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_generator.ckpt from datasolin/sam-3d-objects-mirror: direct link, hf CLI and curl.
- Browser
- Download file 4.91 GB
-
https://huggingface.co/datasolin/sam-3d-objects-mirror/resolve/main/checkpoints/slat_generator.ckpt
- Command line
-
hf download hf://datasolin/sam-3d-objects-mirror/checkpoints/slat_generator.ckpt
-
curl -L -o slat_generator.ckpt https://huggingface.co/datasolin/sam-3d-objects-mirror/resolve/main/checkpoints/slat_generator.ckpt
4.91 GB
- Xet hash:
- 30a915bea5d8f120963a441129e2ae75a0ea3dd195c5197e938c11cf262e591a
- Size of remote file:
- 4.91 GB
- SHA256:
- 91529bde8e7daa12d09618a66c319e3a5a6398db6b23b958cedcb1c3f28faabb
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