Camera Relay

在树莓派上安装USB Camera，通过GPIO口控制设备电源，在电源上点一定时间后，对设备进行拍照。

Ctrl+c停止程序运行。

一、参考文档：

• Getting Webcam Images with Python and OpenCV 2 (For Real This Time)
• Python time to String
• Python的命令行参数解析
• RPi 2B GPIO 测试
• RPi 2B python opencv camera demo example
• python使用matplotlib:subplot绘制多个子图
• 直方图计算
• Python+OpenCV学习（5）---直方图
• How-To: 3 Ways to Compare Histograms using OpenCV and Python
• How to Display a Matplotlib RGB Image

二、USAGE

2.1 Help

usage: CameraRelay.py [-h] -on ON -off OFF -cap CAP

Camera Control Relay.

optional arguments:
  -h, --help  show this help message and exit
  -on ON      Power On Duty(s)
  -off OFF    Power Off Duty(s)
  -cap CAP    Camera Capture Image Delay After Power On(s)

Example: ./CameraRelay.py -on 4 -off 2 -cap 1

2.2 Example

./CameraRelay.py -on 4 -off 2 -cap 1 

• System Power On: 4(s)
• System Power Off: 2(s)
• USB Camera capture a image after Power On: 1(s)

2.3 CMD Output Example

root@raspberrypi:/home/pi/CameraRelay# ./CameraRelay.py -on 4 -off 2 -cap 1
Namespace(cap='1', off='2', on='4')
 powerOnTime: 4.0.
 powerOffTime: 2.0.
 cameraCaptureDelay: 1.0.

Program Is Running...
Type Ctrl+c to stop the program.
start power off: 20171022072547
over power off and start power on: 20171022072549
capture a image: 20171022072550
over power on: 20171022072553
Capture image count: 1
start power off: 20171022072553
over power off and start power on: 20171022072555
capture a image: 20171022072556
over power on: 20171022072559
Capture image count: 2
start power off: 20171022072559
over power off and start power on: 20171022072602
capture a image: 20171022072603
over power on: 20171022072606
Capture image count: 3

三、图像相似度处理

目前没有整合图片相似度对比，不过test/imgcompare.py中有Ubuntu版本的处理图片相似度源代码，可以用于参考整合功能。下图中，中间一行图最后一张，目前不知道为什么显示的时候偏蓝：

• 第一行图是表示test/tpl.jpg的直方图和图片；
• 第二行图是表示test/src.jpg的直方图和图片；
• 第三行图是表示，B、G、R对应的三个相似度和最后一个取B、G、R最小的相似度。

如下是GIMP图像处理软件对test/src.jpg、test/tpl.jpg显示的B、G、R直方图：

3.1 test/tpl.jpg直方图

和前面的Python输出的B、G、R直方图拟合度是一样的。

3.2 test/src.jpg直方图

和前面的Python输出的B、G、R直方图拟合度是一样的。

3.3 颜色偏蓝原因

OpenCV represents RGB images as multi-dimensional NumPy arrays…, but in reverse order! This means that images are actually represented in BGR order rather than RGB! There’s an easy fix though. All we need to do is convert the image from BGR to RGB:

plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))

3.4 显示颜色正常