allysonkapers / ai

Traffic Sign Recognition

Still underdevelopment

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Build a Traffic Sign Recognition Project with TensorFlow 2.0

More examples can be found at TensorFlow tutorials

Raw data from Kaggle: GTSRB - German Traffic Sign Recognition Benchmark. Each image in raw downloaded data has different sizes, thus they were processed to have a consistent shape. After processes including: resizing, splitting into training and validation, conversion to grayscale and normalization.

• Number of training examples = 31367
• Number of validation examples = 7842
• Number of testing examples = 12630
• Image data shape = (32, 32, 1)
• Number of classes = 43

My final model consisted of the following layers:

Layer	Description
Input	32x32x1 Grayscale image
Convolution 5x5	1x1 stride, valid padding, outputs 28x28x6
RELU
Max pooling	2x2 stride, outputs 14x14x6
Convolution 5x5	1x1 stride, valid padding, outputs 10x10x16
RELU
Max pooling	2x2 stride, outputs 5x5x6
Fully connected	Input = 400. Output = 120.
Fully connected	Input = 120. Output = 84.
Dropout
Fully connected	Input = 84. Output = 43.
Softmax	Output layer

My final model results were:

• validation set accuracy of ~ 0.98
• test set accuracy of ~ 0.92