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import spaces
import gradio as gr
import torch
from PIL import Image
from diffusers import DiffusionPipeline
import random
from transformers import pipeline

torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
torch.backends.cuda.matmul.allow_tf32 = True

# ๋ฒˆ์—ญ ๋ชจ๋ธ ์ดˆ๊ธฐํ™”
translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")

# ๊ธฐ๋ณธ ๋ชจ๋ธ ๋ฐ LoRA ์„ค์ •
base_model = "black-forest-labs/FLUX.1-dev"
model_lora_repo = "Motas/Flux_Fashion_Photography_Style"  # ํŒจ์…˜ ๋ชจ๋ธ LoRA
clothes_lora_repo = "prithivMLmods/Canopus-Clothing-Flux-LoRA"  # ์˜๋ฅ˜ LoRA

pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
pipe.to("cuda")

MAX_SEED = 2**32-1

@spaces.GPU()
def generate_fashion(prompt, mode, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale, progress=gr.Progress(track_tqdm=True)):
    # ํ•œ๊ธ€ ๊ฐ์ง€ ๋ฐ ๋ฒˆ์—ญ
    def contains_korean(text):
        return any(ord('๊ฐ€') <= ord(char) <= ord('ํžฃ') for char in text)
    
    if contains_korean(prompt):
        translated = translator(prompt)[0]['translation_text']
        actual_prompt = translated
    else:
        actual_prompt = prompt

    # ๋ชจ๋“œ์— ๋”ฐ๋ฅธ LoRA ๋ฐ ํŠธ๋ฆฌ๊ฑฐ์›Œ๋“œ ์„ค์ •
    if mode == "Generate Model":
        pipe.load_lora_weights(model_lora_repo)
        trigger_word = "fashion photography, professional model"
    else:
        pipe.load_lora_weights(clothes_lora_repo)
        trigger_word = "upper clothing, fashion item"

    if randomize_seed:
        seed = random.randint(0, MAX_SEED)
    generator = torch.Generator(device="cuda").manual_seed(seed)

    progress(0, "Starting fashion generation...")

    for i in range(1, steps + 1):
        if i % (steps // 10) == 0:
            progress(i / steps * 100, f"Processing step {i} of {steps}...")

    image = pipe(
        prompt=f"{actual_prompt} {trigger_word}",
        num_inference_steps=steps,
        guidance_scale=cfg_scale,
        width=width,
        height=height,
        generator=generator,
        joint_attention_kwargs={"scale": lora_scale},
    ).images[0]

    progress(100, "Completed!")
    return image, seed

def generate_image(prompt, structure_image, style_image, depth_strength, style_strength):
    # ์‹ค์ œ ์ด๋ฏธ์ง€ ์ƒ์„ฑ ๋กœ์ง์„ ์—ฌ๊ธฐ์— ๊ตฌํ˜„
    return Image.new('RGB', (512, 512), 'white')

with gr.Blocks(theme="Yntec/HaleyCH_Theme_Orange") as app:
    gr.Markdown("# ๐ŸŽญ Fashion AI Studio")
    gr.Markdown("Generate fashion images and try on virtual clothing using AI")
    
    with gr.Tabs():
        # Virtual Try-On ํƒญ
        with gr.TabItem("๐Ÿ‘” Virtual Try-On"):
            with gr.Row():
                with gr.Column():
                    prompt_input = gr.Textbox(
                        label="Style Description", 
                        placeholder="Describe the desired style (e.g., 'person wearing elegant dress')"
                    )
                    with gr.Row():
                        with gr.Group():
                            structure_image = gr.Image(
                                label="Your Photo (Full-body)", 
                                type="filepath"
                            )
                            gr.Markdown("*Upload a clear, well-lit full-body photo*")
                            depth_strength = gr.Slider(
                                minimum=0, 
                                maximum=50, 
                                value=15, 
                                label="Fitting Strength"
                            )
                        with gr.Group():
                            style_image = gr.Image(
                                label="Clothing Item", 
                                type="filepath"
                            )
                            gr.Markdown("*Upload the clothing item you want to try on*")
                            style_strength = gr.Slider(
                                minimum=0, 
                                maximum=1, 
                                value=0.5, 
                                label="Style Transfer Strength"
                            )
                    tryon_btn = gr.Button("Generate Try-On")
                
                with gr.Column():
                    output_image = gr.Image(label="Generated Result")

        # Fashion Generation ํƒญ
        with gr.TabItem("๐Ÿ‘— Fashion Generation"):
            with gr.Column():
                # ๋ชจ๋“œ ์„ ํƒ
                with gr.Group():
                    mode = gr.Radio(
                        choices=["Generate Model", "Generate Clothes"],
                        label="Generation Mode",
                        value="Generate Model"
                    )
                
                # ํ”„๋กฌํ”„ํŠธ ์ž…๋ ฅ
                prompt = gr.TextArea(
                    label="โœ๏ธ Fashion Description (ํ•œ๊ธ€ ๋˜๋Š” ์˜์–ด)",
                    placeholder="ํŒจ์…˜ ๋ชจ๋ธ์ด๋‚˜ ์˜๋ฅ˜๋ฅผ ์„ค๋ช…ํ•˜์„ธ์š”...",
                    lines=5
                )
                
                # ๊ฒฐ๊ณผ ์ด๋ฏธ์ง€
                result = gr.Image(label="Generated Fashion")
                
                generate_button = gr.Button("๐Ÿš€ Generate Fashion")
                
                # ๊ณ ๊ธ‰ ์„ค์ • ์•„์ฝ”๋””์–ธ
                with gr.Accordion("๐ŸŽจ Advanced Options", open=False):
                    with gr.Row():
                        cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7.0)
                        steps = gr.Slider(label="Steps", minimum=1, maximum=100, value=30)
                        lora_scale = gr.Slider(label="LoRA Scale", minimum=0, maximum=1, value=0.85)
                    
                    with gr.Row():
                        width = gr.Slider(label="Width", minimum=256, maximum=1536, value=512)
                        height = gr.Slider(label="Height", minimum=256, maximum=1536, value=768)
                    
                    with gr.Row():
                        randomize_seed = gr.Checkbox(True, label="Randomize seed")
                        seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, value=42)

    # ์ด๋ฒคํŠธ ํ•ธ๋“ค๋Ÿฌ
    tryon_btn.click(
        fn=generate_image,
        inputs=[prompt_input, structure_image, style_image, depth_strength, style_strength],
        outputs=[output_image]
    )
    
    generate_button.click(
        generate_fashion,
        inputs=[prompt, mode, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale],
        outputs=[result, seed]
    )

if __name__ == "__main__":
    app.launch(share=True)