app.py

import os
import cv2
import gradio as gr
import numpy as np
import random

MAX_SEED = 999999
example_path = os.path.join(os.path.dirname(__file__), 'assets')

# Load example images
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]

def mock_tryon(person_img, garment_img, seed, randomize_seed, progress=gr.Progress()):
    progress(0, desc="Starting mock try-on...")
    
    if person_img is None or garment_img is None:
        gr.Warning("Please upload both images!")
        return None, None, "Error: Empty image"
    
    if randomize_seed:
        seed = random.randint(0, MAX_SEED)

    progress(0.3, desc="Processing person image...")
    # Convert to grayscale for demo (replace with actual try-on logic)
    person_gray = cv2.cvtColor(person_img, cv2.COLOR_RGB2GRAY)
    person_gray = cv2.cvtColor(person_gray, cv2.COLOR_GRAY2RGB)

    progress(0.6, desc="Adding garment...")
    # Resize garment to fit person (demo only)
    garment_resized = cv2.resize(garment_img, (person_img.shape[1], person_img.shape[0]))

    progress(0.8, desc="Blending images...")
    # Simple alpha blending (replace with real try-on)
    alpha = 0.7
    result = cv2.addWeighted(person_gray, 1-alpha, garment_resized, alpha, 0)

    progress(1.0, desc="Done!")
    return result, seed, "Mock try-on complete"

def load_description(fp):
    with open(fp, 'r', encoding='utf-8') as f:
        return f.read()

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; }
"""

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='text-align: center; font-size: 20px;'>Step 1. Upload person ⬇️</div>")
            imgs = gr.Image(label="Person", sources='upload', type="numpy")
            gr.Examples(inputs=imgs, examples_per_page=12, examples=human_list_path)
        
        with gr.Column(elem_id="col-mid"):
            gr.HTML("<div style='text-align: center; font-size: 20px;'>Step 2. Upload garment ⬇️</div>")
            garm_img = gr.Image(label="Garment", sources='upload', type="numpy")
            gr.Examples(inputs=garm_img, examples_per_page=12, examples=garm_list_path)
        
        with gr.Column(elem_id="col-right"):
            gr.HTML("<div style='text-align: center; font-size: 20px;'>Step 3. Click Run</div>")
            image_out = gr.Image(label="Result")
            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="Status")
            test_button = gr.Button("Run", elem_id="button")

    test_button.click(
        fn=mock_tryon,
        inputs=[imgs, garm_img, seed, randomize_seed],
        outputs=[image_out, seed_used, result_info],
        concurrency_limit=5
    )

    with gr.Column(elem_id="col-showcase"):
        gr.HTML("<div style='text-align: center; font-size: 20px;'>Examples</div>")
        gr.Examples(
            examples=[
                [human_list_path[0], garm_list_path[0]],  # First human + first garment
                [human_list_path[1], garm_list_path[1]],  # Second pair
            ],
            inputs=[imgs, garm_img],
            outputs=[image_out]
        )

Tryon.queue().launch()