import os import cv2 from PIL import Image import gradio as gr import numpy as np import random import base64 import requests import json def start_tryon(person_img, garment_img, seed, randomize_seed): if randomize_seed: seed = random.randint(0, MAX_SEED) encoded_person_img = cv2.imencode('.jpg', person_img)[1].tobytes() encoded_person_img = base64.b64encode(encoded_person_img).decode('utf-8') encoded_garment_img = cv2.imencode('.jpg', garment_img)[1].tobytes() encoded_garment_img = base64.b64encode(encoded_garment_img).decode('utf-8') url = "https://" + os.environ['tryon_url'] token = os.environ['token'] cookie = os.environ['Cookie'] headers = {'Content-Type': 'application/json', 'token': token, 'Cookie': cookie} data = { "clothImage": encoded_garment_img, "humanImage": encoded_person_img, "seed": seed } # print(url, token, cookie, encoded_garment_imgm, encoded_person_img) response = requests.post(url, headers=headers, data=json.dumps(data)) print("response code", response.status_code) print("response", response, type(response)) if response.status_code == 200: result = response.json()['result'] print("result", result) status = response['status'] if status == "success": result = base64.b64decode(result['result']) result_np = np.frombuffer(result, np.uint8) result_img = cv2.imdecode(result_np, cv2.IMREAD_UNCHANGED) # result_img = cv2.imdecode(np.frombuffer(base64.b64decode(encoded_person_img), np.uint8), cv2.IMREAD_UNCHANGED) return result_img, seed MAX_SEED = 999999 example_path = os.path.join(os.path.dirname(__file__), 'assets') garm_list = os.listdir(os.path.join(example_path,"cloth")) garm_list_path = [os.path.join(example_path,"cloth",garm) for garm in garm_list] human_list = os.listdir(os.path.join(example_path,"human")) human_list_path = [os.path.join(example_path,"human",human) for human in human_list] css=""" #col-left { margin: 0 auto; max-width: 380px; } #col-mid { margin: 0 auto; max-width: 380px; } #col-right { margin: 0 auto; max-width: 580px; } #button { color: blue; } """ def load_description(fp): with open(fp, 'r', encoding='utf-8') as f: content = f.read() return content with gr.Blocks(css=css) as Tryon: gr.HTML(load_description("assets/title.md")) with gr.Row(): with gr.Column(elem_id = "col-left"): imgs = gr.Image(label="Person image", sources='upload', type="numpy") # category = gr.Dropdown(label="Garment category", choices=['upper_body', 'lower_body', 'dresses'], value="upper_body") example = gr.Examples( inputs=imgs, examples_per_page=10, examples=human_list_path ) with gr.Column(elem_id = "col-mid"): garm_img = gr.Image(label="Garment image", sources='upload', type="numpy") example = gr.Examples( inputs=garm_img, examples_per_page=10, examples=garm_list_path) with gr.Column(elem_id = "col-right"): image_out = gr.Image(label="Output", show_share_button=False) seed_used = gr.Number(label="Seed Used") try_button = gr.Button(value="Try-on", elem_id="button") with gr.Column(): with gr.Accordion(label="Advanced Settings", open=False): seed = gr.Slider( label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0, ) randomize_seed = gr.Checkbox(label="Randomize seed", value=True) try_button.click(fn=start_tryon, inputs=[imgs, garm_img, seed, randomize_seed], outputs=[image_out, seed_used], api_name='tryon') ip = requests.get('http://ifconfig.me/ip', timeout=1).text.strip() print("ip address", ip) Tryon.queue(max_size=10).launch()