import os import cv2 as cv import numpy as np import json import random from PIL import Image, ImageDraw, ImageFont import asyncio import socket import requests import base64 import gradio as gr # from IPython import embed 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: cv.Mat) -> cv.Mat: h, w, _ = img.shape img = cv.putText(img, 'Powered by OutfitAnyone', (int(0.3*w), h-20), cv.FONT_HERSHEY_PLAIN, 2, (128, 128, 128), 2, cv.LINE_AA) return img def get_tryon_result(model_name: str, garment1: cv.Mat, garment2: cv.Mat | None, seed: int = 1234) -> cv.Mat: #model_name = "AI Model " + model_name.split("\\")[-1].split(".")[0] # windows model_name = "AI Model " + model_name.split("/")[-1].split(".")[0] # linux print(model_name) encoded_garment1 = cv.imencode('.jpg', garment1)[1].tobytes() encoded_garment1 = base64.b64encode(encoded_garment1).decode('utf-8') if garment2 is not None: encoded_garment2 = cv.imencode('.jpg', garment2)[1].tobytes() encoded_garment2 = base64.b64encode(encoded_garment2).decode('utf-8') else: encoded_garment2 = '' host_ip = socket.gethostbyname(socket.gethostname()) url = f"https://{host_ip}:192.168.115.27" 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 = cv.imdecode(result_np, cv.IMREAD_UNCHANGED) else: print('server error!') final_img = add_waterprint(result_img) return final_img '''height, width = 500, 500 # Adjust dimensions as needed channels = 3 # 3 for RGB, 1 for grayscale result_img = np.zeros((height, width, channels), dtype=np.uint8) result_img[:] = (255, 0, 0) # Set the image to solid blue color # final_img = add_waterprint(result_img) return result_img''' with gr.Blocks(css = ".output-image, .input-image, .image-preview {height: 400px !important} ") as demo: # gr.Markdown("# Outfit Anyone v0.9") gr.HTML( """

Outfit Anyone: Ultra-high quality virtual try-on for Any Clothing and Any Person

""") with gr.Row(): with gr.Column(): init_image = gr.Image(type="filepath", label="model", value=model) 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')), os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Rouyan_2')), os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Eva_0')), os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Simon_1')), os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Eva_1')), os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Simon_0')), os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Xuanxuan_0')), os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Xuanxuan_2')), os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yaqi_1')), os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yifeng_0')), os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yifeng_3')), os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Rouyan_1')), os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yifeng_2')), os.path.join(os.path.dirname(__file__), MODEL_MAP.get('AI Model Yaqi_0')), ]) with gr.Column(): gr.HTML( """

Models are fixed and cannot be uploaded or modified; we only support users uploading their own garments.

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.

""") with gr.Row(): garment_top = gr.Image(type="numpy", label="top garment") garment_down = gr.Image(type="numpy", label="lower garment") 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], show_progress=True, concurrency_limit=2) # Examples 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"], ["examples/basemodel.png", "examples/garment2.png", "examples/result2.png"], ["examples/basemodel.png", "examples/garment3.png", "examples/result3.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 alibaba", ip) demo.queue(max_size=10) demo.launch()