Files
ltx2-mps/generate.py
Norbert Schmidt c75e87b9be Initial release
2026-01-11 10:17:37 +01:00

107 lines
3.6 KiB
Python

#!/usr/bin/env python3
"""
LTX-2 Video Generator for Apple Silicon (MPS)
Usage:
python generate.py "Your prompt here" -o output.mp4 [options]
Options:
--width Video width (default: 512, must be divisible by 32)
--height Video height (default: 320, must be divisible by 32)
--frames Number of frames (default: 25, must be 8n+1)
--steps Inference steps (default: 20)
--guidance Guidance scale (default: 5.0)
--fps Output FPS (default: 24)
--seed Random seed (optional)
-n Negative prompt (optional)
"""
import argparse
import sys
import torch
from diffusers import LTX2Pipeline
from diffusers.utils import export_to_video
def main():
parser = argparse.ArgumentParser(description="LTX-2 Video Generator for MPS")
parser.add_argument("prompt", help="Text prompt for video generation")
parser.add_argument("-o", "--output", default="output.mp4", help="Output video path")
parser.add_argument("-n", "--negative-prompt", default="", help="Negative prompt")
parser.add_argument("--steps", type=int, default=20, help="Inference steps")
parser.add_argument("--guidance", type=float, default=5.0, help="Guidance scale")
parser.add_argument("--width", type=int, default=512, help="Video width")
parser.add_argument("--height", type=int, default=320, help="Video height")
parser.add_argument("--frames", type=int, default=25, help="Number of frames")
parser.add_argument("--fps", type=int, default=24, help="Frames per second")
parser.add_argument("--seed", type=int, default=None, help="Random seed")
args = parser.parse_args()
# Validate dimensions
if args.width % 32 != 0:
print(f"Error: width must be divisible by 32 (got {args.width})")
sys.exit(1)
if args.height % 32 != 0:
print(f"Error: height must be divisible by 32 (got {args.height})")
sys.exit(1)
if (args.frames - 1) % 8 != 0:
valid = [8*i + 1 for i in range(1, 13)]
print(f"Error: frames must be 8n+1 (valid: {valid})")
sys.exit(1)
# Check MPS availability
if not torch.backends.mps.is_available():
print("Warning: MPS not available, falling back to CPU (will be slow)")
device = "cpu"
else:
device = "mps"
print(f"Using MPS (Apple Silicon GPU)")
# Load model
print("Loading LTX-2 model (this may take a while on first run)...")
pipe = LTX2Pipeline.from_pretrained(
"Lightricks/LTX-2",
torch_dtype=torch.bfloat16
)
pipe.to(device)
print("Model loaded!")
# Set up generator
if args.seed is None:
args.seed = torch.randint(0, 2**31, (1,)).item()
generator = torch.Generator(device="cpu") # CPU generator more stable with MPS
generator.manual_seed(args.seed)
print(f"\nGenerating video...")
print(f" Prompt: {args.prompt}")
print(f" Size: {args.width}x{args.height}, {args.frames} frames")
print(f" Steps: {args.steps}, Guidance: {args.guidance}")
print(f" Seed: {args.seed}")
print()
# Generate
result = pipe(
prompt=args.prompt,
negative_prompt=args.negative_prompt if args.negative_prompt else None,
num_inference_steps=args.steps,
guidance_scale=args.guidance,
width=args.width,
height=args.height,
num_frames=args.frames,
generator=generator,
)
# Export video
video_frames = result.frames[0]
export_to_video(video_frames, args.output, fps=args.fps)
print(f"\nVideo saved to: {args.output}")
print(f"Seed: {args.seed}")
if __name__ == "__main__":
main()