Purpose of this project was to train a image classifier to recognize indoor scene from 67 different category. Classifier cnn modal's accuracy found to be 0.86 for testing. Trained dataset includes 15617 files from all 67 classes. Splitted as 0.7 for train, 0.2 for validation, 0.1 for testing.
MIT Indoor Dataset
https://web.mit.edu/torralba/www/indoor.html
Modal's Acc Loss:
TO DO:
-Fine tuning w/ Densenet, VGG16, Alexnet compare the results.
-Try LoRA (Low rank adaptation).