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@@ -14,18 +14,22 @@ python generate_dataset.py
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It will split scenes and generate all data you need for your neural network.
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It will split scenes and generate all data you need for your neural network.
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-You can specify the number of sub images you want in the script by modifying **_NUMBER_SUB_IMAGES_** variables.
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+You can specify the number of sub images you want in the script by modifying **_NUMBER_SUB_IMAGES_** variable or using parameter.
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+
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+```
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+python generate_dataset.py --nb xxxx
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+```
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There are 3 kinds of Neural Networks :
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There are 3 kinds of Neural Networks :
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- **classification_cnn_keras.py** : *based on cropped images and do convolution*
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- **classification_cnn_keras.py** : *based on cropped images and do convolution*
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- **classification_cnn_keras_cross_validation.py** : *based on cropped images and do convolution. Data are randomly split for training*
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- **classification_cnn_keras_cross_validation.py** : *based on cropped images and do convolution. Data are randomly split for training*
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- **classification_cnn_keras_svd.py** : *based on svd metrics of image*
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- **classification_cnn_keras_svd.py** : *based on svd metrics of image*
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-Note that the image input size need to change in you used specific size for your croped images.
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After your built your neural network in classification_cnn_keras.py, you just have to run it :
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After your built your neural network in classification_cnn_keras.py, you just have to run it :
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+
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```
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```
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-classification_cnn_keras_svd.py --directory xxxx --output xxxxx --batch_size xx --epochs xx --img xx (or --image_width xx --img_height xx)
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+python classification_cnn_keras_svd.py --directory xxxx --output xxxxx --batch_size xx --epochs xx --img xx (or --image_width xx --img_height xx)
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```
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```
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A config file in json is available and keeps in memory all image sizes available.
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A config file in json is available and keeps in memory all image sizes available.
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