This repository contains the code for Advanced Driver Assistance System using Traffic signs & Driver EEG data.
Summary of the Project:
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We used EEG signal to detect the drowsiness of driver and also parallely detects the traffic signs from the dash board camera.
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belgium traffic sign dataset is used for deep learning model training - http://btsd.ethz.ch/shareddata/.
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EEG brain wave data from Kaggle is used for detecting the driver drowsiness detection - https://www.kaggle.com/wanghaohan/eeg-brain-wave-for-confusion.
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For the traffic sign board recognition we resized all the images into 32×32×3 and used three fully connected layers with 200,100,62 number neurons in each layer.
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Linear SVM is used to classify EEG Signal data for driver drowsiness detection.
Description of the python file:
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EEG_python_out.py - EEG signal data classification
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sign_model_3_out.py - Traffic Sign board recognition
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combined_out_main.py - Final classification based on the EEG data and Traffic sign board recognition.