From 329e47b5d64f52a6d899c70401e2629b705078f2 Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Sat, 31 Dec 2016 13:02:06 +0000
Subject: [PATCH] Update Readme.md - Pareto frontier mAP-FPS

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 README.md |   10 +++++++++-
 1 files changed, 9 insertions(+), 1 deletions(-)

diff --git a/README.md b/README.md
index 794829b..c597f27 100644
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-![Darknet Logo](http://pjreddie.com/media/files/darknet-black-small.png)
+|  ![Darknet Logo](http://pjreddie.com/media/files/darknet-black-small.png) | &nbsp; ![map_fps](https://cloud.githubusercontent.com/assets/4096485/21550284/88f81b8a-ce09-11e6-9516-8c3dd35dfaa7.jpg) https://arxiv.org/abs/1612.08242 |
+|---|---|
+
 
 # Yolo-Windows v2
 # "You Only Look Once: Unified, Real-Time Object Detection (version 2)"
@@ -196,3 +198,9 @@
 
 8. Start training by using the command line: `darknet.exe detector train data/obj.data yolo-obj.cfg darknet19_448.conv.23`
 
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+## How to mark bounded boxes of objects and create annotation files:
+
+Here you can find repository with GUI-software for marking bounded boxes of objects and generating annotation files for Yolo v2: https://github.com/AlexeyAB/Yolo_mark
+
+With example of: `train.txt`, `obj.names`, `obj.data`, `yolo-obj.cfg`, `air`1-6`.txt`, `bird`1-4`.txt` for 2 classes of objects (air, bird) and `train_obj.cmd` with example how to train this image-set with Yolo v2

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