/InstrumentRecognition

This is an example of object recognition

Instrument Recognition

This code classifies a set of instruments given as a set of images.

-To test: python testing.py the result of classification is the image output.jpg i in /test directory

-To train: python training.py and manually label the instruments (only numbers accepted)

-To validate the dataset and print the confusion matrix: python validate.py

-Directories:

--/storage used to store all features *.npy they correspond to the contours of the instruments after being normalized by rotation

--/test place the image that you want to tes

--/images images used for training