我需要在 opencv 中将 base-64 字符串转换为 Mat 格式，
需要将图像从 java 发送到 C++(opencv 代码)。
在 C++ 中:
使用以下链接将 mat 编码为字符串流并将字符串流解码为 c++(opencv) 中的 mat:OpenCV cv::Mat to std::ifstream for base64 encoding -效果很好。
但是当我使用 java 中的 base64 字符串，将其转换为字符串流并用于解码时，发生运行时错误(bad-alloc-error)
为了检查从java传递给c++的base64字符串是否相同，我使用了在线工具(http://codebeautify.org/base64-to-image-converter)。图像保持不变，所以我认为从java传递给c++的base64字符串确实如此不改变。
在 Java 中:
在java中，base64字符串使用字节数组转换为图像。
在 C++ 中:
尝试在c++中解码字节数组。但它也会在运行时导致相同的错误。
我想知道是否有任何其他方法可以将 base64 字符串转换为 c++(opencv) 中的 mat(image) 或我在上述方法中尝试过的任何其他改进。
Base64 字符串:
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
最佳答案
您需要在解码后的字符串上使用 imdecode。
看看这段代码(base64 解码来自 here ):
#include <opencv2\opencv.hpp>
#include <vector>
#include <string>
using namespace std;
using namespace cv;
// Code from: http://www.adp-gmbh.ch/cpp/common/base64.html
static const std::string base64_chars =
"ABCDEFGHIJKLMNOPQRSTUVWXYZ"
"abcdefghijklmnopqrstuvwxyz"
"0123456789+/";
static inline bool is_base64(unsigned char c) {
return (isalnum(c) || (c == '+') || (c == '/'));
}
std::string base64_decode(std::string const& encoded_string) {
int in_len = encoded_string.size();
int i = 0;
int j = 0;
int in_ = 0;
unsigned char char_array_4[4], char_array_3[3];
std::string ret;
while (in_len-- && (encoded_string[in_] != '=') && is_base64(encoded_string[in_])) {
char_array_4[i++] = encoded_string[in_]; in_++;
if (i == 4) {
for (i = 0; i < 4; i++)
char_array_4[i] = base64_chars.find(char_array_4[i]);
char_array_3[0] = (char_array_4[0] << 2) + ((char_array_4[1] & 0x30) >> 4);
char_array_3[1] = ((char_array_4[1] & 0xf) << 4) + ((char_array_4[2] & 0x3c) >> 2);
char_array_3[2] = ((char_array_4[2] & 0x3) << 6) + char_array_4[3];
for (i = 0; (i < 3); i++)
ret += char_array_3[i];
i = 0;
}
}
if (i) {
for (j = i; j < 4; j++)
char_array_4[j] = 0;
for (j = 0; j < 4; j++)
char_array_4[j] = base64_chars.find(char_array_4[j]);
char_array_3[0] = (char_array_4[0] << 2) + ((char_array_4[1] & 0x30) >> 4);
char_array_3[1] = ((char_array_4[1] & 0xf) << 4) + ((char_array_4[2] & 0x3c) >> 2);
char_array_3[2] = ((char_array_4[2] & 0x3) << 6) + char_array_4[3];
for (j = 0; (j < i - 1); j++) ret += char_array_3[j];
}
return ret;
}
int main()
{
string encoded_string = "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";
string decoded_string = base64_decode(encoded_string);
vector<uchar> data(decoded_string.begin(), decoded_string.end());
Mat img = imdecode(data, IMREAD_UNCHANGED);
imshow("Image", img);
waitKey();
return 0;
}
关于java - 将Base64(字符串或字节数组)转换为c++(opencv)中的mat(图像)，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/32264709/
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我有一个字符串input="maybe(thisis|thatwas)some((nice|ugly)(day|night)|(strange(weather|time)))"Ruby中解析该字符串的最佳方法是什么？我的意思是脚本应该能够像这样构建句子:maybethisissomeuglynightmaybethatwassomenicenightmaybethiswassomestrangetime等等，你明白了......我应该一个字符一个字符地读取字符串并构建一个带有堆栈的状态机来存储括号值以供以后计算，还是有更好的方法？也许为此目的准备了一个开箱即用的库？
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