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import gradio as gr |
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import spaces |
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from model import ModelHandler |
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from generator import Generator |
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from config import Config |
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print("Initializing Application...") |
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handler = ModelHandler() |
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handler.load_models() |
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gen = Generator(handler) |
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@spaces.GPU(duration=20) |
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def process_text( |
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prompt, |
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negative_prompt, |
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aspect_ratio, |
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cfg_scale, |
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steps, |
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seed |
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): |
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try: |
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print("--- Starting Generation ---") |
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result = gen.predict( |
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user_prompt=prompt, |
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negative_prompt=negative_prompt, |
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aspect_ratio=aspect_ratio, |
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guidance_scale=cfg_scale, |
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num_inference_steps=steps, |
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seed=seed |
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) |
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print("--- Generation Complete ---") |
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return result |
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except Exception as e: |
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print(f"Error during generation: {e}") |
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raise gr.Error(f"An error occurred: {str(e)}") |
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with gr.Blocks(title="Pixel Art Generator", theme=gr.themes.Soft()) as demo: |
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gr.Markdown( |
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""" |
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# 🎮 Text to Pixel Art |
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Type a prompt to generate high-quality pixel art scenes. |
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""" |
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) |
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with gr.Row(): |
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with gr.Column(scale=2): |
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prompt = gr.Textbox( |
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label="Prompt", |
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placeholder="e.g. cyberpunk city street at night, rain", |
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info="The trigger words 'p1x3l4rt, pixel art' are added automatically." |
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) |
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negative_prompt = gr.Textbox( |
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label="Negative Prompt", |
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placeholder="e.g., blurry, text, watermark, bad art...", |
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value=Config.DEFAULT_NEGATIVE_PROMPT |
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) |
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with gr.Accordion("Settings", open=True): |
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aspect_ratio = gr.Dropdown( |
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label="Aspect Ratio", |
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choices=list(Config.ASPECT_RATIOS.keys()), |
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value=Config.DEFAULT_ASPECT_RATIO, |
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info="Image dimensions (all ~1MP resolution)" |
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) |
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seed = gr.Number( |
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label="Seed", |
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value=-1, |
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info="-1 for random", |
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precision=0 |
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) |
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cfg_scale = gr.Slider( |
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elem_id="cfg_scale", |
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minimum=1.0, |
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maximum=5.0, |
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step=0.1, |
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value=Config.CGF_SCALE, |
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label="CFG Scale" |
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) |
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steps = gr.Slider( |
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elem_id="steps", |
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minimum=4, |
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maximum=20, |
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step=1, |
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value=Config.STEPS_NUMBER, |
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label="Steps" |
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) |
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run_btn = gr.Button("Generate", variant="primary") |
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with gr.Column(scale=1): |
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output_img = gr.Image(label="Result") |
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all_inputs = [ |
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prompt, |
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negative_prompt, |
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aspect_ratio, |
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cfg_scale, |
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steps, |
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seed |
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] |
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run_btn.click( |
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fn=process_text, |
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inputs=all_inputs, |
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outputs=[output_img] |
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) |
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if __name__ == "__main__": |
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demo.queue(max_size=20, api_open=True) |
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demo.launch( |
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server_name="0.0.0.0", |
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server_port=7860, |
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show_api=True |
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) |
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