This repository contains 4 python scripts that points out what a kernel is, how to create testdata for a convolutional neuronal network, how to create and train a neuronal network and finally how to run camera capture live images against this neuronal network.
https://www.youtube.com/watch?v=Q4-DOaoceys
Image dimension is 26x26 and there are 3 classification types:
The total amount of images is just 429 (including 43 images for validation). This is very little training data for a CNN, but the results are very good.
python-3.6.8-amd64.exe https://www.python.org/downloads/release/python-368/
pip install opencv-python
pip install matplotlib
pip install tensorflow==1.8.0
pip install keras==2.1.5
pip install sklearn
pip install pandas
pip install absl-py
pip install pathlib
https://www.machinecurve.com/index.php/2019/09/17/how-to-create-a-cnn-classifier-with-keras/ https://www.learnopencv.com/image-classification-using-convolutional-neural-networks-in-keras/ https://github.com/spmallick/learnopencv/tree/master/KerasCNN-CIFAR https://www.tensorflow.org/tutorials/images/classification https://github.com/spmallick/learnopencv https://pythonprogramming.net/using-trained-model-deep-learning-python-tensorflow-keras/