SolitaryThinker
e54106110e
The activation switch. After this PR merges, MagiHuman is publicly
loadable via:
from fastvideo import VideoGenerator
gen = VideoGenerator.from_pretrained('FastVideo/MagiHuman-Diffusers/base')
Files:
- fastvideo/registry.py: 153 lines of register_configs/register_presets
calls covering all 4 variants x 2 modes (8 total entrypoints).
- examples/inference/basic/basic_magi_human{_,_ti2v,_distill,_distill_ti2v,
_sr540p,_sr540p_ti2v,_sr1080p,_sr1080p_ti2v}.py: 8 user-facing scripts.
- fastvideo/tests/ssim/test_magi_human_similarity.py: CI-eligible SSIM
regression test against the umbrella HF repo.
- .agents/memory/codebase-map/models/magi_human.md: codebase-map entry
(first per-model entry under the models/ subdir; sets the convention).
- fastvideo/pipelines/basic/magi_human/AGENTS.md: provenance section
finalized with all 8 PR numbers + the will/magi source SHA.
Verification:
- Existing tests on main: should still pass (no shared component changes
in this PR; the umbrella loader infra landed in PR-B / loader-infra).
- pre-commit run --all-files: clean.
- E2E smoke after activation: any of the 8 examples emits expected mp4
with hash dcf5f2bf6534c7c0d91e7353e42b23db on the base T2V variant.
Magi-Stack: 8/8
52 lines
1.8 KiB
Python
52 lines
1.8 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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"""Minimal user-runnable example for the daVinci-MagiHuman base AV pipeline.
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Produces an mp4 with both video (Wan 2.2 TI2V-5B VAE) and audio (Stable
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Audio Open 1.0 VAE, first-class FastVideo port in
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`fastvideo/models/vaes/oobleck.py`) muxed together via PyAV.
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Prerequisites (one-off):
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# Accept terms of use on the gated HF repos with your HF_TOKEN:
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# - https://huggingface.co/google/t5gemma-9b-9b-ul2
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# - https://huggingface.co/stabilityai/stable-audio-open-1.0
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# All four cross-variant shared components (Wan 2.2 VAE, T5-Gemma
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# encoder + tokenizer, Stable Audio VAE) are lazy-loaded from their
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# canonical upstream HF repos on first build, so a single ~25 GB
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# cache is shared across every MagiHuman variant.
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The umbrella HF repo `FastVideo/MagiHuman-Diffusers` holds all four
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variants (base / distill / sr_540p / sr_1080p) under sibling subfolders
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and FastVideo will download just the requested subfolder. Local
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conversion via `scripts/checkpoint_conversion/convert_magi_human_to_diffusers.py`
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is also supported.
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"""
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from fastvideo import VideoGenerator
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PROMPT = (
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"A warm afternoon scene: a person sits on a park bench reading a book, "
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"surrounded by softly swaying trees."
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)
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def main() -> None:
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generator = VideoGenerator.from_pretrained(
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"FastVideo/MagiHuman-Diffusers/base",
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num_gpus=1,
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)
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output_path = "outputs_video/magi_human_basic/output_magi_human.mp4"
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generator.generate_video(
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prompt=PROMPT,
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output_path=output_path,
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save_video=True,
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# Defaults pulled from the registered preset (magi_human_base):
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# height=256, width=448, fps=25, num_inference_steps=32, seed=42.
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# Override here only if you have a specific QA scenario.
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)
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generator.shutdown()
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if __name__ == "__main__":
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main()
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