1. DETECTION:- In this part, we used YOLOv3 with darknet configuration to detect the license plates with pre-trained weights and model and then store the coordinates in a json file. https://github.com/SwarnenduGanguli25/Vehicle_Number_Plate_Recognition/blob/main/Vehicle_Number_Plate_Detection(Using_YOLOv3).ipynb
2. CROPPING:- Here, we cropped out the license plate from the rest of the image by deducing border coordinates from the json file. https://github.com/SwarnenduGanguli25/Vehicle_Number_Plate_Recognition/blob/main/Vehicle_Plates_Crop(OCR).ipynb
3. RECOGNITION:- This is the final part where we recognized the text from the license plates.
a) Using Microsoft Visual Studio API:
https://github.com/SwarnenduGanguli25/Vehicle_Number_Plate_Recognition/blob/main/Vehicle_Number_Plates(OCR).ipynb
b) Using Tesseract(Open Source):
https://github.com/SwarnenduGanguli25/Vehicle_Number_Plate_Recognition/blob/main/OCR_Using_Pytesseract.ipynb
All the files were not able to be uploaded due to large size. So, here are the links which will help you:
Training Dataset- https://drive.google.com/file/d/1t20-WpJWvon2o7MdoS88FyBw8yYrRKln/view
Test Dataset- https://drive.google.com/file/d/1as5wGXC3M4ErAYn9Q0vxeLPwlS5JInNV/view
Initial Weights(To be used in YOLO)- https://drive.google.com/file/d/1OBNcSfNH53HHCEZbfIRsCygDCevS8NaJ/view
Trained Weights(To be used in YOLO)- https://drive.google.com/file/d/1I3JY2-0mr1wNz7ifEzxct8GJyxEy-doL/view
Dataset used for OCR with Tesseract- https://drive.google.com/drive/folders/14WqPaVs3dQ_A5PDznk0t7KQTlOhwsJKT?usp=sharing
Also, you need to GIT CLONE(For Darknet): https://github.com/AlexeyAB/darknet.git
Config File- https://drive.google.com/file/d/1LUn13-uzHkPDaCjnNvJwiDnUWYROZeBB/view?usp=sharing
Train.txt File- https://drive.google.com/file/d/1GR4MAlj4l5RrqqXvCrCMwRKmc0Qz13NK/view?usp=sharing
Valid.txt File- https://drive.google.com/file/d/1do-En6hXvgPv2JG4-g1ro5Dz8hlYCx9R/view?usp=sharing
obj.data File- https://drive.google.com/file/d/1dr9hrp6GlBih7b7Nl8orf0nY3yN8OdFV/view?usp=sharing
obj.name File- https://drive.google.com/file/d/1XMeEWbGjHvBo7m-wSIeNM03n0UNioTuQ/view?usp=sharing
https://medium.com/data-science-in-your-pocket/vehicle-number-plate-detection-and-ocr-tcs-humain-2019-a253019e52a1
https://medium.com/data-science-in-your-pocket/image-labelling-for-yolo-using-yolo-mark-c58eb75b77fd
https://pjreddie.com/darknet/yolo/
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/quickstarts-sdk/client-library?tabs=visual-studio&pivots=programming-language-python
https://github.com/Azure-Samples/cognitive-services-quickstart-code/blob/master/python/ComputerVision/REST/python-print-text.md