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The 3D Lidar Object Detection and Tracking Challenge of Apolloscape Dataset

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Our 3D Lidar object detection and tracking dataset consists of LiDAR scanned point clouds with high quality annotation. It is collected under various lighting conditions and traffic densities in Beijing, China. More specifically, it contains highly complicated traffic flows mixed with vehicles, cyclists, and pedestrians.

Evaluation is the evaluation code. Run the code for a sample evaluation:

source activate apolloscape

# export CUDA_VISIBLE_DEVICES=4,5,6,7

# tracking
python --modeType=tracking --gtPath=../track/apollo_lab --dtPath=../track/apollo_res --typeFilterFlag
# detection
# python --gtPath=apollo_lab_test --dtPath=apollo_res_test --apSampleNum=10 #--typeFilterFlag #2>&1 | tee run.log

Submission of data format

Submit your result for online evaluation here: Submit



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