From 617cf313ccb1fe005db3f7d88dec04a04bd97cc2 Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Tue, 28 Nov 2017 10:19:23 +0000
Subject: [PATCH] Update Readme.md - fixed typo
---
README.md | 23 +++++++++++++++--------
1 files changed, 15 insertions(+), 8 deletions(-)
diff --git a/README.md b/README.md
index 36413cf..0ee4c05 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:
@@ -108,7 +113,7 @@
Just do `make` in the darknet directory.
Before make, you can set such options in the `Makefile`: [link](https://github.com/AlexeyAB/darknet/blob/9c1b9a2cf6363546c152251be578a21f3c3caec6/Makefile#L1)
-* `GPU=1` to build with CUDA to accelerate by using GPU (CUDA should be in `/use/local/cuda`)
+* `GPU=1` to build with CUDA to accelerate by using GPU (CUDA should be in `/usr/local/cuda`)
* `CUDNN=1` to build with cuDNN v5/v6 to accelerate training by using GPU (cuDNN should be in `/usr/local/cudnn`)
* `OPENCV=1` to build with OpenCV 3.x/2.4.x - allows to detect on video files and video streams from network cameras or web-cams
* `DEBUG=1` to bould debug version of Yolo
@@ -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
@@ -170,8 +173,8 @@
* `cusolver64_80.dll, curand64_80.dll, cudart64_80.dll, cublas64_80.dll` - 80 for CUDA 8.0 or your version, from C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0\bin
- * For OpenCV 3.0: `opencv_world320.dll` and `opencv_ffmpeg320_64.dll` from `C:\opencv_3.0\opencv\build\x64\vc14\bin`
- * For OpenCV 2.4.13: `opencv_core249.dll`, `opencv_highgui249.dll` and `opencv_ffmpeg249_64.dll` from `C:\opencv_2.4.9\opencv\build\x64\vc14\bin`
+ * For OpenCV 3.X: `opencv_world320.dll` and `opencv_ffmpeg320_64.dll` from `C:\opencv_3.0\opencv\build\x64\vc14\bin`
+ * For OpenCV 2.4.13: `opencv_core2413.dll`, `opencv_highgui2413.dll` and `opencv_ffmpeg2413_64.dll` from `C:\opencv_2.4.13\opencv\build\x64\vc14\bin`
## How to train (Pascal VOC Data):
@@ -213,9 +216,11 @@
* change line batch to [`batch=64`](https://github.com/AlexeyAB/darknet/blob/master/build/darknet/x64/yolo-voc.2.0.cfg#L2)
* change line subdivisions to [`subdivisions=8`](https://github.com/AlexeyAB/darknet/blob/master/build/darknet/x64/yolo-voc.2.0.cfg#L3)
* change line `classes=20` to your number of objects
- * change line #237 from [`filters=125`](https://github.com/AlexeyAB/darknet/blob/master/cfg/yolo-voc.2.0.cfg#L224) to `filters=(classes + 5)*5` (generally this depends on the `num` and `coords`, i.e. equal to `(classes + coords + 1)*num`)
+ * change line #237 from [`filters=125`](https://github.com/AlexeyAB/darknet/blob/master/cfg/yolo-voc.2.0.cfg#L224) to: filters=(classes + 5)*5, so if `classes=2` then should be `filter=35`
+
+ (Generally `filters` depends on the `classes`, `num` and `coords`, i.e. equal to `(classes + coords + 1)*num`)
- For example, for 2 objects, your file `yolo-obj.cfg` should differ from `yolo-voc.2.0.cfg` in such lines:
+ So for example, for 2 objects, your file `yolo-obj.cfg` should differ from `yolo-voc.2.0.cfg` in such lines:
```
[convolutional]
@@ -320,6 +325,8 @@
+How to calculate **mAP** [voc_eval.py](https://github.com/AlexeyAB/darknet/blob/master/scripts/voc_eval.py) or [datascience.stackexchange link](https://datascience.stackexchange.com/questions/16797/what-does-the-notation-map-5-95-mean)
+
### Custom object detection:
Example of custom object detection: `darknet.exe detector test data/obj.data yolo-obj.cfg yolo-obj_8000.weights`
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