Instructions to use codingggasdfasf/video-animator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codingggasdfasf/video-animator with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("codingggasdfasf/video-animator", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
root commited on
Commit ·
ca00209
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Parent(s): 0be44e5
muse pose
Browse files- __pycache__/handler.cpython-310.pyc +0 -0
- handler.py +1 -1
__pycache__/handler.cpython-310.pyc
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Binary files a/__pycache__/handler.cpython-310.pyc and b/__pycache__/handler.cpython-310.pyc differ
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handler.py
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@@ -308,7 +308,7 @@ class EndpointHandler():
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command = [
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"python", "./MusePose/pose_align.py",
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"--imgfn_refer", downloaded_image_path,
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"--vidfn",
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"--output_dir", pose_output_path
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]
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result = subprocess.run(command, capture_output=True, text=True)
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command = [
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"python", "./MusePose/pose_align.py",
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"--imgfn_refer", downloaded_image_path,
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"--vidfn", downloaded_video_path,
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"--output_dir", pose_output_path
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]
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result = subprocess.run(command, capture_output=True, text=True)
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