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--- cryolo_train_general_model [2019/04/19 16:49]
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+++ cryolo_train_general_model [2019/04/19 16:51]
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 Training a model for a specific dataset is very easy with crYOLO. However, you might have multiple data collections of the same particle with different settings, a different camera or another microscope. A model trained on the data of one data collection, might not perform very good on a dataset from another data collection.
-However, you can easily train a crYOLO model that **generalize** well on data recorded under multiple conditions. To achieve this, all you have to do is to **merge training data** of multiple datasets. The result will be a model that be applied to new dataset from a new data collection without additional training.
+However, you can easily train a crYOLO model that **generalize** well on data recorded under multiple conditions. To achieve this, all you have to do is to **merge training data** of multiple datasets. The result will be a model that can be applied to a new dataset from a new data collection without additional training.
 Here is our recommendation how to organize the training data. Instead of copying your images and box files directly into ''train_images'' / ''train_annot'', you can copy them into subfolders. One for each data collection: