SARosPerceptionKitti

ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark

Demo

Setup

Sticking to this folder structure is highly recommended:

    ~                                        # Home directory
    ├── catkin_ws                            # Catkin workspace
    │   ├── src                              # Source folder
    │       └── SARosPerceptionKitti         # Repo
    ├── kitti_data                           # Dataset
    │   ├── 0012                             # Demo scenario 0012
    │   │   └── synchronized_data.bag        # Synchronized ROSbag file

Install ROS and create a catkin workspace in your home directory:

mkdir -p ~/catkin_ws/src

Clone this repository into the catkin workspace's source folder (src) and build it:

cd ~/catkin_ws/src
git clone https://github.com/appinho/SARosPerceptionKitti.git
cd ~/catkin_ws
catkin_make
source devel/setup.bash

Download a preprocessed scenario and unzip it into a separate kitti_data directory, also stored under your home directory:

mkdir ~/kitti_data && cd ~/kitti_data/
mv ~/Downloads/0012.zip .
unzip 0012.zip
rm 0012.zip

Usage

Launch one of the following ROS nodes to perform and visualize the pipeline (Sensor Processing -> Object Detection -> Object Tracking) step-by-step:

source devel/setup.bash
roslaunch sensor_processing sensor_processing.launch home_dir:=/home/YOUR_USERNAME
roslaunch detection detection.launch home_dir:=/home/YOUR_USERNAME
roslaunch tracking tracking.launch home_dir:=/home/YOUR_USERNAME

Default parameters:
- scenario:=0012
- speed:=0.2
- delay:=3

Without assigning any of the abovementioned parameters the demo scenario 0012 is replayed at 20% of its speed with a 3 second delay so RViz has enough time to boot up.

Write the results to file and evaluate them:

roslaunch evaluation evaluation.launch home_dir:=/home/YOUR_USERNAME
cd ~/catkin_ws/src/SARosPerceptionKitti/benchmark/python
python evaluate_tracking.py

Results for demo scenario 0012

Class	MOTA	MOTP	MOTAL	MODA	MODP
Car	0.881119	0.633595	0.881119	0.881119	0.642273
Pedestrian	0.546875	0.677919	0.546875	0.546875	0.836921

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