Files
hao-ai-lab-FastVideo/examples/inference/basic/basic_zimage.py
T

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3.5 KiB
Python

# SPDX-License-Identifier: Apache-2.0
"""Run Z-Image-Turbo text-to-image generation through FastVideo.
User story:
"I want the official Z-Image-Turbo defaults and a deterministic PNG from
a local or Hugging Face checkpoint."
"""
import argparse
from pathlib import Path
from fastvideo import VideoGenerator
from fastvideo.api import (
EngineConfig,
GenerationRequest,
GeneratorConfig,
OutputConfig,
ParallelismConfig,
PipelineSelection,
SamplingConfig,
)
DEFAULT_PROMPT = (
"Young Chinese woman in red Hanfu, intricate embroidery. Impeccable makeup, red floral forehead pattern. "
"Elaborate high bun, golden phoenix headdress, red flowers, beads. Holds round folding fan with lady, trees, bird. "
"Neon lightning-bolt lamp (⚡️), bright yellow glow, above extended left palm. Soft-lit outdoor night background, "
"silhouetted tiered pagoda (西安大雁塔), blurred colorful distant lights."
)
DEFAULT_REVISION = "f332072aa78be7aecdf3ee76d5c247082da564a6"
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Run Z-Image-Turbo text-to-image generation.")
parser.add_argument("--model-path", default="Tongyi-MAI/Z-Image-Turbo")
parser.add_argument("--revision", default=DEFAULT_REVISION)
parser.add_argument("--output", default="outputs/zimage/zimage_turbo.png")
parser.add_argument("--prompt", default=DEFAULT_PROMPT)
parser.add_argument("--negative-prompt", default="")
parser.add_argument("--height", type=int, default=1024)
parser.add_argument("--width", type=int, default=1024)
parser.add_argument("--steps", type=int, default=8)
parser.add_argument("--guidance-scale", type=float, default=0.0)
parser.add_argument("--max-sequence-length", type=int, default=512)
parser.add_argument("--cfg-normalization", action=argparse.BooleanOptionalAction, default=False)
parser.add_argument("--cfg-truncation", type=float, default=1.0)
parser.add_argument("--seed", type=int, default=42)
return parser.parse_args()
def main() -> None:
args = parse_args()
output = Path(args.output)
output.parent.mkdir(parents=True, exist_ok=True)
generator = VideoGenerator.from_config(
GeneratorConfig(
model_path=args.model_path,
revision=args.revision,
engine=EngineConfig(
num_gpus=1,
parallelism=ParallelismConfig(tp_size=1, sp_size=1),
use_fsdp_inference=False,
),
# The model registry selects the native zimage_turbo preset.
pipeline=PipelineSelection(workload_type="t2i"),
))
try:
generator.generate(
GenerationRequest(
prompt=args.prompt,
negative_prompt=args.negative_prompt,
sampling=SamplingConfig(
height=args.height,
width=args.width,
num_frames=1,
fps=1,
num_inference_steps=args.steps,
guidance_scale=args.guidance_scale,
max_sequence_length=args.max_sequence_length,
cfg_normalization=args.cfg_normalization,
cfg_truncation=args.cfg_truncation,
seed=args.seed,
),
output=OutputConfig(
output_path=str(output),
save_video=True,
return_frames=False,
),
))
finally:
generator.shutdown()
if __name__ == "__main__":
main()