Syntesis images noise detection using CNN approach

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README.md

Noise detection project

Requirements

pip install -r requirements.txt

How to use

Generate dataset (run only once time or clean data folder before):

python generate_dataset.py

It will split scenes and generate all data you need for your neural network. You can specify the number of sub images you want in the script by modifying _NUMBER_SUBIMAGES variable or using parameter.

python generate_dataset.py --nb xxxx

There are 3 kinds of Neural Networks:

  • classification_cnn_keras.py: based on cropped images and do convolution
  • classification_cnn_keras_cross_validation.py: based on cropped images and do convolution. Data are randomly split for training
  • classification_cnn_keras_svd.py: based on svd metrics of image

After your built your neural network in classification_cnn_keras.py, you just have to run it:

python classification_cnn_keras_svd.py --directory xxxx --output xxxxx --batch_size xx --epochs xx --img xx (or --image_width xx --img_height xx)

A config file in json is available and keeps in memory all image sizes available.

Modules

This project contains modules:

  • modules/image_metrics: where all computed metrics function are developed
  • modules/model_helper: contains helpful function to save or display model information and performance

All these modules will be enhanced during development of the project

License

MIT