https://github.com/blankeos/license-plate-detection
🪪 Detect License Plate with YOLOV5, OpenCV, and EasyOCR. Built with PySide and Firebase.
https://github.com/blankeos/license-plate-detection
Last synced: about 1 year ago
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🪪 Detect License Plate with YOLOV5, OpenCV, and EasyOCR. Built with PySide and Firebase.
- Host: GitHub
- URL: https://github.com/blankeos/license-plate-detection
- Owner: Blankeos
- Created: 2024-04-03T14:35:20.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-04-29T10:34:20.000Z (about 2 years ago)
- Last Synced: 2025-02-13T08:41:46.443Z (over 1 year ago)
- Language: Python
- Homepage:
- Size: 12.4 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LicensePlateDetection/__init__.py
Awesome Lists containing this project
README
License Plate Detection
A super simple prototype of a license plate detection application.
Built with:
- PySide6 - GUI
- OpenCV - For image transformations
- YoloV5 - For detections (Might upgrade to YoloV8)
- EasyOCR - for OCR detection
- Firebase - For cloud data storage.
Table of Contents
- [📝 Running Requirements](#%F0%9F%93%9D-running-requirements)
- [🏁 Getting Started](#%F0%9F%8F%81-getting-started)
- [Resources](#resources)
- [Notes](#notes)
## 📝 Running Requirements
- Install [Git](https://git-scm.com/downloads) - On Mac it's already installed.
- Install [Python 3.12.2](https://www.python.org/downloads/)
## 🏁 Getting Started
Open your terminal and do the following:
1. Git clone and go to directory
```sh
git clone https://github.com/Blankeos/license-plate-detection
cd license-plate-detection
```
2. Create Virtual Env:
```sh
python -m venv .venv
```
2. Activate Virtual Env:
```sh
# macOS/Linux
source .venv/bin/activate
# Windows
.venv\Scripts\activate
```
3. Install Deps
```sh
# Install deps for the project.
pip install -r requirements.txt
# Install deps for the model.
git clone https://github.com/ultralytics/yolov5
pip install -r yolov5/requirements.txt
```
4. Create a file called `serviceAccount.json` in the root and paste your **Firebase Project Service Credentials**
> This data is sensitive. Protect it or you risk getting spammed on Firebase.
💡 How to generate it.
1. Go to project settings in Firebase.
2. Generate private key.
3. Rename it to `serviceAccount.json`
```jsonc
// Example `serviceAccount.json`
{
"type": "service_account",
"project_id": "project-id-here",
"private_key_id": "private-key-id-here",
"private_key": "private-key-here",
"client_email": "license-plate-detection-v1-ser@project-id-here.iam.gserviceaccount.com",
"client_id": "123456789101112131415",
"auth_uri": "https://accounts.google.com/o/oauth2/auth",
"token_uri": "https://oauth2.googleapis.com/token",
"auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
"client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/subdomain.iam.gserviceaccount.com",
"universe_domain": "googleapis.com"
}
```
5. Run the app (It will take a while the first run)
```sh
python main.py
```
## Resources
https://realpython.com/python-pyqt-gui-calculator/
## Notes
- We use an existing YoloV5 model `best.pt` from this repo: [here](https://github.com/KALYAN1045/Automatic-Number-Plate-Recognition-using-YOLOv5/blob/main/Weights/best.pt).