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Vehicle number plate detection using TFOD API and OpenVINO
This project demonstrates the use of TensorFlow Object Detection API to automatically number plates (Indian) from vehicles. ...learn more
Project status: Published/In Market
Intel Technologies
OpenVINO,
Movidius NCS
Overview / Usage
This project demonstrates the use of TensorFlow Object Detection API to automatically number plates (Indian) from vehicles.
Dataset used: https://www.kaggle.com/dataturks/vehicle-number-plate-detection
To kick-start the model training process, I followed the steps from TensorFlow Object Detection API's official documentation: https://github.com/tensorflow/models/tree/master/research/object_detection. I used SSD_MobileNet_V1 architecture which was pretrained on the COCO dataset.
The main challenge was to prepare the data for TensorFlow Object Detection API. The dataset comes in YOLO dataset format, so a decent amount of effort has been put to prepare the dataset compatible for using with TensorFlow Object Detection API.
Methodology / Approach
Dataset used: https://www.kaggle.com/dataturks/vehicle-number-plate-detection
To kick-start the model training process, I followed the steps from TensorFlow Object Detection API's official documentation: https://github.com/tensorflow/models/tree/master/research/object_detection. I used SSD_MobileNet_V1 architecture which was pretrained on the COCO dataset.
The main challenge was to prepare the data for TensorFlow Object Detection API. The dataset comes in YOLO dataset format, so a decent amount of effort has been put to prepare the dataset compatible for using with TensorFlow Object Detection API. After the model was trained I used OpenVINO to further optimize the network so that I could run inference on my Neural Compute Stick.
Technologies Used
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TensorFlow Object Detection API
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Google Cloud Platform
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OpenVINO
Repository
https://github.com/sayakpaul/Vehicle-Number-Plate-Detection
Collaborators