没有视频输出OpenCV蟒蛇

Question

我想将我的图像上的代码转换为视频。我的程序获取一幅画面，作品出来的平均RGB各9 * 9窗口，并输出图像：

输入图像：

输出图像：

这里是我的代码具有图像输入/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) 

当试图使用上的视频I得到的视频输出相同的代码，但它为空（0字节）。

下面是代码：

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() 

谢谢您的阅读:)

Answer 1

我想你的代码。我必须改变的三件事：

• 输出视频的编解码器。我改变它为MP4，它的工作原理。
• 行out.write（frame）的缩进。
• 调整输入框的大小，以确保它具有合适的尺寸。

这里对我来说是什么工作：

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()