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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()
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