tryon_result, 
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                                         inputs=[
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                                                garment_top,
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                                                garment_down,
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                                                ], 
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                                         outputs=[gallery],
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                                         concurrency_limit=2)
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            -
                    
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                #  | 
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                gr.Markdown("##  | 
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                with gr.Row():
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                    reference_image1 | 
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                    reference_image2 | 
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                    reference_image3 | 
|  | |
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                gr.Examples(
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                    examples=[
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                        ["examples/basemodel.png", "examples/garment1.png", "examples/result1.png"],
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                        ["examples/basemodel.png", "examples/garment2.png", "examples/result2.png"],
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                        ["examples/basemodel.png", "examples/garment3.png", "examples/result3.png"],
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                    ],
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                    inputs=[reference_image1, reference_image2, reference_image3],
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                    label= | 
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                )
         | 
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            if __name__ == "__main__":
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                ip = requests.get('http://ifconfig.me/ip', timeout=1).text.strip()
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                print(" | 
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                demo.queue(max_size=10)
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                demo.launch()
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            import requests
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            import base64
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            import gradio as gr
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            +
            # Set the machine number and model path
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            machine_number = 0
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            +
            model = os.path.join(os.path.dirname(__file__), "models", "eva", "Eva_0.png")
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            # Define a mapping of model names to file paths
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            MODEL_MAP = {
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                "AI Model Rouyan_0": os.path.join("models", "rouyan_new", "rouyan_new\\Rouyan_0.png"),
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                "AI Model Rouyan_1": os.path.join("models", "rouyan_new", "rouyan_new\\Rouyan_1.png"),
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                "AI Model Rouyan_2": os.path.join("models", "rouyan_new", "rouyan_new\\Rouyan_2.png"),
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                "AI Model Eva_0": os.path.join("models", "eva", "Eva_0.png"),
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                "AI Model Eva_1": os.path.join("models", "eva", "Eva_1.png"),
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                "AI Model Simon_0": os.path.join("models", "simon_online", "Simon_0.png"),
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                "AI Model Simon_1": os.path.join("models", "simon_online", "Simon_1.png"),
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                "AI Model Xuanxuan_0": os.path.join("models", "xiaoxuan_online", "Xuanxuan_0.png"),
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                "AI Model Xuanxuan_1": os.path.join("models", "xiaoxuan_online", "Xuanxuan_1.png"),
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                "AI Model Xuanxuan_2": os.path.join("models", "xiaoxuan_online", "Xuanxuan_2.png"),
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            +
                "AI Model Yaqi_0": os.path.join("models", "yaqi", "Yaqi_0.png"),
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                "AI Model Yaqi_1": os.path.join("models", "yaqi", "Yaqi_1.png"),
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            +
                "AI Model Yaqi_2": os.path.join("models", "yaqi", "Yaqi_2.png"),
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            +
                "AI Model Yaqi_3": os.path.join("models", "yaqi", "Yaqi_3.png"),
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            +
                "AI Model Yifeng_0": os.path.join("models", "yifeng_online", "Yifeng_0.png"),
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                "AI Model Yifeng_1": os.path.join("models", "yifeng_online", "Yifeng_1.png"),
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            +
                "AI Model Yifeng_2": os.path.join("models", "yifeng_online", "Yifeng_2.png"),
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            +
                "AI Model Yifeng_3": os.path.join("models", "yifeng_online", "Yifeng_3.png"),
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            }
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            +
            # Function to add watermark text to image
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            def add_waterprint(img):
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                h, w, _ = img.shape
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                img = cv2.putText(img, 'Powered by OutfitAnyone', (int(0.3*w), h-20), cv2.FONT_HERSHEY_PLAIN, 2, (128, 128, 128), 2, cv2.LINE_AA)
         | 
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                return img
         | 
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            +
            # Function to process try-on results
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            def get_tryon_result(model_name, garment1, garment2, seed=1234):
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            +
                if isinstance(model_name, np.ndarray):
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                   model_name = model_name[0] 
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            +
                
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                model_name = "AI Model " + model_name.split("\\")[-1].split(".")[0]  # Handle Windows path
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            +
                print(type(model_name))
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            +
             | 
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            +
                # Directly load the model image from the disk, no need for Gradio file upload
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            +
                model_image = cv2.imread(MODEL_MAP.get(model_name))  # Load model image from disk
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            +
                if model_image is None:
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            +
                    raise ValueError(f"Model image {model_name} could not be loaded.")
         | 
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            +
                # Encode garments as base64
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                encoded_garment1 = cv2.imencode('.jpg', garment1)[1].tobytes()
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                encoded_garment1 = base64.b64encode(encoded_garment1).decode('utf-8')
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                else:
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                    encoded_garment2 = ''
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            +
                # Get the IP address from environment variable or default to localhost
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            +
                url = os.environ.get('OA_IP_ADDRESS', 'http://localhost:5000')
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                headers = {'Content-Type': 'application/json'}
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                seed = random.randint(0, 1222222222)
         | 
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            +
             | 
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            +
                # Prepare data for POST request
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                data = {
         | 
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                    "garment1": encoded_garment1,
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                    "garment2": encoded_garment2,
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                    "model_name": model_name,
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                    "seed": seed
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                }
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            +
             | 
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            +
                # Send POST request to server
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                response = requests.post(url, headers=headers, data=json.dumps(data))
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                print("response code", response.status_code)
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            +
             | 
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                if response.status_code == 200:
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                    result = response.json()
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                    result = base64.b64decode(result['images'][0])
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                    result_np = np.frombuffer(result, np.uint8)
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                    result_img = cv2.imdecode(result_np, cv2.IMREAD_UNCHANGED)
         | 
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                else:
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            +
                    print('Server error!')
         | 
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                final_img = add_waterprint(result_img)
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                return final_img
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            +
            with gr.Blocks(css=".output-image, .input-image, .image-preview {height: 400px !important}") as demo:
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            +
                
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                # Header Section
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                gr.HTML(
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                    """
         | 
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            +
                    <div style="text-align: center; padding: 20px;">
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            +
                        <h1 style="font-size: 2.5rem; color: #2c3e50;">Outfit Anyone</h1>
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                        <h2 style="color: #34495e;">Ultra-high quality virtual try-on for any clothing and any person</h2>
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                    </div>
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                    """
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            +
                )
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            +
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            +
                # UI Layout for Image Inputs and Text Description
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                with gr.Row():
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                    with gr.Column():
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            +
                        gr.Markdown("### Upload Your Model Image")
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            +
                        init_image = gr.Image(sources='upload', type="numpy", label="Select a Model Image", value=None)
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                        example = gr.Examples(inputs=init_image,
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                                              examples_per_page=4,
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            +
                                              examples=[os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Rouyan_0'))])
         | 
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            +
                    
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                    with gr.Column():
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            +
                        gr.Markdown(
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            +
                            """
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            +
                            <h3 style="color: #2c3e50;">Instructions</h3>
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            +
                            <p style="font-size: 1.1rem; color: #7f8c8d;">Please upload your model image and garment images (top and bottom). 
         | 
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            +
                            The models are pre-loaded and cannot be modified. 
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            +
                            For a dress or coat, you only need to upload the image for the 'Top Garment' section and leave the 'Bottom Garment' section empty.</p>
         | 
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                            """
         | 
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            +
                        )
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                        with gr.Row():
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            +
                            garment_top = gr.Image(sources='upload', type="numpy", label="Top Garment")
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                            example_top = gr.Examples(inputs=garment_top,
         | 
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                                                      examples_per_page=5,
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            +
                                                      examples=[os.path.join(os.path.dirname(__file__), "garments", "top222.JPG")])
         | 
| 134 | 
            +
                            
         | 
| 135 | 
            +
                            garment_down = gr.Image(sources='upload', type="numpy", label="Bottom Garment")
         | 
|  | |
|  | |
|  | |
|  | |
| 136 | 
             
                            example_down = gr.Examples(inputs=garment_down,
         | 
| 137 | 
             
                                                       examples_per_page=5,
         | 
| 138 | 
            +
                                                       examples=[os.path.join(os.path.dirname(__file__), "garments", "bottom1.png")])
         | 
| 139 | 
            +
             | 
| 140 | 
            +
                        run_button = gr.Button(value="Run Try-On")
         | 
| 141 | 
            +
                    
         | 
|  | |
|  | |
|  | |
|  | |
| 142 | 
             
                    with gr.Column():
         | 
| 143 | 
            +
                        gallery = gr.Image(label="Try-On Result")
         | 
| 144 |  | 
| 145 | 
             
                        run_button.click(fn=get_tryon_result, 
         | 
| 146 | 
            +
                                         inputs=[init_image, garment_top, garment_down], 
         | 
| 147 | 
            +
                                         outputs=[gallery], 
         | 
|  | |
|  | |
|  | |
|  | |
| 148 | 
             
                                         concurrency_limit=2)
         | 
|  | |
| 149 |  | 
| 150 | 
            +
                # Example Section
         | 
| 151 | 
            +
                gr.Markdown("## Example Try-On Results")
         | 
| 152 | 
             
                with gr.Row():
         | 
| 153 | 
            +
                    reference_image1 = gr.Image(label="Model Example", scale=1, value="examples\\examples_basemodel.png")
         | 
| 154 | 
            +
                    reference_image2 = gr.Image(label="Garment Example", scale=1, value="examples\\examples_garment1.jpg")
         | 
| 155 | 
            +
                    reference_image3 = gr.Image(label="Result Example", scale=1, value="examples\\examples_result1.png")
         | 
| 156 | 
            +
             | 
| 157 | 
             
                gr.Examples(
         | 
| 158 | 
            +
                    examples=[["examples\\examples_basemodel.png", "examples\\examples_garment1.png", "examples\\examples_result1.png"]],
         | 
|  | |
|  | |
|  | |
|  | |
| 159 | 
             
                    inputs=[reference_image1, reference_image2, reference_image3],
         | 
| 160 | 
            +
                    label="Check out our example outfits!",
         | 
| 161 | 
             
                )
         | 
| 162 |  | 
| 163 | 
             
            if __name__ == "__main__":
         | 
| 164 | 
             
                ip = requests.get('http://ifconfig.me/ip', timeout=1).text.strip()
         | 
| 165 | 
            +
                print("IP address", ip)
         | 
| 166 | 
             
                demo.queue(max_size=10)
         | 
| 167 | 
             
                demo.launch()
         | 
|  | 
