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A Node-RED node for license plate recognition.

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View how to integrate with other languages in our documentation.

It lets you take a picture and send it to our API. See our sample projects to easily get started with the API. It can also forward the results to our parking management service Parkpow.

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Once processed, images are moved to an archive directory. It monitors a folder and automatically process images (Cloud or SDK) as they are added. To remove images from FTP server after processing, add the argument -delete.Īutomatic Image Transfer is a command line tool that runs our ALPR Engine. Python ftp_processor.py -api-key MY_API_KEY -ftp-host hostname -ftp-user user -ftp-password password -folder /path/to/server_folder To process images from the FTP server run ftp_processor script:

Python number_plate_redaction.py -sdk-url -split-image vehicels.jpg Python number_plate_redaction.py -api-key API_KEY vehicels.jpg The option -ignore-no-bb lets you ignore recognitions without a vehicle bounding box from blur. This option can be specified multiple times. The option -ignore-regexp lets you specify a regex of plates to ignore from blur. They are saved to a new file with _blurred suffix. The option -save-blurred lets you save blurred images. This will use 3 lookups instead of just 1. In addition, it can split the image in smaller images to better deal with high resolution images. They can be used to blur or mask the license plates. It returns the bounding boxes of all the license plates. The script number_plate_redaction.py differs from the default prediction script because it also detects plates that are barely readable and/or very small. Python plate_recognition.py -sdk-url /path/to/vehicle.jpg To use a locally hosted sdk, pass the url to the docker container as follows: Python plate_recognition.py -api-key MY_API_KEY /path/to/car1.jpg /path/to/car2.jpg /path/to/trucks*.jpg Running the ALPR Locally (SDK) To run the script on all the images of a directory, use: You can also run the license plate reader on many files at once. Python plate_recognition.py -api-key MY_API_KEY -regions fr -regions it /path/to/car.jpg Process Multiple Files (Batch Mode) You can match the license plate patterns of a specific region. Replace MY_API_KEY with your API key and run the command below.

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Our license plate recognition (LPR) software can also forward results to our full ALPR Dashboard and Parking Management software solution, ParkPow.

Runs on-premise on Linux, Windows, Mac and Jetson.ĪLPR, ANPR software is ideal for parking, highway monitoring, toll, police surveillance, community security, and other use cases.

Handles 4 cameras simultaneously on mid-range PC.

Returns license plate results via CSV file or Webhooks.

Stream : Get number plate recognition from camera or video feed:

Runs on-premise on Linux, Windows, Mac, Jetson, Kubernetes, Raspberry Pi, Zynq, 96Boards, LattePanda and more.

Returns results via JSON Response or Webhooks.

Access a simple REST API for easy integration in 8 programming languages.

Snapshot : Get license plate reader from images in under 60 minutes:

Is optimized for all 50 USA States, India, Brazil and 90+ countries worldwide.

SUV, van, pickup truck), vehicle make model (e.g.

Decodes license plate, vehicle type (e.g.

Works on dark, low-res, blurry images and tough angles, all vehicle types, etc.

Number Plate Recognition on a Video or Camera Stream.

Get high-accuracy, developer-friendly automatic license plate recognition ( ALPR) or automatic number plate recognition ( ANPR) software! The core of our ALPR, ANPR system is based on state of the art deep neural networks architectures. Automatic License Plate Recognition Software (ALPR, ANPR)