- Download project dataset and unzip it
- Update ToKITTITrain.py and ToKITTITest.py so data_dir is set to the directory where the project dataset was unzipped to
- Run "python ToKITTITest.py"
- Update exps/config.yaml so DATA/ROOT is set to the path with the KITTI data
- Run "python test.py --config_file exps/config.yaml --checkpoint_file /exps/checkpoints/{CHECKPOINT_FILE} --evaluate"
- Run "python merger.py --folder_path output/ --save_path {DIRECTORY TO SAVE PREDICTIONS TO}"
- 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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- Python 100.0%