AlexNet-pytorch

This repo is created for imitation learning Pytorch AlexNet which was a material of AI course in NCTU.
People can use any robot with ROS to predict which is the direction to go next. (omega)

Dataset

/joy_mapper_node/car_cmd
/camera_node/image/compressed

Input = image, omega
Output = 15 classes (['R0' 'R1' 'R2' 'R3' 'R4' 'R5' 'R6' 'S7' 'L8' 'L9' 'L10' 'L11' 'L12' 'L13' 'L14'])

I. Prerequisite

1. OS: Ubuntu 16.04/18.04
2. GPU with Nvidia driver >= 384.xx (cuda10.0 or newer)
3. Docker

II. Test

$ cd AlexNet_pytorch
$ pip install -r requirements.txt
$ jupyter notebook 

1. Download_dataset.ipynb (Get the dataset)
2. Download_models.ipynb (Get the models)
3. train-pytorch.ipynb (To start training)
4. evaluation-pytorch.ipynb (To evaluate the models)

III. Evaluation

IV. Predict & Demo

Connect to ROS

# RPi3 (duckietown)
$ cd robot-lane-following
$ source start_pi.sh   #joystick and camera

# On Jetson Nano
$ cd robot-lane-following
$ source docker_run_robot.sh
container$ cd nano_ws
container$ catkin_make
container$ source devel/setup.bash
container$ vim ~/.bashrc
# modify "ROS_IP=10.42.0.2" to "ROS_IP=$(hostname -I)"
container$ source  ~/.bashrc
container$ roslaunch imitation_following pytorch_joy_mapper_node.launch veh:=[car_hostname] model:=[model_name].pth