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