没有视频输出OpenCV Python

时间:2015-03-03 09:09:26

标签: python opencv video image-processing computer-vision

我正在尝试将处理图片的代码转换为视频。我的程序接收一个图像,计算出每个9 * 9窗口的平均RGB并输出一个图像:

输入图片: Input Image

输出图片: Output Image

这是我的代码,它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,我得到视频输出,但它是空的(0字节)。

以下是代码:

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()

感谢您阅读:)

1 个答案:

答案 0 :(得分:1)

我尝试了你的代码。我必须改变三件事:

  • 输出视频的编解码器。我将它改为mp4并且有效。
  • 行out.write(frame)的缩进。
  • 调整输入框的大小,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()