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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 | |
| # ๋ฒ์ญ ๋ชจ๋ธ ์ด๊ธฐํ | |
| translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en") | |
| # ๊ธฐ๋ณธ ๋ชจ๋ธ ๋ฐ LoRA ์ค์ | |
| base_model = "black-forest-labs/FLUX.1-dev" | |
| model_lora_repo = "Motas/Flux_Fashion_Photography_Style" | |
| clothes_lora_repo = "prithivMLmods/Canopus-Clothing-Flux-LoRA" | |
| pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16) | |
| pipe.to("cuda") | |
| MAX_SEED = 2**32-1 | |
| # ์์ ํ๋กฌํํธ ์ ์ | |
| model_examples = [ | |
| "professional fashion model wearing elegant black dress in studio lighting", | |
| "fashion model in casual street wear, urban background", | |
| "high fashion model in avant-garde outfit on runway" | |
| ] | |
| clothes_examples = [ | |
| "luxurious red evening gown with detailed embroidery", | |
| "casual denim jacket with vintage wash", | |
| "modern minimalist white blazer with clean lines" | |
| ] | |
| def generate_fashion(prompt, mode, cfg_scale, steps, randomize_seed, seed, width, height, lora_scale, progress=gr.Progress(track_tqdm=True)): | |
| if not prompt: | |
| return None, seed | |
| def contains_korean(text): | |
| return any(ord('๊ฐ') <= ord(char) <= ord('ํฃ') for char in text) | |
| if contains_korean(prompt): | |
| translated = translator(prompt)[0]['translation_text'] | |
| actual_prompt = translated | |
| else: | |
| actual_prompt = prompt | |
| if mode == "ํจ์ ๋ชจ๋ธ ์์ฑ": | |
| 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) | |
| 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] | |
| return image, seed | |
| with gr.Blocks(theme="Yntec/HaleyCH_Theme_Orange") as app: | |
| gr.Markdown("# ๐ญ Fashion AI Studio") | |
| with gr.Column(): | |
| mode = gr.Radio( | |
| choices=["Person", "Clothes"], | |
| label="Generation", | |
| value="Fashion Model" | |
| ) | |
| prompt = gr.TextArea( | |
| label="โ๏ธ Prompt (ํ๊ธ ์ง์)", | |
| placeholder="Text Input Prompt", | |
| lines=3 | |
| ) | |
| # ์์ ์น์ ์ ๋ชจ๋๋ณ๋ก ๋ถ๋ฆฌ | |
| with gr.Column(visible=True) as model_examples_container: | |
| gr.Examples( | |
| examples=model_examples, | |
| inputs=prompt, | |
| label="Examples(person)" | |
| ) | |
| with gr.Column(visible=False) as clothes_examples_container: | |
| gr.Examples( | |
| examples=clothes_examples, | |
| inputs=prompt, | |
| label="Examples(clothes)" | |
| ) | |
| result = gr.Image(label="Generated Image") | |
| generate_button = gr.Button("๐ START") | |
| with gr.Accordion("๐จ OPTION", 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="์๋ ๋๋คํ") | |
| seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, value=42) | |
| def update_visibility(mode): | |
| return ( | |
| gr.update(visible=(mode == "Person")), | |
| gr.update(visible=(mode == "Clothes")) | |
| ) | |
| mode.change( | |
| fn=update_visibility, | |
| inputs=[mode], | |
| outputs=[model_examples_container, clothes_examples_container] | |
| ) | |
| 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) |