Instructions to use asdafdfafffg/sam-3d-objects with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SAM 3D Objects
How to use asdafdfafffg/sam-3d-objects with SAM 3D Objects:
from inference import Inference, load_image, load_single_mask from huggingface_hub import hf_hub_download path = hf_hub_download("asdafdfafffg/sam-3d-objects", "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_decoder.yaml from asdafdfafffg/sam-3d-objects: direct link, hf CLI and curl.
- Browser
- Download file 244 Bytes
-
https://huggingface.co/asdafdfafffg/sam-3d-objects/resolve/main/checkpoints/ss_decoder.yaml
- Command line
-
hf download hf://asdafdfafffg/sam-3d-objects/checkpoints/ss_decoder.yaml
-
curl -L -o ss_decoder.yaml https://huggingface.co/asdafdfafffg/sam-3d-objects/resolve/main/checkpoints/ss_decoder.yaml
244 Bytes
| _target_: sam3d_objects.model.backbone.tdfy_dit.models.sparse_structure_vae.SparseStructureDecoderTdfyWrapper | |
| out_channels: 1 | |
| latent_channels: 8 | |
| num_res_blocks: 2 | |
| num_res_blocks_middle: 2 | |
| channels: | |
| - 512 | |
| - 128 | |
| - 32 | |
| reshape_input_to_cube: false | |