Homework Number 2 For Machine Learning Course in Sapienza All the information about this project are in the report at the link: https://api.wandb.ai/report/sapienza_ml_2022_23/wemom697
The dataset used is totally contained in the Dataset folder in the root
This part is in the Efficient Net file
The task chosen for this homework is the classification of domestic enviroments. The main goal behind this choice is to include the project in a real world website. The purpose of this website is to give people the opportunity to find new apartments in new buildings that meets specified requirements. So, when the rendering of an apartment are uploaded on the website, the inference process will attach the label of classification to the image; this information will be useful to then create automatic new filters based on new contents periodically added. For this project the library chosen is pytorch, weight and biases has been use to generate this report and most of the data visualization graphs and images in this document. Furthermore have been choosen two differents type of model, one Deit, a VisionTransformer model based on the transformers architecture, and the other one, EfficientNet based on the classic convolutional neural networks architecture.