沒有視頻輸出OpenCV蟒蛇

Question

我想將我的圖像上的代碼轉換爲視頻。我的程序獲取一幅畫面，作品出來的平均RGB各9 * 9窗口，並輸出圖像：

輸入圖像：

輸出圖像：

這裏是我的代碼具有圖像輸入/輸出：

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) 

當試圖使用上的視頻I得到的視頻輸出相同的代碼，但它爲空（0字節）。

下面是代碼：

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() 

謝謝您的閱讀:)

Answer 1

我想你的代碼。我必須改變的三件事：

• 輸出視頻的編解碼器。我改變它爲MP4，它的工作原理。
• 行out.write（frame）的縮進。
• 調整輸入框的大小，以確保它具有合適的尺寸。

這裏對我來說是什麼工作：

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()