基于 libdmtx和zxing的DM二維碼識別總結(jié)

• 1.基于libdmtx的DM二維碼識別
• • 1.1 python實現(xiàn)
  • 1.2 C++實現(xiàn)
• 2. 基于zxing的DM二維碼識別
• • 2.1 C++實現(xiàn)

1.基于libdmtx的DM二維碼識別

1.1 python實現(xiàn)

python識別DM二維碼比較簡單，只需要pylibdmtx 庫即可，pylibdmtx 庫包含了libdmtx的功能，python代碼如下。

# -*-coding:utf-8 -*- import time import cv2 from pylibdmtx import pylibdmtx # 加載圖片 image = cv2.imread('1.bmp') t0 = time.time() # 解析二維碼 all_barcode_info = pylibdmtx.decode(image, timeout=500, max_count=1) print(all_barcode_info) print(time.time() - t0) print(all_barcode_info[0].data.decode("utf-8"))

1.2 C++實現(xiàn)

用c++實現(xiàn)DM二維碼識別相對復(fù)雜，需要用到libdmtx.lib 和dmtx.h頭文件。編譯libdmtx.lib比較復(fù)雜，所以我很貼心的附上X86和X64環(huán)境下的libdmtx.lib、libdmtx.dll鏈接庫，以及dmtx.h。百度網(wǎng)盤鏈接為：https://pan.baidu.com/s/1e0DK7PiAFAIzLwempsNacg 提取碼：ckux

C++實現(xiàn)代碼如下：

#include <opencv2/opencv.hpp> #include <iostream> #include "dmtx.h"using namespace cv; using namespace std;int main() {DmtxMessage* msg;DmtxRegion* reg;Mat dst;double time = getTickCount();Mat src = imread("1.jpg");if (!src.data){cout << "Load image failed!" << endl;}cvtColor(src, src, COLOR_BGR2GRAY);DmtxImage* image;image = dmtxImageCreate(src.data, src.cols, src.rows, DmtxPack8bppK);//注意圖片類型DmtxDecode* dec = dmtxDecodeCreate(image, 1);//解碼reg = dmtxRegionFindNext(dec, NULL); //獲取二維碼位置，第二個參數(shù)表示掃描時間上限，達(dá)到時間上限退出掃描if (reg != NULL) {msg = dmtxDecodeMatrixRegion(dec, reg, 1);//解碼信息if (msg != NULL){cout << msg->output << endl;dmtxMessageDestroy(&msg);}dmtxRegionDestroy(&reg);}else{cout << "Get region failed!" << endl;}dmtxDecodeDestroy(&dec);dmtxImageDestroy(&image);time = (getTickCount() - time) / getTickFrequency();cout << "the processing time is :" << time << endl;cin.get();return 0; }

2. 基于zxing的DM二維碼識別

2.1 C++實現(xiàn)

zxing是一個比較知名的二維碼識別開源庫。直接抄作業(yè)吧，VS工程以及所有和zxing相關(guān)的依賴項均在此鏈接：
鏈接：https://pan.baidu.com/s/1_aQ-EqaQ4TZdEefO0AF9Qg
提取碼：o72j

#include "ReadBarcode.h" #include "TextUtfEncoding.h"#include <iostream> #include <cstring> #include <string> #include <algorithm> #include <cctype> #include<ctime>#define STB_IMAGE_IMPLEMENTATION #include "stb_image.h"using namespace ZXing;static void PrintUsage(const char* exePath) {std::cout << "Usage: " << exePath << " [-fast] [-norotate] [-format <FORMAT[,...]>] [-ispure] <png image path>\n"<< " -fast Skip some lines/pixels during detection (faster)\n"<< " -norotate Don't try rotated image during detection (faster)\n"<< " -format Only detect given format(s) (faster)\n"<< " -ispure Assume the image contains only a 'pure'/perfect code (faster)\n"<< "\n"<< "Supported formats are:\n";for (auto f : BarcodeFormats::all()) {std::cout << " " << ToString(f) << "\n";}std::cout << "Formats can be lowercase, with or without '-', separated by ',' and/or '|'\n"; }static bool ParseOptions(int argc, char* argv[], DecodeHints* hints, std::string* filePath) {for (int i = 1; i < argc; ++i) {if (strcmp(argv[i], "-fast") == 0) {hints->setTryHarder(false);}else if (strcmp(argv[i], "-norotate") == 0) {hints->setTryRotate(false);}else if (strcmp(argv[i], "-ispure") == 0) {hints->setIsPure(true);hints->setBinarizer(Binarizer::FixedThreshold);}else if (strcmp(argv[i], "-format") == 0) {if (++i == argc)return false;try {hints->setFormats(BarcodeFormatsFromString(argv[i]));}catch (const std::exception& e) {std::cerr << e.what() << "\n";return false;}}else {*filePath = argv[i];}}return !filePath->empty(); }std::ostream& operator<<(std::ostream& os, const Position& points) {for (const auto& p : points)os << p.x << "x" << p.y << " ";return os; }int main(int argc, char* argv[]) {DecodeHints hints;//自己修改二維碼路徑std::string filePath = "C:/Users/admin/Desktop/DM_Rec/imgs/7.jpg";if (!ParseOptions(argc, argv, &hints, &filePath)) {PrintUsage(argv[0]);return -1;}int width, height, channels;clock_t startTime, endTime;std::unique_ptr<stbi_uc, void(*)(void*)> buffer(stbi_load(filePath.c_str(), &width, &height, &channels, 4), stbi_image_free);if (buffer == nullptr) {std::cerr << "Failed to read image: " << filePath << "\n";return -1;}startTime = clock();//計時開始auto result = ReadBarcode({ buffer.get(), width, height, ImageFormat::RGBX }, hints);endTime = clock();//計時結(jié)束std::cout << "Text: \"" << TextUtfEncoding::ToUtf8(result.text()) << "\"\n"<< "Format: " << ToString(result.format()) << "\n"<< "Position: " << result.position() << "\n"<< "Rotation: " << result.orientation() << " deg\n"<< "Error: " << ToString(result.status()) << "\n";std::cout << "The run time is: " << (double)(endTime - startTime) / CLOCKS_PER_SEC << "s" << std::endl;std::map<ResultMetadata::Key, const char*> keys = { {ResultMetadata::ERROR_CORRECTION_LEVEL, "EC Level: "},{ResultMetadata::SUGGESTED_PRICE, "Price: "},{ResultMetadata::ISSUE_NUMBER, "Issue #: "},{ResultMetadata::POSSIBLE_COUNTRY, "Country: "},{ResultMetadata::UPC_EAN_EXTENSION, "Extension:"} };for (auto key : keys) {auto value = TextUtfEncoding::ToUtf8(result.metadata().getString(key.first));if (value.size())std::cout << key.second << value << "\n";}return static_cast<int>(result.status()); }

總結(jié)

以上是生活随笔為你收集整理的基于 libdmtx和zxing的DM二维码识别总结的全部內(nèi)容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網(wǎng)站內(nèi)容還不錯，歡迎將生活随笔推薦給好友。