nirmal-25/Advanced-Driver-Assistance-Systems-ADAS
A deep learning approach to traffic lights/signs detection and car distance estimation is implemented using background thresholding to train multiple datasets, leading to much better cross-detections.
This project helps automotive engineers and researchers develop and evaluate Advanced Driver Assistance Systems (ADAS). It takes raw video footage from a vehicle's camera and outputs real-time detections of traffic lights, traffic signs, and estimated distances to cars ahead. It is designed for those working on autonomous driving or driver assistance features.
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Use this if you need a robust, pre-trained model and pipeline for detecting common road objects and estimating car distances in video sequences.
Not ideal if you require object detection for non-automotive applications or prefer to work with the latest TensorFlow 2.x versions.
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Jupyter Notebook
License
MIT
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Last pushed
Jan 13, 2022
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