Real Time Road Space Rationing control using Jetson Nano

Acknowledge : MDP consulting S.A.C -INNOVATION DEPARTMENT

AI at the Edge Challenge https://www.hackster.io/cristian-lazo-quispe/real-time-road-space-rationing-control-using-jetson-nano-89c2da

Perú’s government implemented an alternate-day travel restriction based on the license plate last-digit. Our solution look to automate this.

GETTING STARTED

Using ISO

Download ISO pico_placa.gz: https://drive.google.com/drive/folders/1_XjzvR0key_jjU8aexq3Zpe6h2fgbZnz?usp=sharing
Flash SD CARD with Etcher:

Open folder Pico_placa_SSD :

  cd home/dlinano/Documents/Pico_placa_SSD

Run code pico_placa.py
```
  python3 pico_placa.py
```

If you want to use special hardware of image capture:

webcam :
```
  self.video = cv2.VideoCapture(0)
```

video :

  self.video = cv2.VideoCapture('PATH_OF_VIDEO')

picam :

  self.video = cv2.VideoCapture(gstreamer_pipeline(flip_method=0),cv2.CAP_GSTREAMER)

Step by step

Download this repository:

  git clone https://github.com/CristianLazoQuispe/Pico_y_placa.git

Follow the instructions of installation on pdf:
```
  Pico_y_placa.pdf
```

SSD MobileNet This project use the model od SSD MobileNet on TensorRT We use the model of the repository tensorrt_demos:

  git clone https://github.com/jkjung-avt/tensorrt_demos.git
  
  Download and implement the TensorRT model from SSD Mobilenet and copy it to the ssd folder

OpenALPR Download the repository and copy the runtime_data folder to Pico_y_placa:
```
  git clone https://github.com/openalpr/openalpr.git
```
Run code pico_placa.py
```
  python3 pico_placa.py
```

You can see our results in the following link