Assignment 3 for SYSC4906. The goal is to build an image classification model to recognize a subset of buildings on Carleton Univeristy campus.
The approach taken is a convolutional neural network. Training makes use of concepts such as data augmentation and dropout. The end results was a model that predicted new images from a randomly selected holdout set with 86% accuracy.
- trainModel.ipynb contains all the code to build and train the model from samples images
- deployModel.ipynb contains all the code to test the model with new images
- model.pkl is a serialization version of the model trained model
- SYSC4906_Assig3_final.ipynb is the contents of both of the previous notebooks combined
- SYSC4906 Assignment 3.pdf is the orginal handout for the assignment
the archive file containing all the images in the dataset is unfortuantely too large to upload here