78 lines
2.2 KiB
Python
78 lines
2.2 KiB
Python
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from __future__ import annotations
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from pathlib import Path
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import shutil
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from model.Animation.animation_loader import (
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build_animation_predictor,
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UnifiedAnimationConfig,
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AnimationBackend,
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)
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# -----------------------------
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# 配置区（按需修改）
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# -----------------------------
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OUTPUT_DIR = "outputs/test_animation"
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ANIMATION_BACKEND = AnimationBackend.ANIMATEDIFF
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OUTPUT_FORMAT = "png_sequence" # "gif" | "png_sequence"
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PROMPT = "a cinematic mountain landscape, camera slowly pans left"
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NEGATIVE_PROMPT = "blurry, low quality"
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NUM_INFERENCE_STEPS = 25
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GUIDANCE_SCALE = 8.0
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WIDTH = 512
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HEIGHT = 512
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VIDEO_LENGTH = 16
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SEED = -1
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CONTROL_IMAGE_PATH = "path/to/your_image.png"
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def main() -> None:
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base_dir = Path(__file__).resolve().parent
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out_dir = base_dir / OUTPUT_DIR
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out_dir.mkdir(parents=True, exist_ok=True)
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predictor, used_backend = build_animation_predictor(
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UnifiedAnimationConfig(backend=ANIMATION_BACKEND)
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)
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if CONTROL_IMAGE_PATH.strip() in {"", "path/to/your_image.png"}:
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raise ValueError("请先设置 CONTROL_IMAGE_PATH 为你的输入图片路径（png/jpg）。")
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control_image = (base_dir / CONTROL_IMAGE_PATH).resolve()
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if not control_image.is_file():
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raise FileNotFoundError(f"control image not found: {control_image}")
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result_path = predictor(
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prompt=PROMPT,
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negative_prompt=NEGATIVE_PROMPT,
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num_inference_steps=NUM_INFERENCE_STEPS,
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guidance_scale=GUIDANCE_SCALE,
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width=WIDTH,
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height=HEIGHT,
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video_length=VIDEO_LENGTH,
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seed=SEED,
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control_image_path=str(control_image),
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output_format=OUTPUT_FORMAT,
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)
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source = Path(result_path)
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if OUTPUT_FORMAT == "png_sequence":
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out_seq_dir = out_dir / f"{used_backend.value}_frames"
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if out_seq_dir.exists():
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shutil.rmtree(out_seq_dir)
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shutil.copytree(source, out_seq_dir)
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print(f"[Animation] backend={used_backend.value}, saved={out_seq_dir}")
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return
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out_path = out_dir / f"{used_backend.value}.gif"
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out_path.write_bytes(source.read_bytes())
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print(f"[Animation] backend={used_backend.value}, saved={out_path}")
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if __name__ == "__main__":
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main()
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