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# ML License Plate Vision | |
## Overview | |
ML License Plate Vision is a Python-based solution for detecting and reading license plates in images. It utilizes advanced machine learning techniques and OCR (Optical Character Recognition) to accurately identify and extract license plate information from a given image. | |
## How it works | |
The whole process consist of three steps: | |
1. recognizing the license plate in the image | |
2. cropping the image to the license plate area, enhancing the image in order to be more readable for OCR | |
3. reading the license plate from the cropped image with the OCR mechanisms | |
The demo implementation uses two ways of reading license plates: | |
- Tesseract OCR | |
- Microsoft/TrOCR | |
## Installation | |
To use ML License Plate Vision, you need to have Python installed on your system. Clone the repository and install the required dependencies: | |
```bash | |
$ git clone https://github.com/Modevntalking-com/ml-license-plate-vision.git | |
$ cd ml-license-plate-vision | |
$ pip install -r requirements.txt | |
``` | |
## Usage | |
To detect and read license plates in an image, run the detect.py script with the image URL as an argument: | |
```bash | |
$ python ./detect.py -i [IMAGE_URL] | |
``` | |
For example: | |
```bash | |
$ python ./detect.py -i https://modevntalking.pl/wp-content/uploads/2023/11/IMG_5513-scaled.jpeg | |
``` | |
Example Output | |
Running the above command will produce the following output: | |
```plain | |
detecting license plate from image: https://modevntalking.pl/wp-content/uploads/2023/11/IMG_5513-scaled.jpeg | |
license plate trocr: GA 250HW | |
license plate tesseract: GA250HW | |
``` | |
based on the photo of a car: | |
 | |
Which will be processed - the license plate will be detected, cropped, enhanced and used: | |
 | |
## Summary | |
The blog post about this project is available at [https://modevntalking.com/2023/11/23/ai-ml-vision-license-plate-recognition/](https://modevntalking.com/2023/11/23/ai-ml-vision-license-plate-recognition//). |