前言

opencv是圖像處理的利器，內(nèi)置了許多圖像處理方法的庫，當(dāng)然也帶了人臉檢測等功能的庫及example，并且支持Intel深度學(xué)習(xí)推理引擎的計算加速。
通過查看opencv-3.4.1的更新日志，我們看到如果使用加速引擎，推理效率非常高（見https://github.com/opencv/opencv/wiki/ChangeLog#version341）：

opencv安裝

opencv源碼下載

我們選擇最新的opencv-3.4.1，下載：https://github.com/opencv/opencv/archive/3.4.1.zip
安裝方法參考：
https://docs.opencv.org/3.4.1/d7/d9f/tutorial_linux_install.html

依賴項及安裝

• 依賴項

Required Packages
GCC 4.4.x or later
CMake 2.8.7 or higher
Git
GTK+2.x or higher, including headers (libgtk2.0-dev)
pkg-config
Python 2.6 or later and Numpy 1.5 or later with developer packages (python-dev, python-numpy)
ffmpeg or libav development packages: libavcodec-dev, libavformat-dev, libswscale-dev
[optional] libtbb2 libtbb-dev
[optional] libdc1394 2.x
[optional] libjpeg-dev, libpng-dev, libtiff-dev, libjasper-dev, libdc1394-22-dev
[optional] CUDA Toolkit 6.5 or higher

• 安裝

[compiler] sudo apt-get install build-essential
[required] sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
[optional] sudo apt-get install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev

如果過程中有遇到網(wǎng)絡(luò)問題導(dǎo)致安裝失敗的，可以通過安裝命令后加 --fix-missing再次安裝，如sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev --fix-missing，若一直失敗，可以通過更改源的方式再次嘗試，如：

sudo -s
echo -e "deb http://mirrors.ustc.edu.cn/raspbian/raspbian/ stretch main contrib non-free rpi \n deb-src http://mirrors.ustc.edu.cn/raspbian/raspbian/ stretch main contrib non-free rpi" > /etc/apt/sources.list
echo -e "deb http://mirrors.ustc.edu.cn/archive.raspberrypi.org/ stretch main ui" > /etc/apt/sources.list.d/raspi.list
exit
sudo apt update && sudo apt -y upgrade

opencv編譯

• 解壓源碼包

unzip opencv-3.4.1.zip

• 創(chuàng)建build目錄及配置

cd opencv-3.4.1/
mkdir build
cd build
cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON ..

• 編譯

make

編譯過程大概4小時。

• 安裝

sudo make install

• 單元測試驗證

./bin/opencv_test_core

運行各個核心組件的單元測試程序，該測試是在google test框架下寫的，均顯示OK說明安裝成功，筆者這里遇到了一個Failure，原因是其中一個測試case需要有圖片輸入，因此和opencv的安裝無關(guān)，規(guī)避該錯誤需要拷貝任意.jpg和.png圖片各一張到build/bin/目錄下并重命名為lena.jpg和lena.png。
筆者遇到的錯誤：

/home/yinan/install/opencv/opencv-3.4.1/modules/core/test/test_io.cpp:562: Failure
Expected: (lenas.size()) > (pngLenas.size()), actual: 0 vs 0
[  FAILED  ] Core_globbing.accuracy (479 ms)

...

[----------] Global test environment tear-down
[==========] 10532 tests from 210 test cases ran. (724467 ms total)
[  PASSED  ] 10531 tests.
[  FAILED  ] 1 test, listed below:
[  FAILED  ] Core_globbing.accuracy

 1 FAILED TEST
  YOU HAVE 10 DISABLED TESTS

• 驗證python中引用opencv

yinan@raspberrypi:~ $ python
Python 2.7.13 (default, Nov 24 2017, 17:33:09)
[GCC 6.3.0 20170516] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import cv2
>>>

正常引用cv2無錯誤說明一切OK！

• 運行opencv獲取攝像頭數(shù)據(jù)，代碼：

#!/usr/bin/env python
import cv2

capture = cv2.VideoCapture(0)

while True:
    ret, frame = capture.read()
    print "frame.shape: {}".format(frame.shape)

    cv2.imshow("capture", frame)
    if cv2.waitKey(100) & 0xff == ord("q"):
        break

cv2.destroyAllWindows()

• 錯誤一

Traceback (most recent call last):
  File "video.py", line 13, in <module>
    print "frame.shape: {}".format(frame.shape)
AttributeError: 'NoneType' object has no attribute 'shape'

這是由于當(dāng)前用戶對/dev/video0沒有權(quán)限導(dǎo)致，運行命令
sudo chmod 666 /dev/video0

• 錯誤二

frame.shape: (480, 640, 3)
MobaXterm X11 proxy: Unsupported authorisation protocol

(capture:1404): Gtk-WARNING **: cannot open display: localhost:11.0

使用pi賬戶運行命令xhost +后重新登錄當(dāng)前賬戶

運行起來效果：

image.png