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Download README.md from NTU-AI2Lab/RDPN: direct link, hf CLI and curl.
- Browser
- Download file 843 Bytes
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https://huggingface.co/NTU-AI2Lab/RDPN/resolve/main/README.md
- Command line
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hf download hf://NTU-AI2Lab/RDPN/README.md
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curl -L -o README.md https://huggingface.co/NTU-AI2Lab/RDPN/resolve/main/README.md
843 Bytes
| tags: | |
| - 6d-pose-estimation | |
| - pose-estimation | |
| - computer-vision | |
| - pytorch | |
| datasets: | |
| - NTU-AI2Lab/RDPN-data | |
| # RDPN | |
| Pretrained checkpoints and metadata for RDPN. Training data archives are in [NTU-AI2Lab/RDPN-data](https://huggingface.co/datasets/NTU-AI2Lab/RDPN-data). | |
| ## Contents | |
| - `checkpoints/lmso/` β per-object checkpoints for LM (13 objects) | |
| - `checkpoints/lmoso/` β per-object checkpoints for LM-O (8 objects) | |
| - `checkpoints/mp6dso/` β per-object checkpoints for MP6D (`obj_01`β`obj_20`) | |
| - `metadata/` β models, image sets, bounding boxes and test targets for `lm`, `lmo`, `MP6D` and `YCBV` | |
| ## Download | |
| ```bash | |
| hf download NTU-AI2Lab/RDPN --local-dir RDPN | |
| ``` | |
| or a single checkpoint: | |
| ```python | |
| from huggingface_hub import hf_hub_download | |
| path = hf_hub_download("NTU-AI2Lab/RDPN", "checkpoints/lmso/ape.pth") | |
| ``` | |