diff --git a/How to training your data on YOLO.md b/How to training your data on YOLO.md new file mode 100644 index 00000000..08172d56 --- /dev/null +++ b/How to training your data on YOLO.md @@ -0,0 +1,36 @@ +![Darknet Logo](http://pjreddie.com/media/files/darknet-black-small.png) + +#Darknet# +Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation. + +For more information see the [Darknet project website](http://pjreddie.com/darknet). + +For questions or issues please use the [Google Group](https://groups.google.com/forum/#!forum/darknet). + + +---------- + +#How to training your own data on YOLO# + +## **Steps:** ## +1. first, prepare your data, including images and lables. Note the image extension name and label format. + (1). The darknet support images: jpeg jpg. I had add some code to support other image format the same as OpenCV. Please see the [darknet pull 13](https://github.com/pjreddie/darknet/pull/13) or my github. + (2). The label must be unix format. If you generate labels in Windows, you can use dos2unix tools ion Ubuntu to convert the format. + (3). Please note the code in Data.c line 231: + + `char *labelpath = find_replace(path, "images", "images");` + + `labelpath = find_replace(labelpath, "JPEGImages", "labels");` + + + **the darknet will replace images to images in trainging data's txt file.** + +2. Change the train.txt file's path in tolo.c line 17 18 and line 147: + `char *train_images = "/data/voc/train.txt";` + + `char *backup_directory = "/home/pjreddie/backup/";` + + `list *plist = get_paths("/home/pjreddie/data/voc/2007_test.txt");` + + +