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/ss_generator.ckpt from datasolin/sam-3d-objects-mirror: direct link, hf CLI and curl.
- Browser
- Download file 6.69 GB
-
https://huggingface.co/datasolin/sam-3d-objects-mirror/resolve/main/checkpoints/ss_generator.ckpt
- Command line
-
hf download hf://datasolin/sam-3d-objects-mirror/checkpoints/ss_generator.ckpt
-
curl -L -o ss_generator.ckpt https://huggingface.co/datasolin/sam-3d-objects-mirror/resolve/main/checkpoints/ss_generator.ckpt
6.69 GB
- Xet hash:
- 837797eccea7e5391b0394cd077a7d3df0b429638132dbb042314fd881d21bfa
- Size of remote file:
- 6.69 GB
- SHA256:
- 225f40479e4cff4f39d6fa14c55be3abad1475bf55b61af3bec1e19ed2f6c146
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