- This is a tool for unsupervised feature extraction with spiking neural networks.
- Neurons are non-leaky integrate and fire. There are methods to enforce lateral inhibition, STDP competition.
- It provides insights like spike activity, feature extraction, animation of synapse evoltuion for each layer etc.
- It also provides feature classification class and a few other jupyter notebooks with misc codes.
AllDataSetsfolder should contain the data that you wish to work with.spykeflowfolder contains all the important classes of SpykeFlow.notebookscontains miscelleneous jupyter notebooks for classification, plots, etc.outputscontains all the outputs/plots generated so far with SpykeFlow.notebooks/main_emnist.ipynbshows an example to train a spiking convolutional layer with two conv and pool layers with EMNIST dataset and effects of lateral inhibition on spike activity and feature extraction inside the network.notebooks/main_facebike.ipynbshows an example to train a spiking convolutional layer with three conv and pool layers with facebikes dataset and effects of lateral inhibition on spike activity and feature extraction inside the network.- An example notebook to classify the extracted spike features is given in
notebooks/classifierclass_usage.ipynb. - Exhaustive list of requirements in listed in
requirements.txthowever most important requirements are NumPy==1.15.3,SciPy==1.1.0,Progressbar==2.3,Theano==0.8.0,Pandas==u'0.20.3,Pickle==$Revision:72223$,Matplotlib==2.2.3,Keras==2.2.4,Sklearn==0.19.1,OpenCv==3.3.0,Tensorflow==1.14.0.- Unfortunately, the code is in
Python2.7. I will work on porting it toPython3.7soon. I started working on this tool from Summer 2018 and Python 2.7 was still in the game for many packages that I was experimenting with and I chose to dance with the same girl that I came with.