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Syntesis images noise detection using CNN approach

Drzewo: cb805ba96b
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Thesis-Noise...
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jbuisine cb805ba96b Merge tag 'v0.0.3' into develop 6 lat temu
img_train a22b32b71a First CNN model version 6 lat temu
img_validation a22b32b71a First CNN model version 6 lat temu
.gitignore 2c8ad26c6b Add of model using SVD of images 6 lat temu
README.md db0864c00b Update of README file 6 lat temu
RESULTS.md 2c8ad26c6b Add of model using SVD of images 6 lat temu
classification_cnn_keras.py 2c8ad26c6b Add of model using SVD of images 6 lat temu
classification_cnn_keras_cross_validation.py 2c8ad26c6b Add of model using SVD of images 6 lat temu
classification_cnn_keras_svd.py 2c8ad26c6b Add of model using SVD of images 6 lat temu
generate_dataset.py 2c8ad26c6b Add of model using SVD of images 6 lat temu
requirements.txt 2c8ad26c6b Add of model using SVD of images 6 lat temu

README.md

Noise detection project

Requirements

pip install -r requirements.txt

How to use

Generate dataset (run only once time) :

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_SUB_IMAGES variables.

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

python classification_cnn_keras.py

How to contribute

This git project uses git-flow implementation. You are free to contribute to it.