SPD is the successor to the DAIR-V2X-C dataset. While maintaining the overall structure, we have cleaned the dataset, annotated tracking IDs for each object, and provided vector maps.
- Refer to the SPD dataset structure.
- Check out the HD Map usage.
- For more dataset usage details, visit the DAIR-V2X documentation.
We offer early fusion, late fusion, and middle fusion benchmarks like FF-Tracking for the VIC3D Tracking task. To learn about training and evaluating these benchmarks, visit the following link:
The TFD dataset comprises trajectories, vector maps, and traffic light signals.
- Explore the TFD dataset structure.
- Learn about loading trajectories, vector maps, traffic light signals and the visualization of TFD using the TFD Tutorial.
We provide various benchmarks, including PP-VIC, for solving Online-VIC Forecasting and Offline-VIC Forecasting tasks. Find basic guidance in the TFD Benchmark README. Detailed training and evaluation of Baselines with HiVT and TNT are as follows:
- For training and evaluation of Baselines with HiVT, refer to the HiVT README.
- For training and evaluation of Baselines with TNT, refer to the TNT README.
Here's how to evaluate PP-VIC with HiVT for solving the Online-VIC Forecasting task using the TFD-Example dataset.
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Create a conda environment and install dependencies as specified in HiVT:
conda create -n HiVT python=3.8 conda activate HiVT conda install pytorch==1.8.0 cudatoolkit=11.1 -c pytorch -c conda-forge conda install pytorch-geometric==1.7.2 -c rusty1s -c conda-forge conda install pytorch-lightning==1.5.2 -c conda-forge
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Install the Argoverse 1 API.
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Dataset Preparation:
# Download TFD-Example into ./dataset/v2x-seq-tfd/V2X-Seq-TFD-Example bash tools/dataset_example_download.sh # export DATA_ROOT, change the DATA_ROOT to TFD-Example data root export DATA_ROOT=${PWD}'/dataset/v2x-seq-tfd/V2X-Seq-TFD-Example' # Merge Multiple Maps into One Map python tools/data_converter/maps_merge.py # Preprocess Cooperative-view Trajectories python tools/trajectory_fusion/fusion_for_prediction.py python tools/data_converter/tfd_argoverse_converter.py
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Evaluation:
# parsers: GPU_ID, DATA_ROOT, CKPT # DATA_ROOT=../../dataset/v2x-seq-tfd/V2X-Seq-TFD-Example cd projects/HiVT_plugin bash tools/hivt_eval.sh 0 ${DATA_ROOT}/cooperative-vehicle-infrastructure/fusion_for_prediction ./checkpoints/online.ckpt