Instructions to use datasolin/sam-3d-objects-mirror with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SAM 3D Objects
How to use datasolin/sam-3d-objects-mirror with SAM 3D Objects:
from inference import Inference, load_image, load_single_mask from huggingface_hub import hf_hub_download path = hf_hub_download("datasolin/sam-3d-objects-mirror", "pipeline.yaml") inference = Inference(path, compile=False) image = load_image("path_to_image.png") mask = load_single_mask("path_to_mask.png", index=14) output = inference(image, mask) - Notebooks
- Google Colab
- Kaggle
Download checkpoints/slat_decoder_mesh.ckpt from datasolin/sam-3d-objects-mirror: direct link, hf CLI and curl.
- Browser
- Download file 364 MB
-
https://huggingface.co/datasolin/sam-3d-objects-mirror/resolve/main/checkpoints/slat_decoder_mesh.ckpt
- Command line
-
hf download hf://datasolin/sam-3d-objects-mirror/checkpoints/slat_decoder_mesh.ckpt
-
curl -L -o slat_decoder_mesh.ckpt https://huggingface.co/datasolin/sam-3d-objects-mirror/resolve/main/checkpoints/slat_decoder_mesh.ckpt
364 MB
- Xet hash:
- f12af4a9e8d437a9d5dca0696dc7faff7d91b2be02faa7cfd82d5e9dc4c3e814
- Size of remote file:
- 364 MB
- SHA256:
- 85907b37b67d8ce5b099a96629bdcfbd873eb407dee6b3aa9a75deb15038db33
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