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wjldragon
/
AdaOcc

PyTorch
DepthAnythingV2
occupancy-prediction
semantic-occupancy
embodied-ai
occscannet
adaocc
radio
Model card Files Files and versions
xet
Community

Instructions to use wjldragon/AdaOcc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • DepthAnythingV2

    How to use wjldragon/AdaOcc with DepthAnythingV2:

    # Install from https://github.com/DepthAnything/Depth-Anything-V2
    
    # Load the model and infer depth from an image
    import cv2
    import torch
    from huggingface_hub import hf_hub_download
    
    from depth_anything_v2.dpt import DepthAnythingV2
    
    # instantiate the model
    model = DepthAnythingV2(encoder="<ENCODER>", features=<NUMBER_OF_FEATURES>, out_channels=<OUT_CHANNELS>)
    
    # load the weights
    filepath = hf_hub_download(repo_id="wjldragon/AdaOcc", filename="depth_anything_v2_<ENCODER>.pth", repo_type="model")
    state_dict = torch.load(filepath, map_location="cpu")
    model.load_state_dict(state_dict)
    model.eval()
    
    raw_img = cv2.imread("your/image/path")
    depth = model.infer_image(raw_img) # HxW raw depth map in numpy
        
  • Notebooks
  • Google Colab
  • Kaggle

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Preview of files found in this repository
  • checkpoints
    Publish the OccScanNet full epoch-100 checkpoint 9 days ago
  • configs
    Add the matching OccScanNet full config snapshot 9 days ago
  • logs
    Add the matching OccScanNet full training log 9 days ago
  • pretrain
    Upload AdaOcc reproduction metadata and slim fusion pretrain 4 months ago
  • .gitattributes
    1.56 kB
    Track release logs with large-file storage 9 days ago
  • README.md
    6.49 kB
    Link the arXiv preprint (arXiv:2609.38864) 5 days ago
  • SHA256SUMS
    801 Bytes
    Document the OccScanNet full checkpoint release 9 days ago
  • upload_to_hf.sh
    214 Bytes
    Upload AdaOcc reproduction metadata and slim fusion pretrain 4 months ago