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Data Augmentation
Focuses on the augmentation of the RawData used in the project
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Mantis Detect using a CNN
Focuses on the CNNs created during this project
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Note that if you want to generate more data with the Augmentaion.py file we recommend to copie an existing rawdata folder (e.g. RawData_2C or RawData_17C) and rename it to your own preference.
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Open the Augmentation.py skript using your editor of choise
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Run the Code. This will set your working directory to the source file location and show you an example augmentation
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In the console run the function create_augmented_data(folder,number_wanted_files): for the folder parameter set the name of your folder you want to augment data in. The number_wanted_files parameter stands for your wished number of data in each subfolder at the end of augmentation.
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You will see that the code is runing when you look at the console and will be able to see howmany new data was generated using augmentation.
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Open the file MantisDetect.py in your editor of choice
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If you want to see how the training of the CNNs is archived in this project you can simply run the entire code.
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NOTE If you wish to save your model please end-comend the lines 267 and 338 in the code.
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NOTE If you wish to load the models to use the utility functions without training you can also load the CNNs by end-commend the lines 268 and
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Feel free to play around with the prediction_visualization function.