import asyncio import base64 import json import os import random import cv2 import gradio as gr import numpy as np import requests from PIL import Image, ImageDraw, ImageFont # from IPython import embed machine_number = 0 model = os.path.join(os.path.dirname(__file__), "models/eva/Eva_0.png") MODEL_MAP = { "AI Model Oroton": "models/oroton/model.png", "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] # 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( """
""" ) 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 Oroton") ), 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( """