Preparation
Please see dataset/README.md to get more details about our datasets-VIL100
Please see INSTALL.md to install environment and evaluation tools
Before training, we should download datasets-VIL100 and models
datasets : https://pan.baidu.com/s/1NkP_5LMLTn6qsu9pSbyi0g - iy16
models : https://pan.baidu.com/s/1_o13TBbTf258-j7iACDS2Q - sgh2
- The first training stage loads the model: initial_STM
- The second training stage loads the model: resume STM and resume ATT
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
To train the MMA network, run following command
python3 train.py --gpu ${GPU-IDS}
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
generate accuracy
, fp
, fp
python evaluate_acc.py # Please modify `pre_dir_name` and `json_dir_name` in evaluate_acc.py
Install CULane evaluation tools
, please see INSTALL.md
generate F
, mIoU
evaluate_acc after the CULane evaluation tools are installed
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`
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`
Attention!! if you want to evaluation results one more time, please delete all folders/files under MMA-Net/evaluation/txt/results_txt
.