This project is to create a small Android app that allows to recognize the license plate of a car quickly and easily with the camera of a smartphone or tablet and translate the license into plain text. The app marks the recognized license plate within the camera image with a bounding box and displays the determined license in plain text as annotation above the bounding box, as can be seen in the following example:
For training the models of this project it is strongly recommended to use a computer with GPU support!
First create and change to a project directory and clone the project using the following command:
https://github.com/aboerzel/German_License_Plate_Recognition.git
This will download the repo to the current project directory.
For this project we need 2 development environments, a Tensorflow 1.13 environment for license plate detection with the Tensorflow Object Detection API, and a Tensorflow 2.0 environment for license recognition.
Important: The Tensorflow Object Detection API is currently not compatible with Tensorflow 2.0!
Change to the tf_object_detection folder and create a Tensorflow 1.13 environment tf1.13 for the Tensorflow Object Detction API and activate it
cd ./tf_object_detection
conda env create -f tf1.13.yml
activate tf1.13
Compile Protobufs
for /f %i in ('dir /b object_detection\protos\*.proto') do protoc object_detection\protos\%i --python_out=.
Install the object_detection python package
python Setup.py build
python Setup.py install
Install COCO API
pip install git+https://github.com/philferriere/cocoapi.git#egg=pycocotools^&subdirectory=PythonAPI
Deactivate the current environment, change back to the project root folder and create a Tensorflow 2.0 environment tf2.0
deactivate
cd ..
conda env create -f tf2.0.yml
Download and install Android Studio
Here you can find the project proposal and the write-up of the final project:
- The project proposal
- The final project report
To train the plate detection model activate the tf1.13 environment and run the following notebooks from the project root folder:
To train the license recognition model activate the tf2.0 environment and run the following notebooks from the project root folder:
The following notebook demonstrates the complete workflow by first extracting the license plate from the camera image using the Plate Detector and then determining the license text using the License Recognizer:
The Android App (APK file) can be downloaded from here.