Noise detection using 26 attributes
Noise detection on synthesis images with 26 attributes obtained using few filters.
pip install -r requirements.txt
Link to your dataset
You need database which respects this structure:
Code architecture description
- modules/*: contains all modules usefull for the whole project (such as configuration variables)
- analysis/*: contains all jupyter notebook used for analysis during thesis
- generate/*: contains python scripts for generate data from scenes (described later)
- data_processing/*: all python scripts for generate custom dataset for models
- prediction/*: all python scripts for predict new threshold from computed models
- data_attributes.py: files which contains all extracted features implementation from an image.
- custom_config.py: override the main configuration project of
- train_model.py: script which is used to run specific model available.
Generated data directories:
- data/*: folder which will contain all generated .train & .test files in order to train model.
- data/saved_models/*: all scikit learn or keras models saved.
- data/models_info/*: all markdown files generated to get quick information about model performance and prediction obtained after running
- data/results/: This folder contains
model_comparisons.csv file used for store models performance.
The MIT license