| import gradio as gr |
| import numpy as np |
| import random |
| import torch |
| from diffusers import DiffusionPipeline |
| import spaces |
| from transformers import pipeline |
|
|
| |
| dtype = torch.bfloat16 |
| device = "cuda" if torch.cuda.is_available() else "cpu" |
|
|
| |
| translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en", device="cpu") |
|
|
| |
| pipe = DiffusionPipeline.from_pretrained( |
| "black-forest-labs/FLUX.1-schnell", |
| torch_dtype=dtype |
| ).to(device) |
|
|
| MAX_SEED = np.iinfo(np.int32).max |
| MAX_IMAGE_SIZE = 2048 |
|
|
| |
| EXAMPLES = [ |
| { |
| "title": "Smart Coffee Machine", |
| "prompt": """A sleek industrial design concept for a coffee machine: |
| - Curved metallic body with minimal bezel |
| - Touchscreen panel for settings |
| - Modern matte black finish |
| - Hand-drawn concept sketch style""", |
| "width": 1024, |
| "height": 1024 |
| }, |
| { |
| "title": "AI Speaker", |
| "prompt": """A futuristic AI speaker concept: |
| - Cylindrical shape with LED ring near top |
| - Voice assistant concept, floating panel controls |
| - Smooth glossy finish with minimal seams |
| - Techy, modern look in grayscale""", |
| "width": 1024, |
| "height": 1024 |
| }, |
| { |
| "title": "Next-Gen Smartphone", |
| "prompt": """A wireframe-style concept for a bezel-less smartphone: |
| - Edge-to-edge display |
| - Integrated camera under screen |
| - Metallic frame, minimal ports |
| - Sleek, glossy black design""", |
| "width": 1024, |
| "height": 1024 |
| }, |
| { |
| "title": "Futuristic Electric Bicycle", |
| "prompt": """An industrial design sketch of an electric bike: |
| - Lightweight carbon frame, aerodynamic lines |
| - Integrated battery, sleek display on handlebars |
| - Neon color highlights on wheels |
| - High-tech vibe, minimal clutter""", |
| "width": 1024, |
| "height": 1024 |
| }, |
| { |
| "title": "Concept Car Interior", |
| "prompt": """A luxurious and futuristic car interior concept: |
| - Wrap-around digital dashboard |
| - Minimalistic steering control, seat controls on touchscreen |
| - Ambient LED accent lights |
| - Soft leather seats, bright accent stitching""", |
| "width": 1024, |
| "height": 1024 |
| } |
| ] |
|
|
| |
| GRADIO_EXAMPLES = [ |
| [example["prompt"], example["width"], example["height"]] |
| for example in EXAMPLES |
| ] |
|
|
| |
| def contains_korean(text): |
| for char in text: |
| if ord('๊ฐ') <= ord(char) <= ord('ํฃ'): |
| return True |
| return False |
|
|
| |
| @spaces.GPU() |
| def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, progress=gr.Progress(track_tqdm=True)): |
| |
| original_prompt = prompt |
| translated = False |
| |
| if contains_korean(prompt): |
| translated = True |
| translation = translator(prompt) |
| prompt = translation[0]['translation_text'] |
| |
| |
| if randomize_seed: |
| seed = random.randint(0, MAX_SEED) |
| |
| generator = torch.Generator().manual_seed(seed) |
| |
| |
| image = pipe( |
| prompt=prompt, |
| width=width, |
| height=height, |
| num_inference_steps=num_inference_steps, |
| generator=generator, |
| guidance_scale=0.0 |
| ).images[0] |
| |
| |
| if translated: |
| return image, seed, original_prompt, prompt |
| else: |
| return image, seed, None, None |
|
|
| |
| css = """ |
| .container { |
| display: flex; |
| flex-direction: row; |
| height: 100%; |
| } |
| .input-column { |
| flex: 1; |
| padding: 20px; |
| border-right: 2px solid #eee; |
| max-width: 800px; |
| } |
| .examples-column { |
| flex: 1; |
| padding: 20px; |
| overflow-y: auto; |
| background: #f7f7f7; |
| } |
| .title { |
| text-align: center; |
| color: #2a2a2a; |
| padding: 20px; |
| font-size: 2.5em; |
| font-weight: bold; |
| background: linear-gradient(90deg, #f0f0f0 0%, #ffffff 100%); |
| border-bottom: 3px solid #ddd; |
| margin-bottom: 30px; |
| } |
| .subtitle { |
| text-align: center; |
| color: #666; |
| margin-bottom: 30px; |
| } |
| .input-box { |
| background: white; |
| padding: 20px; |
| border-radius: 10px; |
| box-shadow: 0 2px 10px rgba(0,0,0,0.1); |
| margin-bottom: 20px; |
| width: 100%; |
| } |
| .input-box textarea { |
| width: 100% !important; |
| min-width: 600px !important; |
| font-size: 14px !important; |
| line-height: 1.5 !important; |
| padding: 12px !important; |
| } |
| .example-card { |
| background: white; |
| padding: 15px; |
| margin: 10px 0; |
| border-radius: 8px; |
| box-shadow: 0 2px 5px rgba(0,0,0,0.05); |
| } |
| .example-title { |
| font-weight: bold; |
| color: #2a2a2a; |
| margin-bottom: 10px; |
| } |
| .contain { |
| max-width: 1400px !important; |
| margin: 0 auto !important; |
| } |
| .input-area { |
| flex: 2 !important; |
| } |
| .examples-area { |
| flex: 1 !important; |
| } |
| .translation-info { |
| background-color: #f8f9fa; |
| border-left: 4px solid #17a2b8; |
| padding: 10px 15px; |
| margin-top: 10px; |
| border-radius: 4px; |
| font-size: 14px; |
| } |
| """ |
|
|
| with gr.Blocks(css=css) as demo: |
| gr.Markdown( |
| """ |
| <div class="title">GINI Design</div> |
| <div class="subtitle">Generate sleek industrial/product design concepts with FLUX AI</div> |
| """) |
|
|
| with gr.Row(equal_height=True): |
| |
| with gr.Column(elem_id="input-column", scale=2): |
| with gr.Group(elem_classes="input-box"): |
| prompt = gr.Text( |
| label="Design Prompt (ํ๊ตญ์ด ๋๋ ์์ด๋ก ์
๋ ฅํ์ธ์)", |
| placeholder="Enter your product design concept details in Korean or English...", |
| lines=10, |
| elem_classes="prompt-input" |
| ) |
| run_button = gr.Button("Generate Design", variant="primary") |
| result = gr.Image(label="Generated Design") |
| |
| |
| original_prompt = gr.Textbox(visible=False) |
| translated_prompt = gr.Textbox(visible=False) |
| translation_info = gr.Markdown(visible=False, elem_classes="translation-info") |
| |
| |
| def update_translation_info(original, translated): |
| if original and translated: |
| return gr.update(visible=True, value=f"๐ Korean prompt was translated to English:\n\n**Original:** {original}\n\n**Translated:** {translated}") |
| else: |
| return gr.update(visible=False) |
| |
| with gr.Accordion("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) |
| |
| with gr.Row(): |
| width = gr.Slider( |
| label="Width", |
| minimum=256, |
| maximum=MAX_IMAGE_SIZE, |
| step=32, |
| value=1024, |
| ) |
| height = gr.Slider( |
| label="Height", |
| minimum=256, |
| maximum=MAX_IMAGE_SIZE, |
| step=32, |
| value=1024, |
| ) |
| |
| num_inference_steps = gr.Slider( |
| label="Number of inference steps", |
| minimum=1, |
| maximum=50, |
| step=1, |
| value=4, |
| ) |
| |
| |
| with gr.Column(elem_id="examples-column", scale=1): |
| gr.Markdown("### Example Product Designs") |
| for example in EXAMPLES: |
| with gr.Group(elem_classes="example-card"): |
| gr.Markdown(f"#### {example['title']}") |
| gr.Markdown(f"```\n{example['prompt']}\n```") |
| |
| def create_example_handler(ex): |
| def handler(): |
| return { |
| prompt: ex["prompt"], |
| width: ex["width"], |
| height: ex["height"] |
| } |
| return handler |
| |
| gr.Button("Use This Example", size="sm").click( |
| fn=create_example_handler(example), |
| outputs=[prompt, width, height] |
| ) |
|
|
| |
| gr.on( |
| triggers=[run_button.click, prompt.submit], |
| fn=infer, |
| inputs=[prompt, seed, randomize_seed, width, height, num_inference_steps], |
| outputs=[result, seed, original_prompt, translated_prompt] |
| ) |
| |
| |
| gr.on( |
| triggers=[original_prompt.change, translated_prompt.change], |
| fn=update_translation_info, |
| inputs=[original_prompt, translated_prompt], |
| outputs=[translation_info] |
| ) |
|
|
| if __name__ == "__main__": |
| demo.queue() |
| demo.launch( |
| server_name="0.0.0.0", |
| server_port=7860, |
| share=False, |
| show_error=True, |
| debug=True |
| ) |