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import os |
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import cv2 |
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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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import time |
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def tryon(person_img, garment_img, seed, randomize_seed): |
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post_start_time = time.time() |
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if person_img is None or garment_img is None: |
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gr.Warning("Empty image") |
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return None, None, "Empty image" |
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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', cv2.cvtColor(person_img, cv2.COLOR_RGB2BGR))[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', cv2.cvtColor(garment_img, cv2.COLOR_RGB2BGR))[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'] + "Submit" |
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token = os.environ['token'] |
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cookie = os.environ['Cookie'] |
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referer = os.environ['referer'] |
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headers = {'Content-Type': 'application/json', 'token': token, 'Cookie': cookie, 'referer': referer} |
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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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try: |
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response = requests.post(url, headers=headers, data=json.dumps(data), timeout=50) |
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if response.status_code == 200: |
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result = response.json()['result'] |
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status = result['status'] |
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if status == "success": |
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uuid = result['result'] |
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except Exception as err: |
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print(f"Post Exception Error: {err}") |
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raise gr.Error("Too many users, please try again later") |
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post_end_time = time.time() |
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print(f"post time used: {post_end_time-post_start_time}") |
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get_start_time =time.time() |
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time.sleep(9) |
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Max_Retry = 12 |
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result_img = None |
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info = "" |
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err_log = "" |
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for i in range(Max_Retry): |
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try: |
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url = "http://" + os.environ['tryon_url'] + "Query?taskId=" + uuid |
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response = requests.get(url, headers=headers, timeout=20) |
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if response.status_code == 200: |
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result = response.json()['result'] |
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status = result['status'] |
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if status == "success": |
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result = base64.b64decode(result['result']) |
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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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result_img = cv2.cvtColor(result_img, cv2.COLOR_RGB2BGR) |
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info = "Success" |
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break |
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elif status == "error": |
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err_log = f"Status is Error" |
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info = "Error" |
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break |
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else: |
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err_log = "URL error, pleace contact the admin" |
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info = "URL error, pleace contact the admin" |
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break |
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except requests.exceptions.ReadTimeout: |
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err_log = "Http Timeout" |
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info = "Http Timeout, please try again later" |
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except Exception as err: |
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err_log = f"Get Exception Error: {err}" |
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time.sleep(1) |
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get_end_time = time.time() |
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print(f"get time used: {get_end_time-get_start_time}") |
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print(f"all time used: {get_end_time-get_start_time+post_end_time-post_start_time}") |
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if info == "": |
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err_log = f"No image after {Max_Retry} retries" |
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info = "Too many users, please try again later" |
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if info != "Success": |
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print(f"Error Log: {err_log}") |
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gr.Warning("Too many users, please try again later") |
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return result_img, seed, info |
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def start_tryon(person_img, garment_img, seed, randomize_seed): |
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start_time = time.time() |
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if person_img is None or garment_img is None: |
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return None, None, "Empty image" |
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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', cv2.cvtColor(person_img, cv2.COLOR_RGB2BGR))[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', cv2.cvtColor(garment_img, cv2.COLOR_RGB2BGR))[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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referer = os.environ['referer'] |
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headers = {'Content-Type': 'application/json', 'token': token, 'Cookie': cookie, 'referer': referer} |
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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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result_img = None |
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try: |
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session = requests.Session() |
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response = session.post(url, headers=headers, data=json.dumps(data), timeout=60) |
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print("response code", response.status_code) |
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if response.status_code == 200: |
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result = response.json()['result'] |
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status = result['status'] |
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if status == "success": |
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result = base64.b64decode(result['result']) |
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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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result_img = cv2.cvtColor(result_img, cv2.COLOR_RGB2BGR) |
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info = "Success" |
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else: |
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info = "Try again latter" |
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else: |
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print(response.text) |
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info = "URL error, pleace contact the admin" |
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except requests.exceptions.ReadTimeout: |
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print("timeout") |
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info = "Too many users, please try again later" |
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raise gr.Error("Too many users, please try again later") |
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except Exception as err: |
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print(f"其他错误: {err}") |
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info = "Error, pleace contact the admin" |
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end_time = time.time() |
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print(f"time used: {end_time-start_time}") |
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return result_img, seed, info |
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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: 430px; |
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} |
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#col-mid { |
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margin: 0 auto; |
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max-width: 430px; |
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} |
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#col-right { |
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margin: 0 auto; |
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max-width: 430px; |
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} |
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#col-showcase { |
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margin: 0 auto; |
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max-width: 1100px; |
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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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def change_imgs(image1, image2): |
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return image1, image2 |
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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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gr.HTML(""" |
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<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;"> |
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<div> |
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Step 1. Upload a person image ⬇️ |
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</div> |
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</div> |
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""") |
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with gr.Column(elem_id = "col-mid"): |
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gr.HTML(""" |
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<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;"> |
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<div> |
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Step 2. Upload a garment image ⬇️ |
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</div> |
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</div> |
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""") |
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with gr.Column(elem_id = "col-right"): |
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gr.HTML(""" |
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<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;"> |
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<div> |
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Step 3. Press “Run” to get try-on results |
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</div> |
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</div> |
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""") |
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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=12, |
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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=12, |
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examples=garm_list_path |
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) |
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with gr.Column(elem_id = "col-right"): |
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image_out = gr.Image(label="Result", show_share_button=False) |
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with gr.Row(): |
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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="Random seed", value=True) |
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with gr.Row(): |
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seed_used = gr.Number(label="Seed used") |
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result_info = gr.Text(label="Response") |
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test_button = gr.Button(value="Run", elem_id="button") |
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test_button.click(fn=tryon, inputs=[imgs, garm_img, seed, randomize_seed], outputs=[image_out, seed_used, result_info], api_name=False, concurrency_limit=45) |
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with gr.Column(elem_id = "col-showcase"): |
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gr.HTML(""" |
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<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;"> |
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<div> </div> |
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<br> |
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<div> |
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Virtual try-on examples in pairs of person and garment images |
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</div> |
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</div> |
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""") |
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show_case = gr.Examples( |
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examples=[ |
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["assets/examples/model2.png", "assets/examples/garment2.png", "assets/examples/result2.png"], |
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["assets/examples/model3.png", "assets/examples/garment3.png", "assets/examples/result3.png"], |
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["assets/examples/model1.png", "assets/examples/garment1.png", "assets/examples/result1.png"], |
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], |
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inputs=[imgs, garm_img, image_out], |
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label=None |
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) |
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Tryon.queue(api_open=False).launch(show_api=False) |
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