Upload generate_ltx.py with huggingface_hub
Browse files- generate_ltx.py +59 -0
generate_ltx.py
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#!/usr/bin/env python3
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"""
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Generate video with PolarQuant PQ5 LTX-2.3.
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Usage:
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python generate_ltx.py --prompt "A cat playing piano" --output cat.mp4
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python generate_ltx.py --prompt "Ocean waves" --image ref.jpg --output ocean.mp4
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"""
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import argparse, os, subprocess, sys
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def main():
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parser = argparse.ArgumentParser(description="LTX-2.3 Video Generation (PQ5)")
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parser.add_argument("--prompt", type=str, required=True)
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parser.add_argument("--image", type=str, help="Reference image for image-to-video")
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parser.add_argument("--output", type=str, default="output.mp4")
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parser.add_argument("--model-dir", type=str, default="./LTX-PQ5")
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parser.add_argument("--steps", type=int, default=50)
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parser.add_argument("--height", type=int, default=480)
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parser.add_argument("--width", type=int, default=704)
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parser.add_argument("--frames", type=int, default=97)
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args = parser.parse_args()
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model_dir = os.path.abspath(args.model_dir)
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code_dir = os.path.join(model_dir, "ltx_code")
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model_path = os.path.join(model_dir, "ltx-2.3-22b-dev.safetensors")
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if not os.path.exists(model_path):
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print("Error: Run `python setup.py` first.")
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sys.exit(1)
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print("=" * 60)
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print(f" LTX-2.3 Video Generation (PQ5)")
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print(f" Prompt: {args.prompt}")
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print(f" Resolution: {args.width}x{args.height}, {args.frames} frames")
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print("=" * 60)
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# Use ltx-pipelines for inference
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cmd = [
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sys.executable, "-m", "ltx_pipelines.generate",
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"--model_path", model_path,
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"--prompt", args.prompt,
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"--output_path", args.output,
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"--height", str(args.height),
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"--width", str(args.width),
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"--num_frames", str(args.frames),
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"--num_inference_steps", str(args.steps),
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]
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if args.image:
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cmd.extend(["--image_path", args.image])
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result = subprocess.run(cmd, cwd=code_dir)
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if os.path.exists(args.output):
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print(f"\nDone! {args.output} ({os.path.getsize(args.output)/1e6:.1f} MB)")
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else:
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print(f"\nFailed. Check LTX-2 docs: {code_dir}/packages/ltx-pipelines/README.md")
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if __name__ == "__main__":
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main()
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