没有视频输出 OpenCV Python

Question

我正在尝试将适用于图像的代码转换为视频。我的程序接收一张图片，计算出每个 9*9 窗口的平均 RGB 并输出一张图片：

输入图像：

输出图像：

这是我的代码，其中有一个图像作为输入/输出：

import numpy as np
import cv2

#Read in image
img = cv2.imread('images/0021.jpg')

scale = 9
#Get x and y components of image
y_len,x_len,_ = img.shape

mean_values = []
for y in range(scale):
    for x in range(scale):
        #Crop image 3*3 windows
        cropped_img=img[(y*y_len)/scale:((y+1)*y_len)/scale,
                          (x*x_len)/scale:((x+1)*x_len)/scale]

        mean_val=cv2.mean(cropped_img)
        mean_val=mean_val[:3]
        cropped_img[:,:,:] = mean_val

print img.shape     
cv2.imshow('mean_RGB',img)
cv2.waitKey(0)

当尝试在视频上使用相同的代码时，我得到一个视频输出，但它是空的（0 字节）。

代码如下：

import numpy as np
import cv2

cap = cv2.VideoCapture('videos/kondo2.avi')

fourcc = cv2.cv.CV_FOURCC(*'DIVX')
out = cv2.VideoWriter('videos/output.avi',fourcc, 15.0, (800,600),True)

while(cap.isOpened()):
    ret, frame = cap.read()
    if ret == True:
        y_len,x_len,_ = frame.shape
        scale = 9
        for y in range(scale):
            for x in range(scale):
                cropped_frame=frame[(y*y_len)/scale:((y+1)*y_len)/scale,
                                        (x*x_len)/scale:((x+1)*x_len)/scale]

                mean_val=cv2.mean(cropped_frame)
                mean_val=mean_val[:3]
                cropped_frame[:,:,:] = mean_val
                out.write(frame)

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

感谢您的阅读:)

Answer 1

我试过你的代码。我必须改变三件事：

• 输出视频的编解码器。我把它改成 mp4 就可以了。
• out.write(frame) 行的缩进。
• 调整输入帧的大小，以确保其大小合适。

这对我有用：

import numpy as np
import cv2

cap = cv2.VideoCapture('videos/kondo2.avi')
w=800
h=600

fourcc = cv2.cv.CV_FOURCC('m', 'p', '4', 'v')
out = cv2.VideoWriter('videos/output.avi',fourcc, 25, (w,h),True)
count = 0
while(cap.isOpened()):
    count = count + 1
    print "processing frame ", count
    ret, frame = cap.read()
    if ret == True:
        frame = cv2.resize(frame,(w,h), interpolation = cv2.INTER_CUBIC)
        y_len,x_len,_ = frame.shape

        scale = 9
        for y in range(scale):
            for x in range(scale):
                cropped_frame=frame[(y*y_len)/scale:((y+1)*y_len)/scale,
                                    (x*x_len)/scale:((x+1)*x_len)/scale]

                mean_val=cv2.mean(cropped_frame)
                mean_val=mean_val[:3]
                cropped_frame[:,:,:] = mean_val

        out.write(frame)


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