import os import cv2 from PIL import Image import gradio as gr import numpy as np import random import base64 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') return person_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') Tryon.queue(max_size=10).launch()