From a87abe8de58427f842b371c0169b4c41dc1cb6f1 Mon Sep 17 00:00:00 2001 From: Alexey <AlexeyAB@users.noreply.github.com> Date: Sun, 23 Apr 2017 22:52:45 +0000 Subject: [PATCH] Update Readme.md --- README.md | 6 ++++-- 1 files changed, 4 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index f833da9..225e883 100644 --- a/README.md +++ b/README.md @@ -26,7 +26,7 @@ More details: http://pjreddie.com/darknet/yolo/ ##### Requires: -* **MS Visual Studio 2015 (v140)**: https://www.microsoft.com/download/details.aspx?id=48146 +* **MS Visual Studio 2015 (v140)**: https://go.microsoft.com/fwlink/?LinkId=532606&clcid=0x409 (or offline [ISO image](https://go.microsoft.com/fwlink/?LinkId=615448&clcid=0x409)) * **CUDA 8.0 for Windows x64**: https://developer.nvidia.com/cuda-downloads * **OpenCV 2.4.9**: https://sourceforge.net/projects/opencvlibrary/files/opencv-win/2.4.9/opencv-2.4.9.exe/download - To compile without OpenCV - remove define OPENCV from: Visual Studio->Project->Properties->C/C++->Preprocessor @@ -192,7 +192,7 @@ * change line batch to [`batch=64`](https://github.com/AlexeyAB/darknet/blob/master/build/darknet/x64/yolo-voc.cfg#L3) * change line subdivisions to [`subdivisions=8`](https://github.com/AlexeyAB/darknet/blob/master/build/darknet/x64/yolo-voc.cfg#L4) * change line `classes=20` to your number of objects - * change line #224 from [`filters=125`](https://github.com/AlexeyAB/darknet/blob/master/cfg/yolo-voc.cfg#L224) to `filters=(classes + 5)*5` (generally this depends on the `num` and `coords`, i.e. equal to `(classes + coords + 1)*num`) + * change line #237 from [`filters=125`](https://github.com/AlexeyAB/darknet/blob/master/cfg/yolo-voc.cfg#L237) to `filters=(classes + 5)*5` (generally this depends on the `num` and `coords`, i.e. equal to `(classes + coords + 1)*num`) For example, for 2 objects, your file `yolo-obj.cfg` should differ from `yolo-voc.cfg` in such lines: @@ -306,6 +306,8 @@ 1. Before training: * set flag `random=1` in your `.cfg`-file - it will increase precision by training Yolo for different resolutions: [link](https://github.com/AlexeyAB/darknet/blob/47409529d0eb935fa7bafbe2b3484431117269f5/cfg/yolo-voc.cfg#L244) + + * desirable that your training dataset include images with objects at diffrent: scales, rotations, lightings, from different sides 2. After training - for detection: -- Gitblit v1.10.0