小编ved*_*ala的帖子

以下是在Ubuntu OS 16.04上使用GNU编译器(g ++命令)编译的示例代码:

#include<iostream>
#include<unistd.h>
#include<fcntl.h>
#include <errno.h>
int main()
{           char* pBuffer;          

            char* storedfilepath = "/home/rtpl/Desktop/ts.mp4";

            std::cout<<"\n Opening file at "<<storedfilepath<<"\n";

            int NumBytesToRead = 1000 ;
            int filedes = open(storedfilepath,O_RDONLY);

            std::cout<<"\n value of error is "<<errno<<"\n";

            std::cout<<"\n value of filedes is "<<filedes;

            if (filedes==0)
            std::cout<<"\n File cannot be opened";
            else
            {
            std::cout<<"\n File opened successfully";
            std::cout<<"\n Now reading file\n"; 

            }

            //if(
            int ret = read(filedes,pBuffer,NumBytesToRead);

            std::cout<<"\n value of error is "<<errno<<"\n";

            if(ret!= -1)
            std::cout<<"\n File read successfully";
            else …

我的目标是拾取图像，分离出灰度阈值低于本地数字（例如 3）的曲线/轮廓，然后在它们周围放置矩形，同时将其写回原始图像 - 作为检测的一种方式灰度图像上的裂纹。以下是我提出的 - 通过在线查看教程。

# import the necessary packages
import numpy as np
import cv2

# Load an color image in grayscale
img = cv2.imread('chest-ct-lungs.jpg',0)
ret,thresh = cv2.threshold(img,3,255,cv2.THRESH_BINARY_INV)

# Detect the contours in the image
image, contours =         
cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)

# Draw all the contours
all_contour_img = cv2.drawContours(image, contours, -1, (0,255,0), 3)
cv2.imwrite('all_contour_img.png',all_contour_img)

# Use bounding rectangles
x,y,w,h = cv2.boundingRect(contours)
cv2.rectangle(all_contour_img,(x,y),(x+w,y+h),(0,255,0),2)

# Draw over original image
imwrite(uint8(double(img)+all_contour_img), 'output.png');

但是，当我使用 python IDLE 运行它时，我将其作为输出：

Traceback (most recent call last):
  File "C:\Users\com\Desktop\python.py", …