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Alexey
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@ -372,6 +372,8 @@ Example of custom object detection: `darknet.exe detector test data/obj.data yol
* desirable that your training dataset include images with objects at diffrent: scales, rotations, lightings, from different sides
* desirable that your training dataset include images with objects (without bounded boxes) that you do not want to detect - negative samples
* for training on small objects, add the parameter `small_object=1` in the last layer [region] in your cfg-file
* for training with a large number of objects in each image, add the parameter `max=200` or higher value in the last layer [region] in your cfg-file