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This repository provides setup instructions and utilities for preparing and processing datasets used in SAM-3D-Body, including downloading annotations and creating WebDataset archives.

⚠️ Please note that you need to request access on the SAM 3D Body Hugging Face repo. Once accepted, you need to be authenticated to download the checkpoints.

⚠️ SAM 3D Body data is available via HuggingFace globally, except in comprehensively sanctioned jurisdictions. Sanctioned jurisdiction will result in requests being rejected.

🧩 Environment Setup

Create and configure the conda environment for dataset preparation:

conda create --name sam_3d_body_data python=3.9 -y
conda activate sam_3d_body_data
conda install pytorch=2.4.0 torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia -y
pip install hdbscan pyntcloud==0.3.1 pykalman torchgeometry colour==0.1.5 flask==3.1.1 trimesh==4.7.3
pip install pandas==2.0.3 numpy==1.26 pycolmap==0.3.0 yacs==0.1.8 projectaria-tools==1.3.3 opencv-python==4.7.0.72
pip install datasets huggingface_hub webdataset pycocotools

📂 Image Preparation

Prepare dataset images required for SAM-3D-Body by following the individual setup guides linked below:

Each dataset guide describes how to download, extract, and structure the raw data for WebDataset creation.

⚙️ Environment Variables

Set up environment variables for annotation download and WebDataset output directories:

  export SAM3D_BODY_ANN_DIR=/path/to/sam3d/body/annotations
  export SAM3D_BODY_WDS_DIR=/path/to/sam3d/body/webdatasets

⬇️ Download Annotations

You can download all annotation splits or only a specific split from SAM-3D-Body.

Download all splits

  python scripts/download.py \
    --save_dir $SAM3D_BODY_ANN_DIR

Download a specific split

Replace DATA_SPLIT with the desired split name (e.g., coco_train, sa1b_train, harmony4d_test, etc.):

  python scripts/download.py \
    --save_dir $SAM3D_BODY_ANN_DIR \
    --splits DATA_SPLIT

🗜️ Create WebDatasets

Convert a dataset split into WebDataset format for efficient distributed training and evaluation.

python scripts/create_webdataset.py \                              
    --annotation_dir $SAM3D_BODY_ANN_DIR/DATA_SPLIT \
    --webdataset_dir $SAM3D_BODY_WDS_DIR/DATA_SPLIT \
    --image_dir DATASET_IMG_DIR

where

  • --annotation_dir: Path to the annotation directory for the target split (e.g., $SAM3D_BODY_ANN_DIR/coco_train).
  • --webdataset_dir: Output directory for the generated WebDataset files (e.g., $SAM3D_BODY_WDS_DIR/coco_train).
  • --image_dir: Path to the corresponding image directory for the dataset (e.g., $COCO_IMG_DIR).
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