Download the latest image from the link below according to your type of Jetson Nano and burn it into a SD card.
https://jetbot.org/master/software_setup/sd_card.html
Install dependencies
sudo apt install libffi-dev
sudo pip3 install ipywidgets
sudo pip3 install traitlets
cd ~/jetbot
sudo python3 setup.py install
You need install Pytorch in order to run jetbot module, the instrution can be refer to https://forums.developer.nvidia.com/t/pytorch-for-jetson-version-1-7-0-now-available/72048.
Download Pytorch whl file according to your jetpack version. The script listed below installs for JetPack version 4.4.1
wget https://nvidia.box.com/shared/static/9eptse6jyly1ggt9axbja2yrmj6pbarc.whl -O torch-1.7.0-cp36-cp36m-linux_aarch64.whl
sudo apt-get install python3-pip libopenblas-base libopenmpi-dev
pip3 install Cython
pip3 install numpy torch-1.7.0-cp36-cp36m-linux_aarch64.whl
Install libcanberra-gtk-module
sudo apt install libcanberra-gtk-module libcanberra-gtk3-module
Create swap, refer to the link below:
This section introduces how to prepare the environment in your jetbot.
Install gdown for downloading TensorRT model from the google drive
sudo pip3 install gdown
Clone the project of tensorrt_demos to your home directory, and then setup environment by following its instruction.
git clone https://github.com/jkjung-avt/tensorrt_demos.git
Download model and config from the google drive (For CUDA 10.0)
cd ~/tensorrt_demos/yolo
gdown 'https://drive.google.com/uc?id=1nuVzboVN6sJLrQengTObuCrTUPzVMRtU'
gdown 'https://drive.google.com/uc?id=1LfTOhGf3C3cVMrLwG1MrXrdTnrH3sZMb'
Download model and config from the google drive (For CUDA 10.2)
cd ~/tensorrt_demos/yolo
gdown 'https://drive.google.com/uc?id=1Xl5ZJ3RNb2H-D3wx4ZyXnlbFYFXaJ2Aw'
gdown 'https://drive.google.com/uc?id=1LfTOhGf3C3cVMrLwG1MrXrdTnrH3sZMb'
Copy 'main.py' in this project to ~/tensorrt_demos
cp main.py ~/tensorrt_demos
Finally, you can run main.py now.
cd ~/tensorrt_demos
python3 main.py