To visualize the original dataset i.e. without classes. Launch with:
python tusimple_visualizer.py --json_file /path/to/json_file.json
To save the images with predictions
python tusimple_image_saver.py --json_file /path/to/json_file.json
This repository contains the class labels for the lane boundaries of the TuSimple lane detection dataset. You can download the dataset from TuSimple/tusimple-benchmark#3.
Each lane boundary in the dataset is annotated using 7 different classes. Lanes that cannot be uniquely identified are annotated as Unknown. A hierarchical representation of the classes is shown below. Even if the Double-dashed-continuous class has been considered during the annotation process for completeness, there are no examples in the dataset of that class. The names of the class ids are in class_mapping.txt.
First of all, download the dataset and extract it. Then, move the files inside the data folder inside the resulting folder.
mv data/* path/to/dataset/train_set
You can obtain a .json file with an additional class field with the converter.py script. Launch it with:
python converter.py --root /path/to/dataset
It is also possible to visualize the annotations with the visualizer.py script. Launch with:
python visualizer.py --root /path/to/dataset --labels labels_json_file.json
Coming soon.