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on
CPU Upgrade
Running
on
CPU Upgrade
import os | |
import cv2 | |
from PIL import Image | |
import gradio as gr | |
import numpy as np | |
import random | |
import base64 | |
import requests | |
import json | |
import time | |
from requests.adapters import HTTPAdapter | |
def tryon(person_img, garment_img, seed, randomize_seed): | |
post_start_time = time.time() | |
if person_img is None or garment_img is None: | |
return None, None, "Empty image" | |
if randomize_seed: | |
seed = random.randint(0, MAX_SEED) | |
encoded_person_img = cv2.imencode('.jpg', cv2.cvtColor(person_img, cv2.COLOR_RGB2BGR))[1].tobytes() | |
encoded_person_img = base64.b64encode(encoded_person_img).decode('utf-8') | |
encoded_garment_img = cv2.imencode('.jpg', cv2.cvtColor(garment_img, cv2.COLOR_RGB2BGR))[1].tobytes() | |
encoded_garment_img = base64.b64encode(encoded_garment_img).decode('utf-8') | |
url = "http://" + os.environ['tryon_url'] + "Submit" | |
token = os.environ['token'] | |
cookie = os.environ['Cookie'] | |
referer = os.environ['referer'] | |
headers = {'Content-Type': 'application/json', 'token': token, 'Cookie': cookie, 'referer': referer} | |
data = { | |
"clothImage": encoded_garment_img, | |
"humanImage": encoded_person_img, | |
"seed": seed | |
} | |
try: | |
response = requests.post(url, headers=headers, data=json.dumps(data), timeout=50) | |
print("post response code", response.status_code) | |
if response.status_code == 200: | |
result = response.json()['result'] | |
status = result['status'] | |
if status == "success": | |
uuid = result['result'] | |
print(uuid) | |
except Exception as err: | |
print(f"Error: {err}") | |
raise gr.Error("Too many users, please try again later") | |
post_end_time = time.time() | |
print(f"post time used: {post_end_time-post_start_time}") | |
get_start_time =time.time() | |
time.sleep(9) | |
Max_Retry = 10 | |
result_img = None | |
for i in range(Max_Retry): | |
try: | |
url = "http://" + os.environ['tryon_url'] + "Query?taskId=" + uuid | |
response = requests.get(url, headers=headers, timeout=15) | |
print("get response code", response.status_code) | |
if response.status_code == 200: | |
result = response.json()['result'] | |
status = result['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.cvtColor(result_img, cv2.COLOR_RGB2BGR) | |
info = "Success" | |
break | |
elif status == "error": | |
raise gr.Error("Too many users, please try again later") | |
else: | |
print(response.text) | |
info = "URL error, pleace contact the admin" | |
except requests.exceptions.ReadTimeout: | |
print("timeout") | |
info = "Too many users, please try again later" | |
time.sleep(1) | |
get_end_time = time.time() | |
print(f"get time used: {get_end_time-get_start_time}") | |
return result_img, seed, info | |
def start_tryon(person_img, garment_img, seed, randomize_seed): | |
start_time = time.time() | |
if person_img is None or garment_img is None: | |
return None, None, "Empty image" | |
if randomize_seed: | |
seed = random.randint(0, MAX_SEED) | |
encoded_person_img = cv2.imencode('.jpg', cv2.cvtColor(person_img, cv2.COLOR_RGB2BGR))[1].tobytes() | |
encoded_person_img = base64.b64encode(encoded_person_img).decode('utf-8') | |
encoded_garment_img = cv2.imencode('.jpg', cv2.cvtColor(garment_img, cv2.COLOR_RGB2BGR))[1].tobytes() | |
encoded_garment_img = base64.b64encode(encoded_garment_img).decode('utf-8') | |
url = "http://" + os.environ['tryon_url'] | |
token = os.environ['token'] | |
cookie = os.environ['Cookie'] | |
referer = os.environ['referer'] | |
headers = {'Content-Type': 'application/json', 'token': token, 'Cookie': cookie, 'referer': referer} | |
data = { | |
"clothImage": encoded_garment_img, | |
"humanImage": encoded_person_img, | |
"seed": seed | |
} | |
result_img = None | |
try: | |
session = requests.Session() | |
response = session.post(url, headers=headers, data=json.dumps(data), timeout=60) | |
print("response code", response.status_code) | |
if response.status_code == 200: | |
result = response.json()['result'] | |
status = result['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.cvtColor(result_img, cv2.COLOR_RGB2BGR) | |
info = "Success" | |
else: | |
info = "Try again latter" | |
else: | |
print(response.text) | |
info = "URL error, pleace contact the admin" | |
except requests.exceptions.ReadTimeout: | |
print("timeout") | |
info = "Too many users, please try again later" | |
raise gr.Error("Too many users, please try again later") | |
except Exception as err: | |
print(f"其他错误: {err}") | |
info = "Error, pleace contact the admin" | |
end_time = time.time() | |
print(f"time used: {end_time-start_time}") | |
return result_img, seed, info | |
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: 430px; | |
} | |
#col-mid { | |
margin: 0 auto; | |
max-width: 430px; | |
} | |
#col-right { | |
margin: 0 auto; | |
max-width: 430px; | |
} | |
#col-showcase { | |
margin: 0 auto; | |
max-width: 1100px; | |
} | |
#button { | |
color: blue; | |
} | |
""" | |
def load_description(fp): | |
with open(fp, 'r', encoding='utf-8') as f: | |
content = f.read() | |
return content | |
def change_imgs(image1, image2): | |
return image1, image2 | |
with gr.Blocks(css=css) as Tryon: | |
gr.HTML(load_description("assets/title.md")) | |
with gr.Row(): | |
with gr.Column(elem_id = "col-left"): | |
gr.HTML(""" | |
<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;"> | |
<div> | |
Step 1. Upload a person image ⬇️ | |
</div> | |
</div> | |
""") | |
with gr.Column(elem_id = "col-mid"): | |
gr.HTML(""" | |
<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;"> | |
<div> | |
Step 2. Upload a garment image ⬇️ | |
</div> | |
</div> | |
""") | |
with gr.Column(elem_id = "col-right"): | |
gr.HTML(""" | |
<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;"> | |
<div> | |
Step 3. Press “Run” to get try-on results | |
</div> | |
</div> | |
""") | |
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=12, | |
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=12, | |
examples=garm_list_path | |
) | |
with gr.Column(elem_id = "col-right"): | |
image_out = gr.Image(label="Result", show_share_button=False) | |
with gr.Row(): | |
seed = gr.Slider( | |
label="Seed", | |
minimum=0, | |
maximum=MAX_SEED, | |
step=1, | |
value=0, | |
) | |
randomize_seed = gr.Checkbox(label="Random seed", value=True) | |
with gr.Row(): | |
seed_used = gr.Number(label="Seed used") | |
result_info = gr.Text(label="Response") | |
# try_button = gr.Button(value="Run", elem_id="button") | |
test_button = gr.Button(value="Run", elem_id="button") | |
# try_button.click(fn=start_tryon, inputs=[imgs, garm_img, seed, randomize_seed], outputs=[image_out, seed_used, result_info], api_name='tryon',concurrency_limit=10) | |
test_button.click(fn=tryon, inputs=[imgs, garm_img, seed, randomize_seed], outputs=[image_out, seed_used, result_info], api_name='tryon',concurrency_limit=10) | |
with gr.Column(elem_id = "col-showcase"): | |
gr.HTML(""" | |
<div style="display: flex; justify-content: center; align-items: center; text-align: center; font-size: 20px;"> | |
<div> </div> | |
<br> | |
<div> | |
Virtual try-on examples in pairs of person and garment images | |
</div> | |
</div> | |
""") | |
show_case = gr.Examples( | |
examples=[ | |
["assets/examples/model2.png", "assets/examples/garment2.png", "assets/examples/result2.png"], | |
["assets/examples/model3.png", "assets/examples/garment3.png", "assets/examples/result3.png"], | |
["assets/examples/model1.png", "assets/examples/garment1.png", "assets/examples/result1.png"], | |
], | |
inputs=[imgs, garm_img, image_out], | |
label=None | |
) | |
# ip = requests.get('http://ifconfig.me/ip', timeout=1).text.strip() | |
# print("ip address", ip) | |
Tryon.queue(max_size = 20).launch(max_threads = 5) | |