Hello and welcome to Denoising_HPatches_for_Descriptor_Learning.
This repository contains the software submission for the Deep learning coursework at Imperial College London.
Submission details:
- Name: Antonio Enas
- CID: 01070859
- Login: AE1115
Further instructions:
- All codes in the repository are accompanied by detailed instructions and comments. The content of each code/folder is explained below.
In this folder:
- 1_baseline_denoiser.ipynb This Colaboratory notebook generates, trains and saves the baseline denoiser model.
- 2_baseline_descriptor.ipynb This Colaboratory notebook generates, trains and saves the baseline descriptor model.
- 3_improved_denoiser.ipynb This Colaboratory notebook generates, trains and saves the improved denoiser model (stacked DnCNN).
- 4_improved_descriptor.ipynb This Colaboratory notebook generates, trains and saves the improved descriptor model based on adapted loss function.
- 5_complete_evaluation.ipynb This Colaboratory notebook contains all the codes for qualitative and quantitative analysis and evaluation.
- AE1115.zip This folder contains all the codes above in a downloadable .zip format
- Trained keras models (.h5 files) in the respective .zip folders