License plate parsing using Darknet and YOLO

Last update: Dec 9, 2022

Overview

DarkPlate

Note that DarkPlate by itself is not a complete software project. The intended purpose was to create a simple project showing how to use Darknet/YOLO, DarkHelp, and OpenCV to find license plates, parse them, and display the results.

Dependencies

The 3 dependencies are:

OpenCV (image processing library)
Darknet (neural network framework for YOLO)
DarkHelp (C++ API wrapper for Darknet)

Installing these is explained on the DarkHelp repo: https://github.com/stephanecharette/DarkHelp#building-darknet

Build and run

Once the dependencies have been installed, run the following commands to build and run DarkPlate on Ubuntu:

mkdir -p ~/src
cd ~/src
git clone https://github.com/stephanecharette/DarkPlate
cd DarkPlate
mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release ..
make
src/DarkPlate ../media/m1.mp4

Comments

Multiple video source

Good day! Thank you very much for the tool, it is very useful and necessary! How can I run multiple video sources?

Or at least how can you run the code with the rtsp camera?

P.S Please make a donation button on the channel so that we can support you! Thanks again)

opened by MichaelBryce90 7
Make error

Hi Stephan,

Love the youtube videos and the projects you have created. I am new and working on a hobby project of mine. I installed all the pre requirements of DarkPlate but when I run sudo make I get the following: cosme@yolo:~/src/darkplate/build$ sudo make Consolidate compiler generated dependencies of target DarkPlate [ 50%] Building CXX object src/CMakeFiles/DarkPlate.dir/main.cpp.o /home/cosme/src/darkplate/src/main.cpp: In function ‘void process_plate(DarkHelp::NN&, cv::Mat&, cv::Mat&)’: /home/cosme/src/darkplate/src/main.cpp:77:25: error: loop variable ‘prediction’ creates a copy from type ‘const DarkHelp::PredictionResult’ [-Werror=range-loop-construct] 77 | for (const auto prediction : results) | ^~~~~~~~~~ /home/cosme/src/darkplate/src/main.cpp:77:25: note: use reference type to prevent copying 77 | for (const auto prediction : results) | ^~~~~~~~~~ | & cc1plus: all warnings being treated as errors make[2]: *** [src/CMakeFiles/DarkPlate.dir/build.make:76: src/CMakeFiles/DarkPlate.dir/main.cpp.o] Error 1 make[1]: *** [CMakeFiles/Makefile2:98: src/CMakeFiles/DarkPlate.dir/all] Error 2 make: *** [Makefile:91: all] Error 2

Any ideas? My guess is user error :)

Thanks, Cosme

opened by hurlyburlymarley 6
Awesome work

Hi Stephane,

This is really good, just one issue. How can I reduce the input video size to make it run smoothly. Right now its running the input video in full 1080p mode, hence slow. Is there any way to pass the video in lower resolution to the inference model so as to make it realtime ?

opened by rsingh2083 2
about license plate datasets

Dear Stephan: I think you used the yolov4-tiny model for training. I want to use yolov4 model to train the license plate detection model. Would you please provide your labeled dataset? Thanks a lot!

opened by opentld 1
How to add class names in DarkPlate
Hi Stephan,

I copied my images directory in DarkPlate/nn directory , but while loading the images I can see only 4 classes :-

bicycle car truck person

There is no "plate" or number/alphabet class at all. How to add these classes ?
opened by rsingh2083 1
How to train with gray channel only?

Hello, Stephane! Could you tell me how to train a model only on a gray channel? I do not need RGB, as many experiments have shown that special modes of compensation of light from the camera in the black and white image mode work much better than the color image. In this regard, it is necessary to test the model with only the gray channel. What do I need to change to get a single channel model? Thanks in advance!

opened by MichaelBryce90 1
More details
Could you explain better the idea behind this projected? As far I am concerned, it looks like you :

Trained YOLO to recognize (Letters/Numbers + License Plate)

Parse video, detect each frame

Filter only detections inside 'License Plate detection bbox'

Read detections labels from left to right
opened by folkien 2

Owner

Stéphane Charette

C/C++ developer. Mostly linux-based. IoT, desktop, and embedded device. Computer vision, neural networks, Ubuntu geek.

GitHub

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License plate parsing using Darknet and YOLO

Related tags

Overview

DarkPlate

Dependencies

Build and run

Comments

Multiple video source

Make error

Awesome work

about license plate datasets

How to add class names in DarkPlate

How to train with gray channel only?

More details

Owner

Stéphane Charette

Example of using YOLO v4 with OpenCV, C++ and Python

Marking up images for use with Darknet.

Support Yolov4/Yolov3/Centernet/Classify/Unet. use darknet/libtorch/pytorch to onnx to tensorrt

DarkHelp - C++ wrapper library for Darknet

(ROS) YOLO detection with TensorRT, utilizing tkDNN

YOLO v5 ONNX Runtime C++ inference code.

C Language version for yolo in risc-v

An implementation of [Jimenez et al., 2016] Ground Truth Ambient Occlusion, MIT license

ORB-SLAM3 is the first real-time SLAM library able to perform Visual, Visual-Inertial and Multi-Map SLAM with monocular, stereo and RGB-D cameras, using pin-hole and fisheye lens models.

Radeon Rays is ray intersection acceleration library for hardware and software multiplatforms using CPU and GPU

We implemented our own sequential version of GA, PSO, SA and ACA using C++ and the parallelized version with CUDA support

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