使用 OpenCV
从网络摄像头保存操作视频
原文:https://www . geesforgeks . org/saving-operated-video-from-a-network-use-opencv/
OpenCV 是一个庞大的库，有助于为图像和视频操作提供各种功能。有了 OpenCV，我们可以对输入的视频进行操作。OpenCV 还允许我们保存操作过的视频，以便进一步使用。为了保存图像，我们使用 cv2.imwrite()将图像保存到指定的文件位置。但是，为了保存录制的视频，我们创建了一个视频编写器对象。
首先，我们指定 fourcc 变量。FourCC 是用于指定视频编解码器的 4 字节代码。代码列表可通过 Forcc 在视频编解码器获取。Windows 的编解码器是 DIVX ，OSX 的编解码器是 avc1，h263。FourCC 代码作为 cv2 传递。video writer _ fourcc(*“MJPG”)为 MJPG，为 cv2。video writer _ fourcc(*“XVID”)代表 DIVX。
然后， cv2。使用了 VideoWriter() 功能。
cv2.VideoWriter( filename, fourcc, fps, frameSize )
这些参数是:
- 文件名:指定输出视频文件的名称。
- fourcc: (用于录制)定义编解码器
- fps: 输出视频流的定义帧速率
- 帧大小:视频帧的大小
# Python program to illustrate
# saving an operated video
# organize imports
import numpy as np
import cv2
# This will return video from the first webcam on your computer.
cap = cv2.VideoCapture(0)
# Define the codec and create VideoWriter object
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('output.avi', fourcc, 20.0, (640, 480))
# loop runs if capturing has been initialized.
while(True):
# reads frames from a camera
# ret checks return at each frame
ret, frame = cap.read()
# Converts to HSV color space, OCV reads colors as BGR
# frame is converted to hsv
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# output the frame
out.write(hsv)
# The original input frame is shown in the window
cv2.imshow('Original', frame)
# The window showing the operated video stream
cv2.imshow('frame', hsv)
# Wait for 'a' key to stop the program
if cv2.waitKey(1) & 0xFF == ord('a'):
break
# Close the window / Release webcam
cap.release()
# After we release our webcam, we also release the output
out.release()
# De-allocate any associated memory usage
cv2.destroyAllWindows()
输出:
输出屏幕显示两个窗口。名为“原始”的窗口显示输入帧，而“帧”窗口显示操作的视频序列。
此外，视频以“输出”的名称记录并保存在具有预定义帧速率和帧大小的同一文件位置。
一般是. avi 格式，保存的视频是这样的:输出视频
输入视频也可以在其他颜色空间操作，如灰度
# Python program to illustrate
# saving an operated video
# organize imports
import numpy as np
import cv2
# This will return video from the first webcam on your computer.
cap = cv2.VideoCapture(0)
# Define the codec and create VideoWriter object
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('output.avi', fourcc, 20.0, (640, 480))
# loop runs if capturing has been initialized.
while(True):
# reads frames from a camera
# ret checks return at each frame
ret, frame = cap.read()
# Converts to grayscale space, OCV reads colors as BGR
# frame is converted to gray
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# output the frame
out.write(gray)
# The original input frame is shown in the window
cv2.imshow('Original', frame)
# The window showing the operated video stream
cv2.imshow('frame', gray)
# Wait for 'a' key to stop the program
if cv2.waitKey(1) & 0xFF == ord('a'):
break
# Close the window / Release webcam
cap.release()
# After we release our webcam, we also release the out-out.release()
# De-allocate any associated memory usage
cv2.destroyAllWindows()
输出:
该操作视频的视频文件保存在我们上面看到的相同文件位置。
这种方法可以帮助我们创建自己的数据集，用于项目/模型中的训练数据，从网络摄像头进行记录并进行必要的操作，还可以在不同的颜色空间中创建视频。
不同颜色空间的可视化内容请参考此链接: https://www . geeksforgeeks . org/python-可视化-不同颜色空间的图像/
参考文献:
- https://docs.opencv.org/3.4/dd/d9e/classcv_1_1VideoWriter.html
- https://docs.opencv.org/3.1.0/dd/d43/tutorial_py_video_display.html
- https://en.wikipedia.org/wiki/FourCC
- https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_colorspaces/py_colorspaces.html
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