From 97378e08b584aad83889370c7659d4c0e3766d2d Mon Sep 17 00:00:00 2001 From: Alexey <AlexeyAB@users.noreply.github.com> Date: Sun, 01 Apr 2018 11:04:38 +0000 Subject: [PATCH] Update Readme.md --- README.md | 9 ++++++--- 1 files changed, 6 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 343db79..26d0994 100644 --- a/README.md +++ b/README.md @@ -224,6 +224,7 @@ https://groups.google.com/d/msg/darknet/NbJqonJBTSY/Te5PfIpuCAAJ ## How to train (to detect your custom objects): +Training Yolo v3 1. Create file `yolo-obj.cfg` with the same content as in `yolov3.cfg` (or copy `yolov3.cfg` to `yolo-obj.cfg)` and: @@ -268,15 +269,17 @@ 4. Put image-files (.jpg) of your objects in the directory `build\darknet\x64\data\obj\` -5. Create `.txt`-file for each `.jpg`-image-file - in the same directory and with the same name, but with `.txt`-extension, and put to file: object number and object coordinates on this image, for each object in new line: `<object-class> <x> <y> <width> <height>` +5. You should label each object on images from your dataset. Use this visual GUI-software for marking bounded boxes of objects and generating annotation files for Yolo v2 & v3: https://github.com/AlexeyAB/Yolo_mark + +It will create `.txt`-file for each `.jpg`-image-file - in the same directory and with the same name, but with `.txt`-extension, and put to file: object number and object coordinates on this image, for each object in new line: `<object-class> <x> <y> <width> <height>` Where: * `<object-class>` - integer number of object from `0` to `(classes-1)` - * `<x> <y> <width> <height>` - float values relative to width and height of image, it can be equal from 0.0 to 1.0 + * `<x> <y> <width> <height>` - float values relative to width and height of image, it can be equal from (0.0 to 1.0] * for example: `<x> = <absolute_x> / <image_width>` or `<height> = <absolute_height> / <image_height>` * atention: `<x> <y>` - are center of rectangle (are not top-left corner) - For example for `img1.jpg` you should create `img1.txt` containing: + For example for `img1.jpg` you will be created `img1.txt` containing: ``` 1 0.716797 0.395833 0.216406 0.147222 -- Gitblit v1.10.0