License Plate Recognition Source Code Copyright
README.md openalpr OpenALPR is an open source Automatic License Plate Recognition library written in C with bindings in C#, Java, Node.js, Go, and Python. The library analyzes images and video streams to identify license plates. The output is the text representation of any license plate characters. Check out a live online demo here: User Guide OpenALPR includes a command line utility. Simply typing 'alpr image file path' is enough to get started recognizing license plate images.
- License Plate Recognition API & SDK. Applications which offer License Plate Recognition functionalities utilise the license plate recognition capabilities and functions of a License Plate Recognition Engine. The License Plate Recognition Engine (the core recognition module) has an Application Programming Interface (API), which is a series of functions that the application program can use to.
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For example, the following output is created by analyzing this image: user@linux:/openalpr$ alpr./samplecar.png plate0: top 10 results - Processing Time = 58.1879ms. PE3R2X confidence: 88.9371 - PE32X confidence: 78.1385 - PE3R2 confidence: 77.5444 - PE3R2Y confidence: 76.1448 - P63R2X confidence: 72.9016 - FE3R2X confidence: 72.1147 - PE32 confidence: 66.7458 - PE32Y confidence: 65.3462 - P632X confidence: 62.1031 - P63R2 confidence: 61.5089 Detailed command line usage: user@linux:/openalpr$ alpr -help USAGE: alpr -c -config -n -seek -p -clock -d -j - -version -h Where: -c, -country Country code to identify (either us for USA or eu for Europe). Default=us -config Path to the openalpr.conf file -n, -topn Max number of possible plate numbers to return. Default=10 -seek Seek to the specified millisecond in a video file.
Default=0 -p, -pattern Attempt to match the plate number against a plate pattern (e.g., md for Maryland, ca for California) -clock Measure/print the total time to process image and all plates. Default=off -d, -detectregion Attempt to detect the region of the plate image. Experimental Default=off -j, -json Output recognition results in JSON format. Default=off -, -ignorerest Ignores the rest of the labeled arguments following this flag.version Displays version information and exits.h, -help Displays usage information and exits. Image containing license plates OpenAlpr Command Line Utility Binaries Pre-compiled Windows binaries can be downloaded on the Install OpenALPR on Ubuntu 16.04 with the following commands: sudo apt-get update && sudo apt-get install -y openalpr openalpr-daemon openalpr-utils libopenalpr-dev Documentation Detailed documentation is available at Integrating the Library OpenALPR is written in C and has bindings in C#, Python, Node.js, Go, and Java.
Please see this guide for examples showing how to run OpenALPR in your application: Compiling OpenALPR compiles and runs on Linux, Mac OSX and Windows. OpenALPR requires the following additional libraries: - Tesseract OCR v3.0.4 (- OpenCV v2.4.8+ (After cloning this GitHub repository, you should download and extract Tesseract and OpenCV source code into their own directories. Compile both libraries.
Please follow these detailed compilation guides for your respective operating system:. If all went well, there should be an executable named alpr along with libopenalpr-static.a and libopenalpr.so that can be linked into your project. # Build docker image docker build -t openalpr # Download test image wget # Run alpr on image docker run -it -rm -v $(pwd ):/data:ro openalpr -c eu h786poj.jpg Questions Please post questions or comments to the Google group list: Contributions Improvements to the OpenALPR library are always welcome.
Please review the and get started. Code contributions are not the only way to help out.
Do you have a large library of license plate images? If so, please upload your data to the anonymous FTP located at upload.openalpr.com. Do you have time to 'tag' plate images in an input image or help in other ways? Please let everyone know by posting a note in the forum.
Free License Plate Recognition
License Affero GPLv3 Commercial-friendly licensing available.