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This tutorial describes how to use Cinderella to sort micrographs. Unfortunately, we cannot provide a pretrained model yet. Therefore the first step is to train a model (see section Training) and to apply a model (see section Classify)
You can find the download and installation instructions here: Download and Installation
If you would like to train Cinderella with your own classes, you can easily do it.
First you have to separate your good and bad classes into separate files. Create two folders, one containing good micrographs (e.g GOOD_MICS/
) and one contain bad classes (e.g BAD_MICS/
). Both folders can contain subfolders.
Then specify the paths into a config file like this:
{ "model": { "input_size": [512,512] }, "train": { "batch_size": 6, "good_path": "GOOD_MICS/", "bad_path": "BAD_MICS/", "pretrained_weights": "", "saved_weights_name": "my_model.h5", "learning_rate": 1e-4, "nb_epoch": 100, "nb_early_stop": 15 } }
The fields have the following meaning:
The next step is to run the training:
sp_cinderella_train.py -c example_config.json --gpu 1
This will train a classification network on the GPU with ID=1. After the training finishes, you get a my_model.h5
file. This can then be used to classfiy micrographs into good / bad categories.