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import os |
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import cv2 |
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from PIL import Image |
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import gradio as gr |
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import numpy as np |
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import random |
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import base64 |
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import requests |
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import json |
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def start_tryon(person_img, garment_img, seed, randomize_seed): |
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if randomize_seed: |
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seed = random.randint(0, MAX_SEED) |
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encoded_person_img = cv2.imencode('.jpg', person_img)[1].tobytes() |
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encoded_person_img = base64.b64encode(encoded_person_img).decode('utf-8') |
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encoded_garment_img = cv2.imencode('.jpg', garment_img)[1].tobytes() |
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encoded_garment_img = base64.b64encode(encoded_garment_img).decode('utf-8') |
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url = "http://" + os.environ['tryon_url'] |
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token = os.environ['token'] |
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cookie = os.environ['Cookie'] |
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headers = {'Content-Type': 'application/json', 'token': token, 'Cookie': cookie} |
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data = { |
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"clothImage": encoded_garment_img, |
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"humanImage": encoded_person_img, |
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"seed": seed |
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} |
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response = requests.post(url, headers=headers, data=json.dumps(data)) |
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print("response code", response.status_code) |
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print("response", response) |
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if response.status_code == 200: |
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result = response.json() |
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result = base64.b64decode(result['images'][0]) |
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result_np = np.frombuffer(result, np.uint8) |
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result_img = cv2.imdecode(result_np, cv2.IMREAD_UNCHANGED) |
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return result_img, seed |
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MAX_SEED = 999999 |
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example_path = os.path.join(os.path.dirname(__file__), 'assets') |
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garm_list = os.listdir(os.path.join(example_path,"cloth")) |
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garm_list_path = [os.path.join(example_path,"cloth",garm) for garm in garm_list] |
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human_list = os.listdir(os.path.join(example_path,"human")) |
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human_list_path = [os.path.join(example_path,"human",human) for human in human_list] |
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css=""" |
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#col-left { |
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margin: 0 auto; |
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max-width: 350px; |
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} |
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#col-mid { |
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margin: 0 auto; |
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max-width: 350px; |
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} |
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#col-right { |
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margin: 0 auto; |
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max-width: 600px; |
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} |
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#button { |
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color: blue; |
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} |
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""" |
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def load_description(fp): |
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with open(fp, 'r', encoding='utf-8') as f: |
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content = f.read() |
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return content |
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with gr.Blocks(css=css) as Tryon: |
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gr.HTML(load_description("assets/title.md")) |
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with gr.Row(): |
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with gr.Column(elem_id = "col-left"): |
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imgs = gr.Image(label="Person image", sources='upload', type="numpy") |
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example = gr.Examples( |
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inputs=imgs, |
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examples_per_page=10, |
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examples=human_list_path |
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) |
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with gr.Column(elem_id = "col-mid"): |
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garm_img = gr.Image(label="Garment image", sources='upload', type="numpy") |
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example = gr.Examples( |
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inputs=garm_img, |
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examples_per_page=10, |
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examples=garm_list_path) |
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with gr.Column(elem_id = "col-right"): |
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image_out = gr.Image(label="Output", show_share_button=False) |
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seed_used = gr.Number(label="Seed Used") |
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try_button = gr.Button(value="Try-on", elem_id="button") |
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with gr.Column(): |
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with gr.Accordion(label="Advanced Settings", open=False): |
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seed = gr.Slider( |
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label="Seed", |
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minimum=0, |
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maximum=MAX_SEED, |
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step=1, |
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value=0, |
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) |
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randomize_seed = gr.Checkbox(label="Randomize seed", value=True) |
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try_button.click(fn=start_tryon, inputs=[imgs, garm_img, seed, randomize_seed], outputs=[image_out, seed_used], api_name='tryon') |
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ip = requests.get('http://ifconfig.me/ip', timeout=1).text.strip() |
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print("ip address", ip) |
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Tryon.queue(max_size=10).launch() |
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