Hands-on tutorial: Traffic sign classifier with Tensorflow

Preparation steps

You can download this jupyter notebook with git from here: git clone https://github.com/olesalscheider/traffic-sign-tutorial

Please follow these preparation steps before the hands-on tutorial so that you come with a prepared system:

Please install all required dependencies:
- Python 3
- Jupyter
  - pip3 install --upgrade jupyter
- Pillow
  - pip3 install --upgrade pillow
- urllib3
  - pip3 install --upgrade urllib3
- numpy
  - pip3 install --upgrade numpy
- Tensorflow
  - pip3 install --upgrade tensorflow for the CPU variant
  - pip3 install --upgrade tensorflow-gpu if you have a GPU with CUDA and CUDNN support
  - More details on https://www.tensorflow.org/install/
Download and extract the traffic sign dataset (GTSRB). Execute the first cell with Python code the jupyter notebook to do so.

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traffic-sign-tutorial.ipynb		traffic-sign-tutorial.ipynb