This was created as part of an educational for the Western Founders Network computer vision and machine learning educational session.

The final demo can be seen here and below:

notebook.ipynb contains a full tutorial of basic computer vision and machine learning concepts, including:

• What computers see
• Image Filters and Functions
  • Blurring
  • Dilating
  • Erosion
  • Canny Edge Detectors
  • Thresholding
• Background Subtraction Techniques
  • Using a background image to find differences
  • Using motion based background subtraction algorithms
• Contours
  • Finding and sorting contours
• Tracking
• (Deep) Neural Networks
• (Deep) Convolutional Neural Networks
• Demo Project: Gesture Recognition
  • Extracting the subject
  • Tracking the hand
  • Collecting data
  • Building the Neural Network
  • Preparing Data for Training
  • Training the Network
  • Plotting Model History

Note: Please check the issues on this repo if you're having problems with the notebook.

• Install Anaconda (https://www.anaconda.com/download/) or Miniconda (https://conda.io/miniconda.html) to save hard drive space
• Start an Anaconda Prompt. (Search Anaconda in the start menu.)

• Install Anaconda (https://www.anaconda.com/download/) or Miniconda (https://conda.io/miniconda.html) to save hard drive space

• For Miniconda, open terminal and navigate to the directory you downloaded Miniconda3-latest-MacOSX-x86_64.sh to and run:

    $ bash Miniconda3-latest-MacOSX-x86_64.sh
  

• For Anaconda, double click the Anaconda3-5.0.1-MacOSX-x86_64.pkg file you downloaded

• For Miniconda, open a terminal and navigate to the directory you downloaded Miniconda3-latest-Linux-x86_64.sh to and run:

    $ bash Miniconda3-latest-Linux-x86_64.sh
  

• For Anaconda, open a terminal and navigate to the directory you downloaded Anaconda3-5.0.1-Linux-x86_64.sh to and run:

    $ bash Anaconda3-5.0.1-Linux-x86_64.sh
  

• Create and activate a Python 3.5 conda environment called cv.

    $ conda create -n cv python=3.5
  
    $ source activate cv
  

• Install Numpy (http://www.numpy.org/)

    $ conda install numpy
  

• Install Matplotlib (https://matplotlib.org/)

    $ conda install matplotlib
  

• Install Keras (https://keras.io/)

    $ conda install keras
  

  • This should also install tensorflow

• Install h5py (http://www.h5py.org/)

    $ conda install h5py
  

• Install Jupyter Notebook (http://jupyter.org/)

    $ conda install jupyter notebook
  

• Install IPython (https://ipython.org/)

    $ conda install ipython
  

• Install OpenCV3 (https://opencv.org/)

    $ conda install -c conda-forge opencv 
  

  if the import cv2 does not work with this install, try instead:

    $ conda install -c https://conda.anaconda.org/menpo opencv3