From be9ccb7d7f4135a41910e6401fbe0c604f1a4080 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Thu, 01 Mar 2018 21:09:52 +0000
Subject: [PATCH] Added F1 score to accuracy statistic

---
 README.md |    6 ++++--
 1 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 7b4e8c8..7e3fd65 100644
--- a/README.md
+++ b/README.md
@@ -31,7 +31,7 @@
 This repository supports:
 
 * both Windows and Linux
-* both OpenCV 3.x and OpenCV 2.4.13
+* both OpenCV 2.x.x and OpenCV <= 3.4.0 (3.4.1 and higher isn't supported)
 * both cuDNN v5-v7
 * CUDA >= 7.5
 * also create SO-library on Linux and DLL-library on Windows
@@ -39,7 +39,7 @@
 ##### Requires: 
 * **Linux GCC>=4.9 or Windows 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 9.1**: https://developer.nvidia.com/cuda-downloads
-* **OpenCV 3.x**: https://sourceforge.net/projects/opencvlibrary/files/opencv-win/3.2.0/opencv-3.2.0-vc14.exe/download
+* **OpenCV 3.4.0**: https://sourceforge.net/projects/opencvlibrary/files/opencv-win/3.4.0/opencv-3.4.0-vc14_vc15.exe/download
 * **or OpenCV 2.4.13**: https://sourceforge.net/projects/opencvlibrary/files/opencv-win/2.4.13/opencv-2.4.13.2-vc14.exe/download
   - OpenCV allows to show image or video detection in the window and store result to file that specified in command line `-out_filename res.avi`
 * **GPU with CC >= 2.0** if you use CUDA, or **GPU CC >= 3.0** if you use cuDNN + CUDA: https://en.wikipedia.org/wiki/CUDA#GPUs_supported
@@ -372,6 +372,8 @@
   
   * desirable that your training dataset include images with objects at diffrent: scales, rotations, lightings, from different sides
 
+  * desirable that your training dataset include images with objects (without labels) that you do not want to detect - negative samples
+
   * for training on small objects, add the parameter `small_object=1` in the last layer [region] in your cfg-file
 
   * 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

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