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OpenCV-Python-Tutorial安装详情

程序员文章站 2022-05-02 23:45:57
ch01-关于OpenCV opencv坐标系 ch02-安装OpenCV 安装 opencv-python 安装 opencv-contrib-python Windows安装P...

ch01-关于OpenCV opencv坐标系 ch02-安装OpenCV 安装 opencv-python 安装 opencv-contrib-python Windows安装Python版 编译安装 ch03-相关教程及视频 视频 ch04-图片 ch05-视频 VideoCapturepy VideoPlaypy VideoWriterpy two_camerapy ch06-绘图函数 drawpy draw_opencv_logopy Drawing_UTF-8_stringspy 画圆圈py ch07-把鼠标当画笔 draw_circle_rectanglepy MouseCallbackpy 鼠标左右键回调函数py ch08-用滑动条做调色板 createTrackbarpy Trackbar_drawpy ch09-图像的基础操作 img_roipy itemsetpy MakeBorderpy shapepy split_colorpy

ch01-关于OpenCV

opencv坐标系

关于图像坐标系与行列宽高的对应关系大致如下:

row == height == Point.y col == width == Point.x

区分开矩阵 行列；图像x，y

图像x,y： 类似数学中的x,y坐标轴，x对应水平方向，y对应竖直方向，注意图像的原点在左上角，x表示图像的宽度变化（对应矩阵的列变化），y表示图像的高度变化（对应矩阵的行变化）
因此有： col == width == Point.x ；row == height == Point.y

图像坐标体系中的零点坐标为图片的左上角，X轴为图像矩形的上面那条水平线；Y轴为图像矩形左边的那条垂直线。

如果要获取图像坐标轴(x,y)对应的像素值
1、image.at(y, x) image为Mat
2、Point(x, y)
3、image[x,y] image为对应图像的矩阵

图像的通道数时n，则使用Mat::at(y, x)时，其y的范围依旧是0到image的height，而x的取值范围则是0到image的width乘以n，因为这个时候是有n个通道，所以每个像素需要占有n列。但是如果在同样的情况下，使用Mat::at(point)来访问的话，则这时候可以不用考虑通道的个数，因为你要赋值给获取Mat::at(point)的值时，都不是一个数字，而是一个对应的n维向量。

矩阵行列: 将图像转成对应的矩阵对应的格式[h,w,c]，其中h为矩阵的行数对应图像的高度，w为矩阵的列数对应图像的宽度，c为图像的通道数

# -*- coding: utf-8 -*-
# @Time    : 2017/7/28 23:13
# @Author  : play4fun
# @File    : OpenCV图像坐标系_test.py
# @Software: PyCharm

"""
OpenCV图像坐标系_test.py:
"""

# TODO


import numpy as np
import cv2

img = cv2.imread('../data/Lenna.png', cv2.IMREAD_UNCHANGED)
print('img.shape:', img.shape)
logo = cv2.imread('../data/opencv_logo.png', cv2.IMREAD_UNCHANGED)
logo = cv2.resize(logo, (20, 20))
print('logo.shape:', logo.shape)
butterfly= cv2.imread('../data/butterfly.jpg', cv2.IMREAD_UNCHANGED)
butterfly = cv2.resize(butterfly, (20, 20))
print('butterfly.shape:', butterfly.shape)


cv2.imshow('src', img)
cv2.moveWindow('src', 0, 0)

# read color values at position y, x
y = 100
x = 50
(b, g, r) = img[y, x]
# print color values to screen
print('bgr:',b,g,r)

#先行后列
#img[y:y+height,x:width]
img[100:100 + logo.shape[0], 300:300 + logo.shape[1]] = logo[:, :, 0:3]# 两张图片的shape不一样
# img[10:10+logo.shape[0],30:30+logo.shape[1],:]=logo[:,:,0:3]
img[300:300 + logo.shape[1], 100:100 + logo.shape[0]] = butterfly[:, :, 0:3]


font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img, text='col=width=X0,row=height-Y0', org=(0, 0), fontFace=font, fontScale=0.5, color=(0, 255, 0), thickness=2,bottomLeftOrigin=True)  # text,
cv2.putText(img, text='col=width=X10,row=height-Y30', org=(10, 30), fontFace=font, fontScale=0.5, color=(0, 255, 0), thickness=2)  # text,
cv2.putText(img, text='col=width=X100,row=height-Y300', org=(100, 300), fontFace=font, fontScale=0.5, color=(0, 255, 0), thickness=2)  # text,
cv2.putText(img, text='col=width-X300,row=height-Y100', org=(300, 100), fontFace=font, fontScale=0.5, color=(0, 255, 0), thickness=2)  # text,

cv2.imshow('img+logo', img)
cv2.imwrite('img_logo.jpg',img)
cv2.moveWindow('img+logo', x=img.shape[0], y=0)
cv2.waitKey(0)

ch02-安装OpenCV

安装 opencv-python

virtualenv -p python3 .cv2 source .cv2/bin/activate pip install opencv-python pip install matplotlib 验证 python -c “import cv2;print(cv2.version,cv2.doc,cv2.file)”

安装 opencv-contrib-python

强烈建议先卸载opencv-python

pip uninstall opencv-python pip install opencv-contrib-python 验证 python -c “import cv2;print(cv2.version,cv2.doc,cv2.file)” 验证 python -c “import cv2;print(print(help(cv2.CascadeClassifier)))”

Windows安装Python版

进入https://www.lfd.uci.edu/~gohlke/pythonlibs下载
opencv_python?3.3.1+contrib?cp36?cp36m?win_amd64.whl (包含contrib模块)

打开cmd 切换到文件路径
pip install opencv_python?3.3.1+contrib?cp36?cp36m?win_amd64.whl

ch04-图片

# -*- coding: utf-8 -*-

import numpy as np
import cv2

print(cv2.__version__)


# img = cv2.imread('messi5.jpg',cv2.IMREAD_COLOR)#读入一副彩色图像。图像的透明度会被忽略   默认参数。
# img = cv2.imread('messi5.jpg', cv2.IMREAD_GRAYSCALE)# Load an color image in grayscale 灰度
img = cv2.imread('messi5.jpg',cv2.IMREAD_UNCHANGED)#包括图像的 alpha 通道

img = cv2.resize(img, (640, 480))

# img.I
# AttributeError: 'numpy.ndarray' object has no attribute 'I'

#
rows,cols,ch=img.shape
print('行/高:',rows,'列/宽:',cols,'通道:',ch)
#图像的宽对应的是列数, 高对应的是行数。

cv2.namedWindow('image', cv2.WINDOW_NORMAL)#可以调整窗口大小
# cv2.namedWindow('image', cv2.WINDOW_AUTOSIZE)#自动调整
# cv2.namedWindow('image', cv2.WINDOW_KEEPRATIO)#保持图片比例

# cv2.resizeWindow('image', 200, 200)  # 不起作用？

cv2.imshow('image', img)#窗口会自动调整为图像大小
# 按任意键退出
cv2.waitKey(0)#返回按键的 ASCII 码值

cv2.destroyAllWindows()

#
# cv2.imwrite('messigray.png', img)

ch05-视频

VideoCapture.py

# -*- coding: utf-8 -*-
"""
Created on Fri Jan 3 21:06:22 2014

@author: duan
 """
'''
 注意 当你的程序报错时 你 先检查的是你的摄像头是否能够在其他程 序中正常工作 比如 linux 下的 Cheese 。
'''

import numpy as np
import cv2

cap = cv2.VideoCapture(0)  # 一般的笔 本电脑 有内置摄像头。所以参数就是 0。你可以  设置成 1 或 者其他的来 择别的摄像头

'''
你可以使用函数 cap.get(propId) 来获得  的一些参数信息。   
propId 可以是 0 到 18 之 的任何整数。

其中的一些值可以使用 cap.set(propId,value) 来修改 value 就是 你想  置成的新值。
例如 我可以使用 cap.get(3) cv2.CAP_PROP_FRAME_WIDTH和 cap.get(4) cv2.CAP_PROP_FRAME_HEIGHT来查看每一帧的宽和高。   
默认情况下得到的值是 640X480。但是我可以使用 ret=cap.set(3,320) 和 ret=cap.set(4,240) 来把宽和高改成 320X240。
'''
# ret=cap.set(3,320)
# ret=cap.set(4,240)

# ret = cap.set(cv2.CAP_PROP_FRAME_WIDTH, 480)#避免计算量过大
# ret = cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 270)#
#等比缩放
frame_height = cap.get(cv2.CAP_PROP_FRAME_HEIGHT)#4 ，720
frame_width = cap.get(cv2.CAP_PROP_FRAME_WIDTH)#3   ，1280
frame_height=int(480/frame_width*frame_height)#270
ret = cap.set(cv2.CAP_PROP_FRAME_HEIGHT, frame_height)#高
ret = cap.set(cv2.CAP_PROP_FRAME_WIDTH, 480)



# while (True):
while cap.isOpened():  # 检查是否成功初始化，否则就 使用函数 cap.open()
    # Capture frame-by-frame
    ret, frame = cap.read()  # ret 返回一个布尔值 True/False
    # print('frame shape:',frame.shape)#(720, 1280, 3)

    frame = cv2.flip(frame, flipCode=1)  # 左右翻转,使用笔记本电脑摄像头才有用。
    # flipCode：翻转方向：1：水平翻转；0：垂直翻转；-1：水平垂直翻转

    # Our operations on the frame come here
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # Display the resulting frame
    cv2.imshow('frame', gray)
    cv2.setWindowTitle('frame', 'COLOR_BGR2GRAY')

    # Property=cv2.getWindowProperty('frame',0)#无用

    # if cv2.waitKey(1) & 0xFF == ord('q'):#不行
    #     break
    key = cv2.waitKey(delay=10)
    if key == ord("q"):
        break

# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()

VideoPlay.py

import numpy as np
import cv2

cap = cv2.VideoCapture('../data/vtest.avi')
# cap = cv2.VideoCapture('output.avi')
# cap = cv2.VideoCapture('Minions_banana.mp4')


# 帧率
fps = cap.get(cv2.CAP_PROP_FPS)  # 25.0
print("Frames per second using video.get(cv2.CAP_PROP_FPS) : {0}".format(fps))
# 总共有多少帧
num_frames = cap.get(cv2.CAP_PROP_FRAME_COUNT)
print('共有', num_frames, '帧')
#
frame_height = cap.get(cv2.CAP_PROP_FRAME_HEIGHT) # cap.get(3)
frame_width = cap.get(cv2.CAP_PROP_FRAME_WIDTH) # cap.get(4)
print('高：', frame_height, '宽：', frame_width)

FRAME_NOW = cap.get(cv2.CAP_PROP_POS_FRAMES)  # 第0帧
print('当前帧数', FRAME_NOW)  # 当前帧数 0.0

# 读取指定帧,对视频文件才有效，对摄像头无效？？
frame_no = 121
cap.set(1, frame_no)  # Where frame_no is the frame you want
ret, frame = cap.read()  # Read the frame
cv2.imshow('frame_no'+str(frame_no), frame)

FRAME_NOW = cap.get(cv2.CAP_PROP_POS_FRAMES)
print('当前帧数', FRAME_NOW)  # 当前帧数 122.0

while cap.isOpened():
    ret, frame = cap.read()
    FRAME_NOW = cap.get(cv2.CAP_PROP_POS_FRAMES)  # 当前帧数
    print('当前帧数', FRAME_NOW)

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    cv2.imshow('frame', gray)
    key = cv2.waitKey(1)
    if key == ord("q"):
        break

cap.release()
cv2.destroyAllWindows()

VideoWriter.py

import numpy as np
import cv2

cap = cv2.VideoCapture(0)
width = 640
ret = cap.set(3, width)
height = 480
ret = cap.set(4, height)

# Define the codec and create VideoWriter object
fourcc = cv2.VideoWriter_fourcc(*'XVID')  # opencv 3.0
# Error: 'module' object has no attribute 'VideoWriter_fourcc'
# fourcc=cv2.VideoWriter_fourcc('X', 'V', 'I', 'D')
#jpeg,h263,'m', 'p', '4', 'v'

#
out = cv2.VideoWriter('output.avi', fourcc, 20.0, (width, height))

while cap.isOpened():
    ret, frame = cap.read()
    if ret is True:

        frame = cv2.resize(frame, (640, 480))

        # write the flipped frame
        out.write(frame)

        cv2.imshow('frame', frame)

    else:
        break

    key = cv2.waitKey(1)
    if key == ord("q"):
        break

# Release everything if job is finished
cap.release()
out.release()
cv2.destroyAllWindows()

two_camera.py

# -*- coding: utf-8 -*-
# @Time    : 2017/8/15 00:19
# @Author  : play4fun
# @File    : two_camera.py
# @Software: PyCharm

"""
two_camera.py:
"""

import cv2
import numpy as np

cap0 = cv2.VideoCapture(0)
cap1 = cv2.VideoCapture(1)
ret = cap0.set(3, 320)
ret = cap0.set(4, 240)
ret = cap1.set(3, 320)
ret = cap1.set(4, 240)

while cap0.isOpened() and cap1.isOpened():
    ret0, frame0 = cap0.read()
    ret1, frame1 = cap1.read()

    if ret0:
        cv2.imshow('frame0', frame0)
        cv2.setWindowTitle('frame0','On Top')
    if ret1:
        cv2.imshow('frame1', frame1)
        # cv2.moveWindow('frame1', x=frame0.shape[1], y=0)
        cv2.moveWindow('frame1', x=320, y=40)

    key = cv2.waitKey(delay=2)
    if key == ord("q"):
        break

# When everything done, release the capture
cap0.release()
cap1.release()
cv2.destroyAllWindows()

ch06-绘图函数

draw.py

# -*- coding: utf-8 -*-
import numpy as np
import cv2

'''
? img: 你想 绘制图形的 幅图像。
? color: 形状的颜色。以RGB为例  需要传入一个元组 例如 255,0,0 
   代表蓝色。对于灰度图只需要传入灰度值。
? thickness 线条的粗细。如果给一个闭合图形 置为 -1  那么这个图形
就会被填充。 默认值是 1.
? linetype 线条的类型， 8 连接，抗锯齿等。  默认情况是8 连接。cv2.LINE_AA
   为抗锯齿  这样看起来会非常平滑。

'''

# Create a black image
img = np.zeros((512, 512, 3), np.uint8)

# Draw a diagonal blue line with thickness of 5 px
cv2.line(img, pt1=(0, 0), pt2=(511, 511), color=(255, 0, 0), thickness=5)  # pt1, pt2, color, thickness=
# cv2.polylines() 可以 用来画很多条线。只需要把想 画的线放在一 个列表中， 将 列表传给函数就可以了。每条线 会被独立绘制。 这会比用 cv2.line() 一条一条的绘制 要快一些。
# cv2.polylines(img, pts, isClosed, color, thickness=None, lineType=None, shift=None)
cv2.arrowedLine(img,pt1=(21, 13), pt2=(151, 401), color=(255, 0, 0), thickness=5)

cv2.rectangle(img, (384, 0), (510, 128), (0, 255, 0), 3)

cv2.circle(img, center=(447, 63), radius=63, color=(0, 0, 255), thickness=-1)  # center, radius, color, thickness=None

# 一个参数是中心点的位置坐标。 下一个参数是长轴和短轴的长度。椭圆沿逆时针方向旋转的角度。
# 椭圆弧演顺时针方向起始的角度和结束角度 如果是 0 很 360 就是整个椭圆
cv2.ellipse(img, center=(256, 256), axes=(100, 50), angle=0, startAngle=0, endAngle=180, color=255,
            thickness=-1)  # center, axes, angle, startAngle, endAngle, color, thickness=

pts = np.array([[10, 5], [20, 30], [70, 20], [50, 10]], np.int32)
pts = pts.reshape((-1, 1, 2))
# 这里 reshape 的第一个参数为-1, 表明这一维的长度是根据后面的维度的计算出来的。
# 注意 如果第三个参数是 False 我们得到的多边形是不闭合的 ，首 尾不相  连 。

font = cv2.FONT_HERSHEY_SIMPLEX
#org :Bottom-left corner of the text string in the image.左下角
#或使用 bottomLeftOrigin=True,文字会上下颠倒
cv2.putText(img, text='bottomLeftOrigin', org=(10, 400), fontFace=font, fontScale=1, color=(255, 255, 255), thickness=1,bottomLeftOrigin=True)#text, org, fontFace, fontScale, color, thickness=
cv2.putText(img, text='OpenCV', org=(10, 500), fontFace=font, fontScale=4, color=(255, 255, 255), thickness=2)#text, org, fontFace, fontScale, color, thickness=

# 所有的绘图函数的返回值都是 None ，所以不能使用 img = cv2.line(img,(0,0),(5

winname = 'example'
cv2.namedWindow(winname, 0)
cv2.imshow(winname, img)

cv2.imwrite("example.png", img)

cv2.waitKey(0)
cv2.destroyAllWindows()

draw_opencv_logo.py

# -*- coding: utf-8 -*-
# @Time    : 2017/7/11 下午7:07
# @Author  : play4fun
# @File    : draw_opencv_logo.py
# @Software: PyCharm

"""
draw_opencv_logo.py:Try to create the logo of OpenCV using drawing functions available in OpenCV.
"""

import numpy as np
import cv2  # 3.0.0-dev
import math

r1 = 70
r2 = 30

ang = 60

d = 170
h = int(d / 2 * math.sqrt(3))

dot_red = (256, 128)
dot_green = (int(dot_red[0] - d / 2), dot_red[1] + h)
dot_blue = (int(dot_red[0] + d / 2), dot_red[1] + h)

# tan = float(dot_red[0]-dot_green[0])/(dot_green[1]-dot_red[0])
# ang = math.atan(tan)/math.pi*180

red = (0, 0, 255)
green = (0, 255, 0)
blue = (255, 0, 0)
black = (0, 0, 0)

full = -1

img = np.zeros((512, 512, 3), np.uint8)
# img = np.ones((512, 512, 3), np.uint8)

cv2.circle(img, dot_red, r1, red, full)
cv2.circle(img, dot_green, r1, green, full)
cv2.circle(img, dot_blue, r1, blue, full)
cv2.circle(img, dot_red, r2, black, full)
cv2.circle(img, dot_green, r2, black, full)
cv2.circle(img, dot_blue, r2, black, full)

cv2.ellipse(img, dot_red, (r1, r1), ang, 0, ang, black, full)
cv2.ellipse(img, dot_green, (r1, r1), 360 - ang, 0, ang, black, full)
cv2.ellipse(img, dot_blue, (r1, r1), 360 - 2 * ang, ang, 0, black, full)

font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img, text='OpenCV', org=(15, 450), fontFace=font, fontScale=4, color=(255, 255, 255), thickness=10)#text,

cv2.imwrite("opencv_logo.png", img)
# cv2.imwrite("opencv_logo2.png", img)

Drawing_UTF-8_strings.py

# -*- coding: utf-8 -*-
# @Time    : 2017/7/23 下午9:11
# @Author  : play4fun
# @File    : Drawing_UTF-8_strings.py
# @Software: PyCharm

"""
Drawing_UTF-8_strings.py:

https://fireant.github.io/misc/2017/01/28/ttf-opencv.html
"""

import cv2
import numpy as np

img = np.zeros((100, 300, 3), dtype=np.uint8)

ft = cv2.freetype.createFreeType2()  # 需要安装freetype模块 cv2' has no attribute 'freetype'
# ft.loadFontData(fontFileName='Ubuntu-R.ttf',id=0)
# ft.loadFontData(fontFileName='/usr/share/fonts/truetype/freefont/FreeSans.ttf',id=0)#不支持中文
# ft.loadFontData(fontFileName='/usr/share/fonts-droid/truetype/DroidSansFallback.ttf',id=0)#树莓派,搞定

#sudo apt-get install ttf-wqy-zenhei  #安装字体
ft.loadFontData(fontFileName='/usr/share/fonts/truetype/wqy/wqy-zenhei.ttc', id=0)  # 文泉驿的开源中文字体


ft.putText(img=img,
           # text='Quick Fox',
           text='你好中文',
           org=(15, 70),
           fontHeight=60,
           color=(255, 255, 255),
           thickness=-1,
           line_type=cv2.LINE_AA,
           bottomLeftOrigin=True)

# cv2.imwrite('freetype.png', img)
cv2.imshow('freetype', img)
cv2.waitKey(0)

画圆圈.py

# -*- coding: utf-8 -*-
# @Time    : 2017/7/17 下午12:03
# @Author  : play4fun
# @File    : 画圆圈.py
# @Software: PyCharm

"""
画圆圈.py:随机覆盖，不同颜色，
"""
from time import sleep
import cv2
import numpy as np


def click_event(event, x, y, flags, param):
    '''
    用左键点击屏幕，打印坐标
    :param event:
    :param x:
    :param y:
    :param flags:
    :param param:
    :return:
    '''
    if event == cv2.EVENT_LBUTTONDOWN:
        print(x, y, flags, param)


cv2.namedWindow('Canvas', cv2.WINDOW_GUI_EXPANDED)
cv2.setMouseCallback("Canvas", click_event)

canvas = np.zeros((300, 300, 3), dtype="uint8")
while True:
    try:
        for i in range(0, 25):
            radius = np.random.randint(5, high=200)
            color = np.random.randint(0, high=256, size=(3,)).tolist()
            pt = np.random.randint(0, high=300, size=(2,))
            cv2.circle(canvas, tuple(pt), radius, color, -1)

        cv2.imshow("Canvas", canvas)

        key = cv2.waitKey(1000)  # 等待1秒
        if key == ord('q'):
            break
        else:
            # sleep(1)
            continue
    except KeyboardInterrupt as e:
        print('KeyboardInterrupt', e)
    finally:
        cv2.imwrite('random-circles2.jpg', canvas)

ch07-把鼠标当画笔

draw_circle_rectangle.py

# -*- coding: utf-8 -*-
import cv2
import numpy as np

# 当鼠标按下时变为 True
drawing = False
# 如果 mode 为 true 绘制矩形。按下'm' 变成绘制曲线。 mode=True
ix, iy = -1, -1


# 创建回调函数    #回调函数包含两部分 一部分画矩形 一部分画圆圈
def draw_circle(event, x, y, flags, param):
    global ix, iy, drawing, mode
    # 当按下左键是返回起始位置坐标
    if event == cv2.EVENT_LBUTTONDOWN:
        drawing = True
        ix, iy = x, y
    # 当鼠标左键按下并移动是绘制图形。event 可以查看移动,flag 查看是否按下
    elif event == cv2.EVENT_MOUSEMOVE and flags == cv2.EVENT_FLAG_LBUTTON:
        if drawing is True:
            if mode is True:
                cv2.rectangle(img, (ix, iy), (x, y), (0, 255, 0), -1)
            else:
                # 绘制圆圈,小圆点连在一起就成了线,3 代表了笔画的粗细
                cv2.circle(img, (x, y), 3, (0, 0, 255), -1)
                # 下面注释掉的代码是起始点为圆心,起点到终点为半径的
                # r = int(np.sqrt((x - ix) ** 2 + (y - iy) ** 2))
                # cv2.circle(img, (x, y), r, (0, 0, 255), -1)

    elif event == cv2.EVENT_LBUTTONUP:  # 当鼠标松开停止绘画。
        drawing = False
        # if mode == True:
        #     cv2.rectangle(img, (ix, iy), (x, y), (0, 255, 0), -1)
        # else:
        #     cv2.circle(img, (x, y), 5, (0, 0, 255), -1)


#
img = np.zeros((512, 512, 3), np.uint8)
mode = False

cv2.namedWindow('image', 0)
cv2.setMouseCallback('image', draw_circle)
while True:
    cv2.imshow('image', img)
    k = cv2.waitKey(1)  # & 0xFF
    if k == ord('m'):
        mode = not mode
    elif k == ord("q"):
        break

MouseCallback.py

# -*- coding: utf-8 -*-
import cv2
import numpy as np


# mouse callback function


def draw_circle(event, x, y, flags, param):  # 只用做一件事:在双击过的地方绘 制一个圆圈。
    if event == cv2.EVENT_LBUTTONDBLCLK:
        cv2.circle(img, (x, y), 100, (255, 0, 0), -1)


# 创建图像与窗口并将窗口与回调函数绑定
img = np.zeros((512, 512, 3), np.uint8)
cv2.namedWindow('image', cv2.WINDOW_NORMAL)

cv2.setMouseCallback('image', draw_circle)

while True:
    cv2.imshow('image', img)
    # if cv2.waitKey(20) & 0xFF == 27:
    #     break
    key = cv2.waitKey(1)
    if key == ord("q"):
        break
cv2.destroyAllWindows()

鼠标左右键回调函数.py

# -*- coding: utf-8 -*-
# @Time    : 2017/7/17 下午6:19
# @Author  : play4fun
# @File    : 鼠标左右键回调函数.py
# @Software: PyCharm

"""
鼠标左右键回调函数.py:
"""

import cv2


def click_event(event, x, y, flags, param):
    if event == cv2.EVENT_LBUTTONDOWN:
        print(x, y)

    if event == cv2.EVENT_RBUTTONDOWN:
        red = img[y, x, 2]
        blue = img[y, x, 0]
        green = img[y, x, 1]
        print(red, green, blue)

        strRGB = str(red) + "," + str(green) + "," + str(blue)
        font = cv2.FONT_HERSHEY_SIMPLEX
        cv2.putText(img, strRGB, (x, y), font, 1, (255, 255, 255), 2)
        cv2.imshow('original', img)


img = cv2.imread('../data/messi5.jpg')
cv2.imshow('original', img)

cv2.setMouseCallback("original", click_event)
cv2.waitKey(0)
cv2.imwrite('putText.jpg',img)

cv2.destroyAllWindows()

ch08-用滑动条做调色板

createTrackbar.py

# -*- coding: utf-8 -*-

import cv2
import numpy as np


def nothing(x):
    pass


# Create a black image, a window
img = np.zeros((300, 512, 3), np.uint8)
cv2.namedWindow('image', cv2.WINDOW_NORMAL)

# create trackbars for color change
cv2.createTrackbar('R', 'image', 0, 255, nothing)
cv2.createTrackbar('G', 'image', 0, 255, nothing)
cv2.createTrackbar('B', 'image', 0, 255, nothing)

# create switch for ON/OFF functionality
switch = '0 : OFF \n1 : ON'
cv2.createTrackbar(switch, 'image', 0, 1, nothing)
# 只有当 转换按钮 指向 ON 时 滑动条的滑动才有用，否则窗户 都是黑的。

while True:

    # get current positions of four trackbars
    r = cv2.getTrackbarPos('R', 'image')
    g = cv2.getTrackbarPos('G', 'image')
    b = cv2.getTrackbarPos('B', 'image')
    s = cv2.getTrackbarPos(switch, 'image')  # 另外一个重要应用就是用作转换按钮

    if s == 0:
        img[:] = 0
    else:
        img[:] = [b, g, r]

    cv2.imshow('image', img)
    k = cv2.waitKey(1)  # & 0xFF
    if k == ord("q"):
        break

cv2.destroyAllWindows()

Trackbar_draw.py

# -*- coding: utf-8 -*-
import cv2
import numpy as np


def nothing(x):
    pass


# 当鼠标按下时变为 True
drawing = False
# 如果 mode 为 true 绘制矩形。按下'm' 变成绘制曲线。 mode=True
ix, iy = -1, -1

'''
cv2.getTrackbarPos() 函数的第一个参数是滑动条的名字 
第二个参数 是滑动条被放置窗口的名字 
第三个参数是滑动条的默认位置。
第四个参数是滑动条的最大值 
第五个函数是回调函数， 每次滑动条的滑动都会调用回调函 数。
回调函数通常都会含有一个默认参数 就是滑动条的位置
'''


# 创建回调函数
def draw_circle(event, x, y, flags, param):
    r = cv2.getTrackbarPos('R', 'image')
    g = cv2.getTrackbarPos('G', 'image')
    b = cv2.getTrackbarPos('B', 'image')
    color = (b, g, r)

    global ix, iy, drawing, mode
    # 当按下左键是返回起始位置坐标
    if event == cv2.EVENT_LBUTTONDOWN:
        drawing = True
        ix, iy = x, y
    # 当鼠标左键按下并移动是绘制图形。event 可以查看移动,flag 查看是否按下
    elif event == cv2.EVENT_MOUSEMOVE and flags == cv2.EVENT_FLAG_LBUTTON:
        if drawing is True:
            if mode is True:
                cv2.rectangle(img, (ix, iy), (x, y), color, -1)
            else:
                # 绘制圆圈,小圆点连在一起就成了线,3 代表了笔画的粗细
                cv2.circle(img, (x, y), 3, color, -1)
                # 下面注释掉的代码是起始点为圆心,起点到终点为半径的
                # r=int(np.sqrt((x-ix)**2+(y-iy)**2))
                # cv2.circle(img,(x,y),r,(0,0,255),-1)

                # 当鼠标松开停止绘画。
    elif event == cv2.EVENT_LBUTTONUP:
        drawing = False
        # if mode==True:
        #     cv2.rectangle(img,(ix,iy),(x,y),(0,255,0),-1)
        # else:
        #     cv2.circle(img,(x,y),5,(0,0,255),-1)


img = np.zeros((512, 512, 3), np.uint8)
mode = False

cv2.namedWindow('image')
cv2.createTrackbar('R', 'image', 0, 255, nothing)
cv2.createTrackbar('G', 'image', 0, 255, nothing)
cv2.createTrackbar('B', 'image', 0, 255, nothing)
cv2.setMouseCallback('image', draw_circle)

while True:
    cv2.imshow('image', img)
    k = cv2.waitKey(1)  # & 0xFF
    if k == ord('m'):
        mode = not mode
    elif k == ord("q"):
        break

ch09-图像的基础操作

9.img_roi.py

# -*- coding: utf-8 -*-
import cv2
import numpy as np

'''
例如我们 检测一副图像中 眼睛的位置 我们 先应该在图像中找到脸 再在脸的区域中找眼睛 
而不是 直接在一幅图像中搜索。这样会提高程序的准确性和性能。
'''

img=cv2.imread('../data/messi5.jpg')

ball=img[280:340,330:390]
img[273:333,100:160]=ball #修改像素值



cv2.namedWindow("messi",0)
cv2.imshow("messi",img)
cv2.waitKey(0)

9.itemset.py

# -*- coding: utf-8 -*-
import cv2
import numpy as np

img = cv2.imread('../data/messi5.jpg')

#
px = img[100, 100]
print(px)
blue = img[100, 100, 0]
print(blue)

#
img[100, 100] = [255, 255, 255]
print(img[100, 100])

# 获取像素值及修改的更好方法。
print(img.item(10, 10, 2))
img.itemset((10, 10, 2), 100)
print(img.item(10, 10, 2))

9.MakeBorder.py

# -*- coding: utf-8 -*-

import cv2
import numpy as np
from matplotlib import pyplot as plt

# 为图像扩边，填充
#如果你想在图像周围创建一个边框，就像相框一样
# 经常在卷积运算或 0 填充时被用到。

BLUE = [255, 0, 0]

img1 = cv2.imread('../data/opencv_logo.png')

replicate = cv2.copyMakeBorder(img1, top=10, bottom=10, left=10, right=10, borderType=cv2.BORDER_REPLICATE)

reflect = cv2.copyMakeBorder(img1, 10, 10, 10, 10, cv2.BORDER_REFLECT)
reflect101 = cv2.copyMakeBorder(img1, 10, 10, 10, 10, cv2.BORDER_REFLECT_101)
wrap = cv2.copyMakeBorder(img1, 10, 10, 10, 10, cv2.BORDER_WRAP)

constant = cv2.copyMakeBorder(img1, 10, 10, 10, 10, cv2.BORDER_CONSTANT, value=BLUE)  # value 边界颜色

plt.subplot(231), plt.imshow(img1, 'gray'), plt.title('ORIGINAL')
plt.subplot(232), plt.imshow(replicate, 'gray'), plt.title('REPLICATE')
plt.subplot(233), plt.imshow(reflect, 'gray'), plt.title('REFLECT')
plt.subplot(234), plt.imshow(reflect101, 'gray'), plt.title('REFLECT_101')
plt.subplot(235), plt.imshow(wrap, 'gray'), plt.title('WRAP')
plt.subplot(236), plt.imshow(constant, 'gray'), plt.title('CONSTANT')

plt.show()

9.shape.py

# -*- coding: utf-8 -*-
import cv2
import numpy as np

img = cv2.imread('../data/messi5.jpg', 0)  # gray
print(img.shape)

img = cv2.imread('../data/messi5.jpg')
# print(img.shape)
rows, cols, ch = img.shape
print('行/高:', rows, '列/宽:', cols, '通道:', ch)

print(img.size)
print(img.dtype)#uint8
#注意 在   debug 时 img.dtype非常重要。因为在 OpenCV- Python 代码中经常出现数据类型的不一致。

9.split_color.py

# -*- coding: utf-8 -*-
import cv2
import numpy as np
#拆分及合并图像通道

img=cv2.imread('../data/messi5.jpg')

#
b,g,r=cv2.split(img)#比较耗时的操作，请使用numpy 索引
img=cv2.merge(b,g,r)

#
b=img[:,:,0]

#使所有像素的红色通道值都为 0,你不必先拆分再赋值。
# 你可以 直接使用 Numpy 索引,这会更快。
img[:,:,2]=0

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