Syntesis images noise detection using CNN approach
jbuisine 2c8ad26c6b Add of model using SVD of images | il y a 6 ans | |
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img_train | il y a 6 ans | |
img_validation | il y a 6 ans | |
.gitignore | il y a 6 ans | |
README.md | il y a 6 ans | |
RESULTS.md | il y a 6 ans | |
classification_cnn_keras.py | il y a 6 ans | |
classification_cnn_keras_cross_validation.py | il y a 6 ans | |
classification_cnn_keras_svd.py | il y a 6 ans | |
generate_dataset.py | il y a 6 ans | |
requirements.txt | il y a 6 ans |
pip install -r requirements.txt
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
This git project uses git-flow implementation. You are free to contribute to it.