python opencv读取网络图片_image.open(bytesio(response.content)) timeout

pil

方法二，使用PIL+requests：
 
import requests
from PIL import Image
from io import BytesIO
 
response = requests.get(img_src)
image = Image.open(BytesIO(response.content))
image.save('D:/9.jpg')

 
import time
 
import cv2
import numpy as np
import requests
 
path='d:/guo.jpg'
 
# img=cv2.imread(path)
# x = img.tobytes()
# # 从二进制文件到图片(numpy.ndarray):
#
# aaa=np.fromstring(x, np.uint8)
# img = cv2.imdecode(aaa ,cv2.IMREAD_COLOR)
#
# cv2.imshow("1",img)
# cv2.waitKeyEx()
# import cv2   # opencv-python (3.4.2.16)
# import numpy as np  # numpy (1.14.5)
 
 
#每一张图片需要600ms
for i in range(10):
    start=time.time()
    file = requests.get("https://www.baidu.com/img/bd_logo1.png")
    img = cv2.imdecode(np.fromstring(file.content, np.uint8), 1)    #file.content 是读取的远程文件的字节流
    print('time',time.time()-start)
cv2.imshow("1",img)
cv2.waitKeyEx()
 
 
#需要1000ms左右
for i in range(10):
    start=time.time()
    # file = requests.get("https://www.baidu.com/img/bd_logo1.png")
    url = 'http://i5.qhimg.com/t019c3e49c9c9319c33.jpg'
    url = 'https://www.baidu.com/img/bd_logo1.png'
    cap = cv2.VideoCapture(url)
    ret = cap.isOpened()
    while (ret):
        ret, img = cap.read()
        if not ret: break
    # img = cv2.imdecode(np.fromstring(file.content, np.uint8), 1)    #file.content 是读取的远程文件的字节流
    print('time',time.time()-start)
cv2.imshow('photo', img)
cv2.waitKey(0)

c++读取：

https://answers.opencv.org/question/91344/load-image-from-url/

#include "curl/curl.h" // has to go before opencv headers
 
#include <iostream>
#include <vector>
using namespace std;
 
#include <opencv2/opencv.hpp>
using namespace cv;
 
//curl writefunction to be passed as a parameter
// we can't ever expect to get the whole image in one piece,
// every router / hub is entitled to fragment it into parts
// (like 1-8k at a time),
// so insert the part at the end of our stream.
size_t write_data(char *ptr, size_t size, size_t nmemb, void *userdata)
{
    vector<uchar> *stream = (vector<uchar>*)userdata;
    size_t count = size * nmemb;
    stream->insert(stream->end(), ptr, ptr + count);
    return count;
}
 
//function to retrieve the image as cv::Mat data type
cv::Mat curlImg(const char *img_url, int timeout=10)
{
    vector<uchar> stream;
    CURL *curl = curl_easy_init();
    curl_easy_setopt(curl, CURLOPT_URL, img_url); //the img url
    curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, write_data); // pass the writefunction
    curl_easy_setopt(curl, CURLOPT_WRITEDATA, &stream); // pass the stream ptr to the writefunction
    curl_easy_setopt(curl, CURLOPT_TIMEOUT, timeout); // timeout if curl_easy hangs, 
    CURLcode res = curl_easy_perform(curl); // start curl
    curl_easy_cleanup(curl); // cleanup
    return imdecode(stream, -1); // 'keep-as-is'
}
 
int main(void)
{
    Mat image = curlImg("http://www.cars.co.za/images/pictures/general/graphic_sellyourcar.png");
    if (image.empty())
        return -1; // load fail
 
    namedWindow( "Image output", CV_WINDOW_AUTOSIZE );
    imshow("Image output",image); // here's your car ;)
    waitKey(0); // infinite
}