lane-seg

Experimenting with lane segmentation. The first implementation is with vanilla UNET on the following dataset https://www.kaggle.com/thomasfermi/lane-detection-for-carla-driving-simulator.

The dataset is simple dataset from carla simulator.

Training

Parameters that can be sent during training:
Learning Rate, --lr
Number of epochs, --epochs
Batch size, --batch_size
Resume training, --resume
Number of workers, --num_workers
Dataset path, --dataset_path

Example:
python train.py --dataset_path data/ --lr 0.001 --batch_size 16

Evaluation on a single image

python eval.py --image_path /path/to/image.png

To-do

1. Add accuracy into training
2. Improve tensorboard output: include more information, add images
3. Add more information for saving checkpoints
4. Add evaluation for the whole folder instead of image per image
5. Extrapolate lines
6. Mark driving lane
7. Play around with augmentations, and generate bigger dataset

Future work

1. Explore better solutions for this problem, like LaneNet
2. Explore other datasets