74 lines
2.5 KiB
Markdown
74 lines
2.5 KiB
Markdown
|
|
# Install
|
|
|
|
1. Clone the RESA repository
|
|
```
|
|
git clone https://github.com/zjulearning/resa.git
|
|
```
|
|
We call this directory as `$RESA_ROOT`
|
|
|
|
2. Create a conda virtual environment and activate it (conda is optional)
|
|
|
|
```Shell
|
|
conda create -n resa python=3.8 -y
|
|
conda activate resa
|
|
```
|
|
|
|
3. Install dependencies
|
|
|
|
```Shell
|
|
# Install pytorch firstly, the cudatoolkit version should be same in your system. (you can also use pip to install pytorch and torchvision)
|
|
conda install pytorch torchvision cudatoolkit=10.1 -c pytorch
|
|
|
|
# Or you can install via pip
|
|
pip install torch torchvision
|
|
|
|
# Install python packages
|
|
pip install -r requirements.txt
|
|
```
|
|
|
|
4. Data preparation
|
|
|
|
Download [CULane](https://xingangpan.github.io/projects/CULane.html) and [Tusimple](https://github.com/TuSimple/tusimple-benchmark/issues/3). Then extract them to `$CULANEROOT` and `$TUSIMPLEROOT`. Create link to `data` directory.
|
|
|
|
```Shell
|
|
cd $RESA_ROOT
|
|
ln -s $CULANEROOT data/CULane
|
|
ln -s $TUSIMPLEROOT data/tusimple
|
|
```
|
|
|
|
For Tusimple, the segmentation annotation is not provided, hence we need to generate segmentation from the json annotation.
|
|
|
|
```Shell
|
|
python scripts/convert_tusimple.py --root $TUSIMPLEROOT
|
|
# this will generate segmentations and two list files: train_gt.txt and test.txt
|
|
```
|
|
|
|
For CULane, you should have structure like this:
|
|
```
|
|
$RESA_ROOT/data/CULane/driver_xx_xxframe # data folders x6
|
|
$RESA_ROOT/data/CULane/laneseg_label_w16 # lane segmentation labels
|
|
$RESA_ROOT/data/CULane/list # data lists
|
|
```
|
|
|
|
For Tusimple, you should have structure like this:
|
|
```
|
|
$RESA_ROOT/data/tusimple/clips # data folders
|
|
$RESA_ROOT/data/tusimple/lable_data_xxxx.json # label json file x4
|
|
$RESA_ROOT/data/tusimple/test_tasks_0627.json # test tasks json file
|
|
$RESA_ROOT/data/tusimple/test_label.json # test label json file
|
|
```
|
|
|
|
5. Install CULane evaluation tools.
|
|
|
|
This tools requires OpenCV C++. Please follow [here](https://docs.opencv.org/master/d7/d9f/tutorial_linux_install.html) to install OpenCV C++. Or just install opencv with command `sudo apt-get install libopencv-dev`
|
|
|
|
|
|
Then compile the evaluation tool of CULane.
|
|
```Shell
|
|
cd $RESA_ROOT/runner/evaluator/culane/lane_evaluation
|
|
make
|
|
cd -
|
|
```
|
|
|
|
Note that, the default `opencv` version is 3. If you use opencv2, please modify the `OPENCV_VERSION := 3` to `OPENCV_VERSION := 2` in the `Makefile`. |