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Preparation

  1. Please see dataset/README.md to get more details about our datasets-VIL100

  2. Please see INSTALL.md to install environment and evaluation tools

  3. Before training, we should download datasets-VIL100 and models

    (Google Drive) : https://drive.google.com/drive/folders/178_SSeQ4M1hI3BrTonhiTrpOWTEAenLE

  4. Put them under this structure

      MMA-Net
           |----INSTALL.md
           |----README.md
           |----dataset
           |------|-----VIL100
           |----models
           |----evaluation
           |----options.py
           |----libs
           |----requirements.txt
           |----train.py
           |----test.py
    

Training and Testing

  1. To train the MMA network, run following command

    python3 train.py --gpu ${GPU-IDS}
  2. To test the MMA network, run following command

    python3 test.py

    The test results will be saved as indexed png file at ${root}/${output}/${valset}.

    Additionally, you can modify some setting parameters in options.py to change training configuration.

Evaluation

  1. generate accuracy, fp, fp

    python evaluate_acc.py      # Please modify `pre_dir_name` and `json_dir_name` in evaluate_acc.py
    
  2. Install CULane evaluation tools, please see INSTALL.md

  3. generate F, mIoUevaluate_acc after the CULane evaluation tools are installed

    1. all pred txt files will be generated under MMA-Net/evaluation/txt/pred_txt after this step

      python generate_iou_pred_txt.py      # Please modify `pre_dir_name` and `json_path` in  `generate_iou_pred_txt.py`
      
    2. results_MMA and temp_MMA will be generated under MMA-Net/evaluation/txt/results_txt after this step.

      results_MMA: evaluation results of each sequence

      temp_MMA: temporary files generated during evaluation, you can ignore them

      python evaluate_iou.py      # `data_root` should be set as your VIL-100 dataset path in `evaluate_iou.py`
      
    3. Attention!! if you want to evaluation results one more time, please delete all folders/files under MMA-Net/evaluation/txt/results_txt .

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VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection (ICCV 2021)

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