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 # 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): h, w, _ = img.shape img = cv2.putText(img, 'www.sommer-co.com', (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] # windows model_name = "AI Model " + model_name.split("/")[-1].split(".")[0] # linux print(model_name) 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 = '' url = os.environ['OA_IP_ADDRESS'] 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.Markdown("# Outfit Anyone v0.9") gr.HTML( """

MeinNeuesOutfit. Jedes Kleidungsstück zu jeder Person.

""") with gr.Row(): with gr.Column(): init_image = gr.Image(sources='clipboard', 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( """ """) 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"), os.path.join(os.path.dirname(__file__), "garments/top5.png"), os.path.join(os.path.dirname(__file__), "garments/top333.png"), os.path.join(os.path.dirname(__file__), "garments/dress1.png"), os.path.join(os.path.dirname(__file__), "garments/dress2.png"), ]) 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"), os.path.join(os.path.dirname(__file__), "garments/bottom2.PNG"), os.path.join(os.path.dirname(__file__), "garments/bottom3.JPG"), os.path.join(os.path.dirname(__file__), "garments/bottom4.PNG"), os.path.join(os.path.dirname(__file__), "garments/bottom5.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) # 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()