Open traffic cam (with YOLO)

This project is offline lightweight DIY solution to monitor urban landscape. After installing this software on the specified hardware (Nvidia Jetson board + Logitech webcam), you will be able to count cars, pedestrians, motorbikes from your webcam live stream.

Behind the scenes, it feeds the webcam stream to a neural network (YOLO darknet) and make sense of the generated detections.

It is very alpha and we do not provide any guarantee that this will work for your use case, but we conceived it as a starting point from where you can build-on & improve.

💻 Hardware pre-requise

• Nvidia Jetson TX2
• Webcam Logitech C222 (or any usb webcam compatible with Ubuntu 16.04)
• A smartphone / tablet / laptop that you will use to operate the system

⚙ System overview

See technical architecture for a more detailed overview

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🛠 Step by Step install guide

NOTE: lots of those steps needs to be automated by integrating them in a docker image or something similar, for now need to follow the full procedure

⚡️Flash Jetson Board:

• Download JetPack to Flash your Jetson board with the linux base image and needed dependencies
• Follow the install guide provided by NVIDIA

🛩Prepare Jetson Board

• Update packages

  sudo apt-get update

• Install cURL

  sudo apt-get install curl

• install git-core

  sudo apt-get install git-core

• Install nodejs (v8):

  curl -sL https://deb.nodesource.com/setup_8.x | sudo -E bash -
  sudo apt-get install -y nodejs
  sudo apt-get install -y build-essential

• Install ffmpeg (v3)

  sudo add-apt-repository ppa:jonathonf/ffmpeg-3
  # sudo add-apt-repository ppa:jonathonf/tesseract (ubuntu 14.04 only!!)
  sudo apt update && sudo apt upgrade
  sudo apt-get install ffmpeg

• Optional: Install nano

  sudo apt-get install nano

📡Configure Ubuntu to turn the jetson into a wifi access point

• enable SSID broadcast

  add the following line to /etc/modprobe.d/bcmdhd.conf

  options bcmdhd op_mode=2

  further infos: here

• Configure hotspot via UI

  follow this guide: https://askubuntu.com/a/762885

• Define Address range for the hotspot network

  • Go to the file named after your Hotspot SSID in /etc/NetworkManager/system-connections

    cd /etc/NetworkManager/system-connections
    sudo nano <YOUR-HOTSPOT-SSID-NAME>

  • Add the following line to this file:

    [ipv4]
    dns-search=
    method=shared
    address1=192.168.2.1/24,192.168.2.1 <--- this line
    

  • Restart the network-manager

    sudo service network-manager restart

🚀Configure jetson to start in overclocking mode:

• Add the following line to /etc/rc.local before exit 0:

  #Maximize performances 
  ( sleep 60 && /home/ubuntu/jetson_clocks.sh )&

• Enable rc.local.service

  chmod 755 /etc/init.d/rc.local
  sudo systemctl enable rc-local.service

👁Install Darknet-net:

IMPORTANT Make sure that openCV (v2) and CUDA will be installed via JetPack (post installation step) if not: (fallback :openCV 2: install script, CUDA: no easy way yet)

• Install libwsclient:

  git clone https://github.com/PTS93/libwsclient
  cd libwsclient
  ./autogen.sh
  ./configure && make && sudo make install

• Install liblo:

  wget https://github.com/radarsat1/liblo/releases/download/0.29/liblo-0.29.tar.gz
  tar xvfz liblo-0.29.tar.gz
  cd liblo-0.29
  ./configure && make && sudo make install

• Install json-c:

  git clone https://github.com/json-c/json-c.git
  cd json-c
  sh autogen.sh
  ./configure && make && make check && sudo make install

• Install darknet-net:

  git clone https://github.com/meso-unimpressed/darknet-net.git

• Download weight files:

  link: yolo.weight-files

  Copy yolo-voc.weights to darknet-net repository path (root level)

  e.g.:

  darknet-net
    |-cfg
    |-data
    |-examples
    |-include
    |-python
    |-scripts
    |-src
    |# ... other files
    |yolo-voc.weights <--- Weight file should be in the root directory
  

• Make darknet-net

  cd darknet-net
  make

🎥Install the open-data-cam node app

• Install pm2 and next globally

  sudo npm i -g pm2
  sudo npm i -g next

• Clone open_data_cam repo:

  git clone https://github.com/moovel/lab-open-data-cam.git

• Specify ABSOLUTE PATH_TO_YOLO_DARKNET path in lab-open-data-cam/config.json (open data cam repo)

  e.g.:

  {
  	"PATH_TO_YOLO_DARKNET" : "/home/nvidia/darknet-net"
  }

• Install open data cam

  cd <path/to/open-data-cam>
  npm install
  npm run build

• Run open data cam on boot

  cd <path/to/open-data-cam>
  # launch pm2 at startup
  # this command gives you instructions to configure pm2 to 
  # start at ubuntu startup, follow them
  sudo pm2 startup  
  
  # Once pm2 is configured to start at startup
  # Configure pm2 to start the Open Traffic Cam app
  sudo pm2 start npm --name "open-data-cam" -- start
  sudo pm2 save

🏁 Restart the jetson board and open http://IP-OF-THE-JETSON-BOARD:8080/

Connect you device to the jetson

💡 We should maybe set up a "captive portal" to avoid people needing to enter the ip of the jetson, didn't try yet 💡

When the jetson is started you should have a wifi "YOUR-HOTSPOT-NAME" available.

• Connect you device to the jetson wifi
• Open you browser and open http://IPOFTHEJETSON:8080
• In our case, IPOFJETSON is: http://192.168.2.1:8080

You are done 👌

🚨 This alpha version of december is really alpha and you might need to restart ubuntu a lot as it doesn't clean up process well when you switch between the counting and the webcam view 🚨

You should be able to monitor the jetson from the UI we've build and count 🚗 🏍 🚚 !

‼️Automatic installation (alpha)

The install script for autmatic installation

Setting up the access point is not automated yet! __follow this guide: https://askubuntu.com/a/762885 __ to set up the hotspot.

• run the install.sh script

  sudo chmod +x install.sh
  ./install.sh
  sudo reboot

Troubleshoothing

To debug the app log onto the jetson board and inspect the logs from pm2 or stop the pm2 service (sudo pm2 stop <pid>) and start the app by using sudo npm start to see the console output directly.

• Error: please specify the path to the raw detections file

  Make sure that ffmpeg is installed and is above version 2.8.11

• Error: Could *not* find a valid build in the '.next' directory! Try building your app with '*next* build' before starting the server

  Run npm build before starting the app

• Could not find darknet. Be sure to make darknet without sudo otherwise it will abort mid installation.

• Error: cannot open shared object file: No such file or directory

  Try reinstalling the liblo package.

• Error: Error: Cannot stop process that is not running.

  It is possible that a process with the port 8090 is causing the error. Try to kill the process and restart the board:

  sudo netstat -nlp | grep :8090
  sudo kill <pid>

🛠 Development notes

Technical architecture

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Miscellaneous dev tips

Mount jetson filesystem as local filesystem on mac for dev

sshfs -o allow_other,defer_permissions nvidia@192.168.1.222:/home/nvidia/Desktop/lab-traffic-cam /Users/tdurand/Documents/ProjetFreelance/Moovel/remote-lab-traffic-cam/

SSH jetson

ssh nvidia@192.168.1.222

Install it and run:

yarn install
yarn run dev