【OpenCV】处理文件、摄像头和图形用户界面

2018-6-25 北京 似是暴雨前
2.1 基本I/O脚本
2.1.2 图像与原始字节之间的转换

import cv2
import numpy
# import os

# 构建一个120,000随机字节的序列
# randomByteArray = bytearray(os.urandom(120000))
# flatNumpyArray = numpy.array(randomByteArray)


# 把这个序列转换成400*300的灰度级图像
# grayImage = flatNumpyArray.reshape(300, 400)
grayImage = numpy.random.randint(0, 256, 120000).reshape(300, 400)
cv2.imwrite('RandomGray.png', grayImage)

# 把这个序列转换成400*100的彩色图像
# bgrImage = flatNumpyArray.reshape((100, 400, 3))
bgrImage = numpy.random.randint(0, 256, 120000).reshape(100, 400, 3)
cv2.imwrite('RandomColor.png', bgrImage)

2018-6-27 天气真好啊～

2.1.3 使用numpy.array访问图像数据

import cv2
import numpy as np
img = cv2.imread('jx3qunxiang.jpg')

# 显示像素(150, 120)当前的B值
print(img.item(150, 120, 0))
img.itemset((150, 120, 0), 255)
print(img.item(150, 120, 0))

# 将R通道的所有值置为0
img[:, :, 2] = 0
cv2.imwrite('jx3qunxiang_no_red.jpg', img)

# 一块区域替换另一块同样大的区域
my_roi = img[0:100, 0:100]
img[150:250, 150:250] = my_roi
cv2.imwrite('jx3qunxiang_replace.jpg', img)

注意到，B、G、R三个通道的索引分别为0、1、2。

2.1.4 视频文件的读写

import cv2

videoCapture = cv2.VideoCapture('j3logo.avi')
fps = videoCapture.get(cv2.CAP_PROP_FPS)
size = (int(videoCapture.get(cv2.CAP_PROP_FRAME_WIDTH)), int(videoCapture.get(cv2.CAP_PROP_FRAME_HEIGHT)))
videoWriter = cv2.VideoWriter('j3logo_output.avi', cv2.VideoWriter_fourcc('F', 'L', 'V', '1'), fps, size)

success, frame = videoCapture.read()
print('Success value is %s' % success)
while success:
    # 循环到没有帧
    videoWriter.write(frame)
    success, frame = videoCapture.read()

注意，需要给VideoWriter()类的构造函数指定视频文件名、视频编解码器、帧速率和帧大小。
后两者可以通过videoCapture()类的get()函数得到。

2.1.5 捕获摄像头的帧

import cv2

# 与视频文件cv2.VideoCapture('j3logo.avi')相比
# 构造VideoCapture类是通过摄像头的设备索引---cv2.VideoCapture(0)---0是摄像头的device index
cameraCapture = cv2.VideoCapture(0)
fps = 30
size = (int(cameraCapture.get(cv2.CAP_PROP_FRAME_WIDTH)),
        int(cameraCapture.get(cv2.CAP_PROP_FRAME_HEIGHT)))
videoWriter = cv2.VideoWriter('MySelf.avi', cv2.VideoWriter_fourcc('I', '4', '2', '0'), fps, size)

success, frame = cameraCapture.read()
# print('Success value is %s' % success)
# VideoCapture类的get()方法不能返回摄像头帧速率的准确值，总是返回0
# 但是保存视频文件需要帧速率，需要针对摄像头创建合适的VideoWriter类
# 一种方法是对帧速率做出假设，如下方法
# 一种是使用计时器测量
numFramesRemaining = 10 * fps - 1
while success and numFramesRemaining > 0 :
    videoWriter.write(frame)
    success, frame = cameraCapture.read()
    # print(cameraCapture.isOpened())
    numFramesRemaining -= 1
cameraCapture.release()

2.1.6 在窗口显示图像

import cv2.

img = cv2.imread('jx3qunxiang.jpg')
cv2.imshow('MyPic', img)
cv2.waitKey()
# 释放所有由opencv创建的窗口
cv2.destroyAllWindows()

2.1.7 在窗口显示摄像头帧

import cv2

clicked = False
def onMouse(event, x, y, flags, param):
    global clicked
    if event == cv2.EVENT_LBUTTONUP:
        clicked = True

cameraCapture = cv2.VideoCapture(0)
cv2.namedWindow('MyWindow')
# 鼠标回调函数(鼠标事件相应)
cv2.setMouseCallback('MyWindow', onMouse)

print('Showing camera feed.Click window or press any key to stop.')

success, frame = cameraCapture.read()
# waitKey()中的参数是等待键盘触发的时间，单位是ms，返回值是-1代表没有键被按下
while success and cv2.waitKey(1) == -1 and not clicked:
    cv2.imshow('MyWindow', frame)
    success, frame = cameraCapture.read()

cv2.destroyWindow('MyWindow')
cameraCapture.release()