1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
|
---
category: tool
tool: OpenCV
filename: learnopencv.py
contributors:
- ["Yogesh Ojha", "http://github.com/yogeshojha"]
translators:
- ["GengchenXU", "https://github.com/GengchenXU"]
lang: zh-cn
---
### Opencv
Opencv(开源计算机视觉)是一个编程功能库,主要面向实时计算机视觉。最初由英特尔开发,后来由Willow Garage,然后Itseez(后来被英特尔收购)支持。Opencv 目前支持多种语言,如C++、Python、Java 等
#### 安装
有关在计算机上安装 OpenCV,请参阅这些文章。
* Windows 安装说明: [https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_setup/py_setup_in_windows/py_setup_in_windows.html#install-opencv-python-in-windows]()
* Mac 安装说明 (High Sierra): [https://medium.com/@nuwanprabhath/installing-opencv-in-macos-high-sierra-for-python-3-89c79f0a246a]()
* Linux 安装说明 (Ubuntu 18.04): [https://www.pyimagesearch.com/2018/05/28/ubuntu-18-04-how-to-install-opencv]()
### 在这里,我们将专注于 OpenCV 的 python 实现
```python
# OpenCV读取图片
import cv2
img = cv2.imread('cat.jpg')
# 显示图片
# imshow() 函数被用来显示图片
cv2.imshow('Image',img)
# 第一个参数是窗口的标题,第二个参数是image
# 如果你得到错误,对象类型为None,你的图像路径可能是错误的。请重新检查图像包
cv2.waitKey(0)
# waitKey() 是一个键盘绑定函数,参数以毫秒为单位。对于GUI事件,必须使用waitKey()函数。
# 保存图片
cv2.imwrite('catgray.png',img)
# 第一个参数是文件名,第二个参数是图像
# 转换图像灰度
gray_image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 从摄像头捕捉视频
cap = cv2.VideoCapture(0)
#0 是你的相机,如果你有多台相机,你需要输入他们的id
while(True):
# 一帧一帧地获取
_, frame = cap.read()
cv2.imshow('Frame',frame)
# 当用户按下q ->退出
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# 相机必须释放
cap.release()
# 在文件中播放视频
cap = cv2.VideoCapture('movie.mp4')
while(cap.isOpened()):
_, frame = cap.read()
# 灰度播放视频
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
cv2.imshow('frame',gray)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
# 在OpenCV中画线
# cv2.line(img,(x,y),(x1,y1),(color->r,g,b->0 to 255),thickness)(注 color颜色rgb参数 thickness粗细)
cv2.line(img,(0,0),(511,511),(255,0,0),5)
# 画矩形
# cv2.rectangle(img,(x,y),(x1,y1),(color->r,g,b->0 to 255),thickness)
# 粗细= -1用于填充矩形
cv2.rectangle(img,(384,0),(510,128),(0,255,0),3)
# 画圆
cv2.circle(img,(xCenter,yCenter), radius, (color->r,g,b->0 to 255), thickness)
cv2.circle(img,(200,90), 100, (0,0,255), -1)
# 画椭圆
cv2.ellipse(img,(256,256),(100,50),0,0,180,255,-1)
# 在图像上增加文字
cv2.putText(img,"Hello World!!!", (x,y), cv2.FONT_HERSHEY_SIMPLEX, 2, 255)
# 合成图像
img1 = cv2.imread('cat.png')
img2 = cv2.imread('openCV.jpg')
dst = cv2.addWeighted(img1,0.5,img2,0.5,0)
# 阈值图像
# 二进制阈值
_,thresImg = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
# Adaptive Thresholding
adapThres = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY,11,2)
# 模糊的形象
# 高斯模糊
blur = cv2.GaussianBlur(img,(5,5),0)
# 模糊中值
medianBlur = cv2.medianBlur(img,5)
# Canny 边缘检测
img = cv2.imread('cat.jpg',0)
edges = cv2.Canny(img,100,200)
# 用Haar Cascades进行人脸检测
# 下载 Haar Cascades 在 https://github.com/opencv/opencv/blob/master/data/haarcascades/
import cv2
import numpy as np
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
img = cv2.imread('human.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
aces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x,y,w,h) in faces:
cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
roi_gray = gray[y:y+h, x:x+w]
roi_color = img[y:y+h, x:x+w]
eyes = eye_cascade.detectMultiScale(roi_gray)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
cv2.imshow('img',img)
cv2.waitKey(0)
cv2.destroyAllWindows()
# destroyAllWindows() destroys all windows.
# 如果您希望销毁特定窗口,请传递您创建的窗口的确切名称。
```
### 进一步阅读:
* Download Cascade from [https://github.com/opencv/opencv/blob/master/data/haarcascades]()
* OpenCV 绘图函数 [https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html]()
* 最新的语言参考 [https://opencv.org]()
* 更多的资源 [https://en.wikipedia.org/wiki/OpenCV]()
* 优秀的的 OpenCV 教程
* [https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html]()
* [https://realpython.com/python-opencv-color-spaces]()
* [https://pyimagesearch.com]()
* [https://www.learnopencv.com]()
|