[英]OpenCV/Python: read specific frame using VideoCapture
有没有办法使用VideoCapture()
方法获取特定帧?
我目前的代码是:
import numpy as np
import cv2
cap = cv2.VideoCapture('video.avi')
这是我的参考教程。
谢谢GPPK。
视频参数应以整数形式给出。 每个标志都有自己的值。 有关代码,请参见此处。
正确的解决方案是:
import numpy as np
import cv2
#Get video name from user
#Ginen video name must be in quotes, e.g. "pirkagia.avi" or "plaque.avi"
video_name = input("Please give the video name including its extension. E.g. \"pirkagia.avi\":\n")
#Open the video file
cap = cv2.VideoCapture(video_name)
#Set frame_no in range 0.0-1.0
#In this example we have a video of 30 seconds having 25 frames per seconds, thus we have 750 frames.
#The examined frame must get a value from 0 to 749.
#For more info about the video flags see here: https://stackoverflow.com/questions/11420748/setting-camera-parameters-in-opencv-python
#Here we select the last frame as frame sequence=749. In case you want to select other frame change value 749.
#BE CAREFUL! Each video has different time length and frame rate.
#So make sure that you have the right parameters for the right video!
time_length = 30.0
fps=25
frame_seq = 749
frame_no = (frame_seq /(time_length*fps))
#The first argument of cap.set(), number 2 defines that parameter for setting the frame selection.
#Number 2 defines flag CV_CAP_PROP_POS_FRAMES which is a 0-based index of the frame to be decoded/captured next.
#The second argument defines the frame number in range 0.0-1.0
cap.set(2,frame_no);
#Read the next frame from the video. If you set frame 749 above then the code will return the last frame.
ret, frame = cap.read()
#Set grayscale colorspace for the frame.
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#Cut the video extension to have the name of the video
my_video_name = video_name.split(".")[0]
#Display the resulting frame
cv2.imshow(my_video_name+' frame '+ str(frame_seq),gray)
#Set waitKey
cv2.waitKey()
#Store this frame to an image
cv2.imwrite(my_video_name+'_frame_'+str(frame_seq)+'.jpg',gray)
# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()
下面的代码可以做到这一点:
import cv2
cap = cv2.VideoCapture(videopath)
cap.set(cv2.CAP_PROP_POS_FRAMES, frame_number-1)
res, frame = cap.read()
frame_number
是一个整数,范围为 0 到视频中的帧数。
注意:你应该设置frame_number-1
来强制阅读frame_number
。 它没有很好地记录,但这就是 VideoCapture 模块的行为方式。
可以通过以下方式获得帧数:
amount_of_frames = cap.get(cv2.CAP_PROP_FRAME_COUNT)
如果您想要一个精确的帧,您可以将 VideoCapture 会话设置为该帧。 自动调用该帧要直观得多。 “正确”的解决方案要求您输入已知数据:如 fps、长度等。 使用下面的代码,您只需要知道您要调用的框架。
import numpy as np
import cv2
cap = cv2.VideoCapture(video_name) # video_name is the video being called
cap.set(1,frame_no) # Where frame_no is the frame you want
ret, frame = cap.read() # Read the frame
cv2.imshow('window_name', frame) # show frame on window
如果要按住窗口,直到按退出:
while True:
ch = 0xFF & cv2.waitKey(1) # Wait for a second
if ch == 27:
break
从 VideoCaptureProperties ( docs ) 的文档中可以看出,在 VideoCapture 中设置帧的方法是:
frame = 30
cap.set(cv2.CAP_PROP_POS_FRAMES, frame)
请注意,您不必传递给函数frame - 1
因为,正如文档所述,标志CAP_PROP_POS_FRAMES
表示“接下来要解码/捕获的帧的基于 0 的索引” 。
总结一个我想每秒读取一帧的完整示例是:
import cv2
cap = cv2.VideoCapture('video.avi')
# Get the frames per second
fps = cap.get(cv2.CAP_PROP_FPS)
# Get the total numer of frames in the video.
frame_count = cap.get(cv2.CAP_PROP_FRAME_COUNT)
frame_number = 0
cap.set(cv2.CAP_PROP_POS_FRAMES, frame_number) # optional
success, image = cap.read()
while success and frame_number <= frame_count:
# do stuff
frame_number += fps
cap.set(cv2.CAP_PROP_POS_FRAMES, frame_number)
success, image = cap.read()
在上面链接的文档中可以看到在 VideoCapture 中设置特定时间的方法是:
milliseconds = 1000
cap.set(cv2.CAP_PROP_POS_MSEC, milliseconds)
就像之前每秒读取一帧的完整示例一样,可以通过这种方式实现:
import cv2
cap = cv2.VideoCapture('video.avi')
# Get the frames per second
fps = cap.get(cv2.CAP_PROP_FPS)
# Get the total numer of frames in the video.
frame_count = cap.get(cv2.CAP_PROP_FRAME_COUNT)
# Calculate the duration of the video in seconds
duration = frame_count / fps
second = 0
cap.set(cv2.CAP_PROP_POS_MSEC, second * 1000) # optional
success, image = cap.read()
while success and second <= duration:
# do stuff
second += 1
cap.set(cv2.CAP_PROP_POS_MSEC, second * 1000)
success, image = cap.read()
例如,要开始阅读视频的第 15 帧,您可以使用:
frame = 15
cap.set(cv2.CAP_PROP_POS_FRAMES, frame-1)
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