在python中裁剪一个视频

问题描述 投票:0回答:1

我想创建一个函数,它可以裁剪某一帧的视频,并将其保存在我的磁盘上(OpenCV,moviepy,或类似的东西)。

我指定我的函数的参数是结束帧以及源和目标名称(位置)。

def vid_crop(src,dest,l,t,r,b):
  # something
  # goes
  # here

left = 1    #any number (pixels)
top = 2     # ''''
right = 3   # ''''
bottom = 4  # ''''

vid_crop('myvideo.mp4','myvideo_edit.mp4',left,top,right,bottom)

任何建议和想法都非常有用

python opencv video-processing video-capture moviepy
1个回答
1
投票

好吧,我想你想要这个。

import numpy as np
import cv2

# Open the video
cap = cv2.VideoCapture('vid.mp4')

# Initialize frame counter
cnt = 0

# Some characteristics from the original video
w_frame, h_frame = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
fps, frames = cap.get(cv2.CAP_PROP_FPS), cap.get(cv2.CAP_PROP_FRAME_COUNT)

# Here you can define your croping values
x,y,h,w = 0,0,100,100

# output
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('result.avi', fourcc, fps, (w, h))


# Now we start
while(cap.isOpened()):
    ret, frame = cap.read()

    cnt += 1 # Counting frames

    # Avoid problems when video finish
    if ret==True:
        # Croping the frame
        crop_frame = frame[y:y+h, x:x+w]

        # Percentage
        xx = cnt *100/frames
        print(int(xx),'%')

        # Saving from the desired frames
        #if 15 <= cnt <= 90:
        #    out.write(crop_frame)

        # I see the answer now. Here you save all the video
        out.write(crop_frame)

        # Just to see the video in real time          
        cv2.imshow('frame',frame)
        cv2.imshow('croped',crop_frame)

        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    else:
        break


cap.release()
out.release()
cv2.destroyAllWindows()

0
投票

搜索投资回报率在 opencv:将(0,0)视为图像的左上角,从左到右为x方向,从上到下为y方向。如果我们有(x1,y1)作为左上角,(x2,y2)作为ROI的右下角顶点,我们可以使用Numpy slicing来裁剪图像。

ROI = image[y1:y2, x1:x2]

这是对你有用的链接。链接

请看这个python示例代码。

# Python 2/3 compatibility
from __future__ import print_function
# Allows use of print like a function in Python 2.x

# Import OpenCV and Numpy modules
import numpy as np
import cv2


try:
    # Create a named window to display video output
    cv2.namedWindow('Watermark', cv2.WINDOW_NORMAL)
    # Load logo image
    dog = cv2.imread('Intel_Logo.png')
    # 
    rows,cols,channels = dog.shape
    # Convert the logo to grayscale
    dog_gray = cv2.cvtColor(dog,cv2.COLOR_BGR2GRAY)
    # Create a mask of the logo and its inverse mask
    ret, mask = cv2.threshold(dog_gray, 10, 255, cv2.THRESH_BINARY)
    mask_inv = cv2.bitwise_not(mask)
    # Now just extract the logo
    dog_fg = cv2.bitwise_and(dog,dog,mask = mask)
    # Initialize Default Video Web Camera for capture.
    webcam = cv2.VideoCapture(0)
    # Check if Camera initialized correctly
    success = webcam.isOpened()
    if success == False:
        print('Error: Camera could not be opened')
    else:
        print('Sucess: Grabbing the camera')
        webcam.set(cv2.CAP_PROP_FPS,30);
        webcam.set(cv2.CAP_PROP_FRAME_WIDTH,1024);
        webcam.set(cv2.CAP_PROP_FRAME_HEIGHT,768);

    while(True):
        # Read each frame in video stream
        ret, frame = webcam.read()
        # Perform operations on the video frames here
        # To put logo on top-left corner, create a Region of Interest (ROI)
        roi = frame[0:rows, 0:cols ] 
        # Now blackout the area of logo in ROI
        frm_bg = cv2.bitwise_and(roi,roi,mask = mask_inv)
        # Next add the logo to each video frame
        dst = cv2.add(frm_bg,dog_fg)
        frame[0:rows, 0:cols ] = dst
        # Overlay Text on the video frame with Exit instructions
        font = cv2.FONT_HERSHEY_SIMPLEX
        cv2.putText(frame, "Type q to Quit:",(50,700), font, 1,(255,255,255),2,cv2.LINE_AA)
        # Display the resulting frame
        # Display the resulting frame
        cv2.imshow('Watermark',frame)
        # Wait for exit key "q" to quit
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

    # Release all resources used
    webcam.release()
    cv2.destroyAllWindows()

except cv2.error as e:
    print('Please correct OpenCV Error')
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