Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Fast Automatic License Plate Recognition (ALPR) framework.
| Date | Stars |
|---|---|
| 2026-07-24 | 730 |
| 2026-07-25 | 731 |
| 2026-07-28 | 733 |
| 2026-07-30 | 733 |
| 2026-08-06 | 733 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# FastALPR
[](https://github.com/ankandrew/fast-alpr/actions)
[](https://github.com/ankandrew/fast-alpr/actions)
[](https://github.com/astral-sh/ruff)
[](https://github.com/pylint-dev/pylint)
[](http://mypy-lang.org/)
[](https://onnx.ai/)
[](https://huggingface.co/spaces/ankandrew/fast-alpr)
[](https://ankandrew.github.io/fast-alpr/)
[](https://pypi.python.org/pypi/fast-alpr)
[](https://github.com/ankandrew/fast-alpr/releases)
[](./LICENSE)
[](https://youtu.be/-TPJot7-HTs?t=652)
**FastALPR** is a high-performance, customizable Automatic License Plate Recognition (ALPR) system. We offer fast and
efficient ONNX models by default, but you can easily swap in your own models if needed.
For Optical Character Recognition (**OCR**), we use [fast-plate-ocr](https://github.com/ankandrew/fast-plate-ocr) by
default, and for **license plate detection**, we
use [open-image-models](https://github.com/ankandrew/open-image-models). However, you can integrate any OCR or detection
model of your choice.
## 📋 Table of Contents
* [✨ Features](#-features)
* [📦 Installation](#-installation)
* [🚀 Quick Start](#-quick-start)
* [🛠️ Customization and Flexibility](#-customization-and-flexibility)
* [📖 Documentation](#-documentation)
* [🤝 Contributing](#-contributing)
* [🙏 Acknowledgements](#-acknowledgements)
* [📫 Contact](#-contact)
## ✨ Features
- **High Accuracy**: Uses advanced models for precise license plate detection and OCR.
- **Customizable**: Easily switch out detection and OCR models.
- **Easy to Use**: Quick setup with a simple API.
- **Out-of-the-Box Models**: Includes ready-to-use detection and OCR models
- **Fast Performance**: Optimized with ONNX Runtime for speed.
## 📦 Installation
```shell
pip install fast-alpr[onnx-gpu]
```
By default, **no ONNX runtime is installed**. To run inference, you **must** install at least one ONNX backend using an appropriate extra.
| Platform/Use Case | Install Command | Notes |
|--------------------|----------------------------------------|----------------------|
| CPU (default) | `pip install fast-alpr[onnx]` | Cross-platform |
| NVIDIA GPU (CUDA) | `pip install fast-alpr[onnx-gpu]` | Linux/Windows |
| Intel (OpenVINO) | `pip install fast-alpr[onnx-openvino]` | Best on Intel CPUs |
| Windows (DirectML) | `pip install fast-alpr[onnx-directml]` | For DirectML support |
| Qualcomm (QNN) | `pip install fast-alpr[onnx-qnn]` | Qualcomm chipsets |
## 🚀 Quick Start
> [!TIP]
> Try `fast-alpr` in [Hugging Spaces](https://huggingface.co/spaces/ankandrew/fast-alpr).
Here's how to get started with FastALPR:
```python
from fast_alpr import ALPR
# You can also initialize the ALPR with custom plate detection and OCR models.
alpr = ALPR(
detector_model="yolo-v9-t-384-license-plate-end2end",
ocr_model="cct-xs-v2-global-model",
)
# The "assets/test_image.png" can be found in repo root dir
alpExcerpt of 7,368 characters
Read on GitHub
Andrés
121
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:cfced81289a0fd25, topic:onnxruntime
matched fp:cfced81289a0fd25, topic:computer-vision