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| 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() | |