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@ -421,6 +421,9 @@ Example of custom object detection: `darknet.exe detector test data/obj.data yol
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* 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
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* 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
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* for training for small objects - set `layers = -1, 11` instead of https://github.com/AlexeyAB/darknet/blob/6390a5a2ab61a0bdf6f1a9a6b4a739c16b36e0d7/cfg/yolov3.cfg#L720
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and set `stride=4` instead of https://github.com/AlexeyAB/darknet/blob/6390a5a2ab61a0bdf6f1a9a6b4a739c16b36e0d7/cfg/yolov3.cfg#L717
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* General rule - you should keep relative size of objects in the Training and Testing datasets the same:
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* General rule - you should keep relative size of objects in the Training and Testing datasets the same:
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* `train_network_width * train_obj_width / train_image_width ~= detection_network_width * detection_obj_width / detection_image_width`
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* `train_network_width * train_obj_width / train_image_width ~= detection_network_width * detection_obj_width / detection_image_width`
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