Syntesis images noise detection using CNN approach

Jérôme BUISINE 7b3768132f Add of new reconstruction metric		il y a 4 ans
modules	7b3768132f Add of new reconstruction metric	il y a 4 ans
.gitignore	7b3768132f Add of new reconstruction metric	il y a 4 ans
LICENSE	f80a4942e7 Creation of dataset file script added	il y a 4 ans
README.md	7b3768132f Add of new reconstruction metric	il y a 4 ans
RESULTS.md	2c8ad26c6b Add of model using SVD of images	il y a 5 ans
generate_dataset.py	7b3768132f Add of new reconstruction metric	il y a 4 ans
generate_reconstructed_data.py	7b3768132f Add of new reconstruction metric	il y a 4 ans
requirements.txt	153ef98eae Update code with use of IPFML package	il y a 5 ans
run.sh	7b3768132f Add of new reconstruction metric	il y a 4 ans
train_model_2D.py	7b3768132f Add of new reconstruction metric	il y a 4 ans
transformation_functions.py	7b3768132f Add of new reconstruction metric	il y a 4 ans

Noise detection project

Requirements

pip install -r requirements.txt

Generate reconstructed data from specific method of reconstruction (run only once time or clean data folder before):

python generate_reconstructed_data.py -h

Generate custom dataset from one reconstructed method or multiples (implemented later)

python generate_dataset.py -h

List of expected parameter by reconstruction method:

svd: Singular Values Decomposition
- Param definition: interval data used for reconstruction (begin, end)
- Example: "100, 200"
ipca: Iterative Principal Component Analysis
- Param definition: number of components used for compression and batch size
- Example: "50, 32"
fast_ica: Fast Iterative Component Analysis
- Param definition: number of components used for compression
- Example: "50"

This project contains modules:

modules/utils/config.py: Store all configuration information about the project and dataset information
modules/utils/data.py: Usefull methods used for dataset

All these modules will be enhanced during development of the project