lixiang46
test
6af3026
raw
history blame
3.66 kB
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 = "http://" + os.environ['tryon_url']
token = os.environ['token']
print(url, token)
headers = {'Content-Type': 'application/json', 'token': token}
data = {
"clothImage": encoded_garment_img,
"humanImage": encoded_person_img,
"seed": seed
}
# response = requests.post(url, headers=headers, data=json.dumps(data))
# print("response code", response.status_code)
# if response.status_code == 200:
# result = response.json()
# result = base64.b64decode(result['images'][0])
# 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: 600px;
}
#col-right {
margin: 0 auto;
max-width: 750px;
}
#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():
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():
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():
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()