From 49d39922e6c2f991bcc7f446bcde535b35d24a87 Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Thu, 02 Nov 2017 15:04:18 +0000
Subject: [PATCH] Update Readme.md
---
README.md | 11 +++++++----
1 files changed, 7 insertions(+), 4 deletions(-)
diff --git a/README.md b/README.md
index b79cd21..0b1c20d 100644
--- a/README.md
+++ b/README.md
@@ -1,5 +1,7 @@
# Yolo-v2 Windows and Linux version
+[](https://circleci.com/gh/AlexeyAB/darknet)
+
1. [How to use](#how-to-use)
2. [How to compile on Linux](#how-to-compile-on-linux)
3. [How to compile on Windows](#how-to-compile-on-windows)
@@ -87,6 +89,9 @@
* 194 MB VOC-model - WebCamera #0: `darknet.exe detector demo data/voc.data yolo-voc.cfg yolo-voc.weights -c 0`
* 186 MB Yolo9000 - image: `darknet.exe detector test cfg/combine9k.data yolo9000.cfg yolo9000.weights`
* 186 MB Yolo9000 - video: `darknet.exe detector demo cfg/combine9k.data yolo9000.cfg yolo9000.weights test.mp4`
+* To process a list of images `image_list.txt` and save results of detection to `result.txt` use:
+ `darknet.exe detector test data/voc.data yolo-voc.cfg yolo-voc.weights < image_list.txt > result.txt`
+ You can comment this line so that each image does not require pressing the button ESC: https://github.com/AlexeyAB/darknet/blob/6ccb41808caf753feea58ca9df79d6367dedc434/src/detector.c#L509
##### For using network video-camera mjpeg-stream with any Android smartphone:
@@ -132,9 +137,7 @@
4.2 (right click on project) -> properties -> Linker -> General -> Additional Library Directories: `C:\opencv_2.4.13\opencv\build\x64\vc14\lib`
-5. If you have other version of OpenCV 2.4.x (not 3.x) then you also should change lines like `#pragma comment(lib, "opencv_core2413.lib")` in the file `\src\detector.c`
-
-6. If you want to build with CUDNN to speed up then:
+5. If you want to build with CUDNN to speed up then:
* download and install **cuDNN 6.0 for CUDA 8.0**: https://developer.nvidia.com/cudnn
@@ -202,7 +205,7 @@
1. Train it first on 1 GPU for like 1000 iterations: `darknet.exe detector train data/voc.data yolo-voc.2.0.cfg darknet19_448.conv.23`
-2. Then stop and by using partially-trained model `/backup/yolo-voc_1000.weights` run training with multigpu (up to 4 GPUs): `darknet.exe detector train data/voc.data yolo-voc.2.0.cfg yolo-voc_1000.weights -gpus 0,1,2,3`
+2. Then stop and by using partially-trained model `/backup/yolo-voc_1000.weights` run training with multigpu (up to 4 GPUs): `darknet.exe detector train data/voc.data yolo-voc.2.0.cfg /backup/yolo-voc_1000.weights -gpus 0,1,2,3`
https://groups.google.com/d/msg/darknet/NbJqonJBTSY/Te5PfIpuCAAJ
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