Using pre-trained Deep Convolution Neural Networks as feature identifiers.

We are going to use a Resnet-50 Model trained on ImageNet dataset, as a feature extractor, for a set of input images. The extracted features will be used by a Linear SVM to predict whether any random input image, is in either one of two classes that it belongs.

Steps are enumerated here:

Jupyter Notebook Download (NB: Unzip before uploading to Jupyter. The notebook ran successfully on macOS Sierra.)

Pre-req: MxNet, OpenCV, ScikitLearn

I recommend you have the latest Anaconda installed, build the MxNet binary and link it with python that came with Anaconda. That would be perfect.