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import sys |
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import click |
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import gradio as gr |
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sys.path.append("..") |
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from cli import configure_model, generate_video |
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with gr.Blocks() as demo: |
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gr.Markdown("Video Generator") |
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with gr.Row(): |
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prompt = gr.Textbox( |
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label="Prompt", |
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value="A hand with delicate fingers picks up a bright yellow lemon from a wooden bowl filled with lemons and sprigs of mint against a peach-colored background. The hand gently tosses the lemon up and catches it, showcasing its smooth texture. A beige string bag sits beside the bowl, adding a rustic touch to the scene. Additional lemons, one halved, are scattered around the base of the bowl. The even lighting enhances the vibrant colors and creates a fresh, inviting atmosphere.", |
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) |
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negative_prompt = gr.Textbox(label="Negative Prompt", value="") |
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seed = gr.Number(label="Seed", value=1710977262, precision=0) |
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with gr.Row(): |
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width = gr.Number(label="Width", value=848, precision=0) |
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height = gr.Number(label="Height", value=480, precision=0) |
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num_frames = gr.Number(label="Number of Frames", value=163, precision=0) |
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with gr.Row(): |
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cfg_scale = gr.Number(label="CFG Scale", value=6.0) |
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num_inference_steps = gr.Number(label="Number of Inference Steps", value=100, precision=0) |
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btn = gr.Button("Generate Video") |
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output = gr.Video() |
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btn.click( |
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generate_video, |
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inputs=[ |
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prompt, |
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negative_prompt, |
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width, |
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height, |
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num_frames, |
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seed, |
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cfg_scale, |
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num_inference_steps, |
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], |
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outputs=output, |
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) |
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@click.command() |
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@click.option("--model_dir", required=True, help="Path to the model directory.") |
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@click.option("--lora_path", required=False, help="Path to the lora file.") |
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@click.option("--cpu_offload", is_flag=True, help="Whether to offload model to CPU") |
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def launch(model_dir, lora_path, cpu_offload): |
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configure_model(model_dir, lora_path, cpu_offload) |
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demo.launch() |
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if __name__ == "__main__": |
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launch() |
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