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Implementation of MonoCon for 3D Car Detection in KITTI Format. ROB535 Self-driving Car Final Project.

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Instructions to generate predictions

  1. Download project dataset and unzip it
  2. Update ToKITTITrain.py and ToKITTITest.py so data_dir is set to the directory where the project dataset was unzipped to
  3. Run "python ToKITTITest.py"
  4. Update exps/config.yaml so DATA/ROOT is set to the path with the KITTI data
  5. Run "python test.py --config_file exps/config.yaml --checkpoint_file /exps/checkpoints/{CHECKPOINT_FILE} --evaluate"
  6. Run "python merger.py --folder_path output/ --save_path {DIRECTORY TO SAVE PREDICTIONS TO}"
  7. The generated file has all of the predictions for the test set. All predictions after frame 499 are for the extra credit test set.

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Implementation of MonoCon for 3D Car Detection in KITTI Format. ROB535 Self-driving Car Final Project.

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