vehicle number plate detection and ocr using YOLO .

Demonstration

The Approach

The identifier's approach is straightforward:

1. Determine if a number plate is in the picture
2. Identify where that number plate is
3. Crop out the relevant asset
4. Read characters in the cropped picture

Details

1. LabelReader uses the Yolov3 algorithm for object detection.

• Darknet (Fast, C Implementation)

2. A pretrained model can be downloaded
3. Link : "https://drive.google.com/open?id=1-48BHxaXTEZv3nwZEN7jAbdPLi2x40v7".
4. Download the model and copy it to the directory
5. For custom training follows this tutorial "https://medium.com/@manivannan_data/how-to-train-yolov2-to-detect-custom-objects-9010df784f36"

Setup

1. If you are already installed Anaconda python you can skip this step https://www.anaconda.com/distribution/

2. conda create -n yolo pip python=3.7

3. conda activate yolo

4. pip install -r requirements.txt

5. apt-get install tesseract-ocr

6. ./darknet

Getting Started

Run the main script

1. python app.py