From 2fa539779f4e12e264b9e1b2fc463ac7edec165c Mon Sep 17 00:00:00 2001 From: Alexey Date: Fri, 27 Sep 2019 22:35:56 +0300 Subject: [PATCH] Readme.md --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index 36019663..ca3c2d9f 100644 --- a/README.md +++ b/README.md @@ -540,6 +540,8 @@ Example of custom object detection: `darknet.exe detector test data/obj.data yol * 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 + * What is the best way to mark objects: label only the visible part of the object, or label the visible and overlapped part of the object, or label a little more than the entire object (with a little gap)? Mark as you like - how would you like it to be detected. + * for training with a large number of objects in each image, add the parameter `max=200` or higher value in the last `[yolo]`-layer or `[region]`-layer in your cfg-file (the global maximum number of objects that can be detected by YoloV3 is `0,0615234375*(width*height)` where are width and height are parameters from `[net]` section in cfg-file) * for training for small objects (smaller than 16x16 after the image is resized to 416x416) - set `layers = -1, 11` instead of https://github.com/AlexeyAB/darknet/blob/6390a5a2ab61a0bdf6f1a9a6b4a739c16b36e0d7/cfg/yolov3.cfg#L720