Plate Recognizer examples and utilities
This repository contains example clients, integrations, and operational utilities
for Plate Recognizer Snapshot, Stream, Blur, and
ParkPow. It does not contain the recognition models themselves.
Use the quickstart below to recognize a plate in an image, or jump to the
repository map to find a tool for another workflow.
Image recognition quickstart
Prerequisites
Clone the repository and install the two dependencies required by the image
client:
git clone https://github.com/parkpow/deep-license-plate-recognition.git
cd deep-license-plate-recognition
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
python -m pip install requests pillow
Run recognition against the cloud API:
python plate_recognition.py --api-key MY_API_KEY /path/to/vehicle.jpg
Replace MY_API_KEY locally and do not commit your token. To use a running
self-hosted Snapshot SDK instead:
python plate_recognition.py --sdk-url http://localhost:8080 /path/to/vehicle.jpg
The command returns JSON containing the recognized plate, confidence scores,
and bounding box. The complete response schema is in the
Snapshot API reference.
[
{
"version": 1,
"results": [
{
"box": {"xmin": 85, "ymin": 85, "ymax": 211, "xmax": 331},
"plate": "ABC123",
"score": 0.904,
"dscore": 0.92
}
],
"filename": "car.jpg"
}
]
Common image workflows
Limit recognition to one or more regions:
python plate_recognition.py --api-key MY_API_KEY --regions fr --regions it /path/to/car.jpg
Process several files or a shell glob:
python plate_recognition.py --api-key MY_API_KEY /path/to/car1.jpg /path/to/car2.jpg /path/to/trucks*.jpg
Run python plate_recognition.py --help for all available output, annotation,
cropping, and engine options. See the
bulk-processing guide
for a longer walkthrough.
Repository map
Each subproject has its own dependencies. Follow its README or requirements
file instead of assuming the image-client installation covers the entire
repository. The root pyproject.toml contains the shared Python development
environment, managed with uv.
Development setup
Install uv, then create the root development environment from uv.lock:
uv sync --locked
The root is a collection of scripts rather than an installable package. Run
tools in its environment with uv run, for example:
uv run pre-commit install
uv run pre-commit run --all-files
The first command installs the repository’s Git hooks; the second runs every
configured hook against the repository.
Plate redaction
number_plate_redaction.py detects plates—including small or barely readable
ones—and can save a blurred copy of an image.
python number_plate_redaction.py --api-key MY_API_KEY vehicle.jpg --save-blurred
Useful options include:
--split-image for high-resolution images; this uses three API lookups.--ignore-regexp REGEX to leave matching plates unblurred. Repeat the option
to provide more than one expression.--ignore-no-bb to ignore results without a vehicle bounding box.
python number_plate_redaction.py \
--sdk-url http://localhost:8080 \
--split-image \
--save-blurred \
vehicle.jpg
Run python number_plate_redaction.py --help for the complete CLI reference.
FTP and SFTP processing
Use ftp_and_sftp_processor.py to fetch images from your own FTP or SFTP
server and recognize them with the cloud API or a self-hosted SDK.
python -m pip install requests pillow paramiko
python ftp_and_sftp_processor.py \
--api-key MY_API_KEY \
--hostname FTP_HOST_NAME \
--ftp-user FTP_USER \
--ftp-password FTP_PASSWORD \
--folder /path/to/server_folder
Add --protocol sftp for SFTP. Authentication can use --ftp-password or
--pkey. The --delete option removes processed remote files, so test without
it first. Run python ftp_and_sftp_processor.py --help for camera, polling,
output format, and SDK options.
See the FTP/SFTP bulk-processing guide
for setup details. Plate Recognizer also provides a hosted
FTP integration.
Automatic image transfer
transfer.py watches a directory, recognizes new images, and moves processed
images into an archive. It can optionally forward results to
ParkPow.
python -m pip install requests watchdog jsonlines
python transfer.py --help
The help output includes examples for the cloud API and a self-hosted SDK, as
well as the required source, archive, and camera-path options.
Language examples
For other languages, start with the
API documentation or convert
the API’s curl examples with curlconverter.
Support and license
For product questions, contact Plate Recognizer.
This repository is provided under the terms in LICENSE.
Plate Recognizer is a subsidiary of ParkPow.
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