From 3a33d00d22ef55247fe379b8e6c53850f43a32a8 Mon Sep 17 00:00:00 2001 From: Alexey Date: Wed, 20 Jun 2018 01:29:59 +0300 Subject: [PATCH] Update Readme.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index b40d531d..d43d7974 100644 --- a/README.md +++ b/README.md @@ -422,14 +422,14 @@ 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, on different backgrounds - you should preferably have 2000 images for each class or more - * desirable that your training dataset include images with non-labeled objects that you do not want to detect - negative samples without bounded box (empty `.txt` files) + * desirable that your training dataset include images with non-labeled objects that you do not want to detect - negative samples without bounded box (empty `.txt` files) - use as many images of negative samples as there are images with objects * 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 * for training for small objects - set `layers = -1, 11` instead of https://github.com/AlexeyAB/darknet/blob/6390a5a2ab61a0bdf6f1a9a6b4a739c16b36e0d7/cfg/yolov3.cfg#L720 and set `stride=4` instead of https://github.com/AlexeyAB/darknet/blob/6390a5a2ab61a0bdf6f1a9a6b4a739c16b36e0d7/cfg/yolov3.cfg#L717 - * General rule - your training dataset should include such a set of relative sizes of objects that you want to detect - differing by no more than 2 times: + * General rule - your training dataset should include such a set of relative sizes of objects that you want to detect: * `train_network_width * train_obj_width / train_image_width ~= detection_network_width * detection_obj_width / detection_image_width` * `train_network_height * train_obj_height / train_image_height ~= detection_network_height * detection_obj_height / detection_image_height`