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Classify traffic signs from camera images of an autonomus car.

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Traffic Sign Classifier

Traffic Sign

Overview

In this project, I have implemented a classifier using deep neural networks, convolutional neural networks and transfer learning to classify traffic signs. I have trained a model so that it can decode traffic signs from natural images by using the German Traffic Sign Dataset. After the model is trained, I have tested my model program on new images of traffic signs collected from the web and captured images of traffic sign locally collected from a friend.

Dataset

  1. Download the dataset. This is a pickled dataset in which we've already resized the images to 32x32.

#Test Results Follow the keras version traffic-sign-classification-with-keras.ipynb for updated results ###Validation accuracy 99.31 % ###Test accuracy 95.44 %

#Model architecture

Layer (type) Output Shape Param # Connected to
convolution2d_11 (Convolution2D) (None, 28, 28, 6) 456 convolution2d_input_9[0][0]
maxpooling2d_10 (MaxPooling2D) (None, 14, 14, 6) 0 convolution2d_11[0][0]
activation_10 (Activation) (None, 14, 14, 6) 0 maxpooling2d_10[0][0]
convolution2d_12 (Convolution2D) (None, 10, 10, 16) 2416 activation_10[0][0]
maxpooling2d_11 (MaxPooling2D) (None, 5, 5, 16) 0 convolution2d_12[0][0]
activation_11 (Activation) (None, 5, 5, 16) 0 maxpooling2d_11[0][0]
flatten_7 (Flatten) (None, 400) 0 activation_11[0][0]
dense_15 (Dense) (None, 128) 51328 flatten_7[0][0]
dropout_11 (Dropout) (None, 128) 0 dense_15[0][0]
activation_12 (Activation) (None, 128) 0 dropout_11[0][0]
dense_16 (Dense) (None, 43) 5547 activation_12[0][0]
Total params: 59747

Trained on 26270 samples, validated on 12939 samples