Inicio Explorar Ayuda
Iniciar sesión
Prise3D
/
Thesis-NoiseDetection-CNN
2
0
Fork 0
Archivos Incidencias 0 Pull Requests 0 Wiki

Syntesis images noise detection using CNN approach

Árbol: 2c8ad26c6b
Ramas Etiquetas
Thesis-Noise...
ZIP TAR.GZ
jbuisine 2c8ad26c6b Add of model using SVD of images hace 6 años
img_train a22b32b71a First CNN model version hace 6 años
img_validation a22b32b71a First CNN model version hace 6 años
.gitignore 2c8ad26c6b Add of model using SVD of images hace 6 años
README.md db0864c00b Update of README file hace 6 años
RESULTS.md 2c8ad26c6b Add of model using SVD of images hace 6 años
classification_cnn_keras.py 2c8ad26c6b Add of model using SVD of images hace 6 años
classification_cnn_keras_cross_validation.py 2c8ad26c6b Add of model using SVD of images hace 6 años
classification_cnn_keras_svd.py 2c8ad26c6b Add of model using SVD of images hace 6 años
generate_dataset.py 2c8ad26c6b Add of model using SVD of images hace 6 años
requirements.txt 2c8ad26c6b Add of model using SVD of images hace 6 años

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.