Dynamsoft Barcode Reader SDK一款多功能的條碼讀取控件，只需要幾行代碼就可以將條碼讀取功能嵌入到Web或桌面應用程序。這可以節省數月的開發時間和成本。能支持多種圖像文件格式以及從攝像機或掃描儀獲取的DIB格式。使用Dynamsoft Barcode Reader SDK，你可以創建強大且實用的條形碼掃描儀軟件，以滿足你的業務需求。

點擊下載Dynamsoft Barcode Reader最新版

許多企業喜歡使用Dynamsoft Barcode Reader SDK，因為它具有靈活的參數配置和強大的對多個條形碼的解碼能力。在本文中，讓我們看一下條形碼SDK模板以及從開發人員的角度優化解碼性能的可能方法。

如何配置用于解碼性能的模板

如果您從未嘗試過Dynamsoft Barcode Reader SDK，則可以在在線條形碼游樂場玩耍，只需更改模式即可直接比較性能差異。

此外，如果您是專家，則可以單擊高級設置自行調整一系列參數。

為了方便開發人員，我向Github上傳了五個有用的模板文件：

• Speed.json
• Balanced.json
• Coverage.json
• Morecoverage.json
• Mostcoverage.json

這是我的測試圖像：

我們來看一下使用不同模板的檢測準確性和時間成本：

BarcodeReader.exe AllSupportedBarcodeTypes.png  license.txt  speed.json   
Total barcode(s) found: 12. Time cost: 63 ms

BarcodeReader.exe AllSupportedBarcodeTypes.png  license.txt   balanced.json
Total barcode(s) found: 13. Time cost: 140 ms
 
BarcodeReader.exe AllSupportedBarcodeTypes.png  license.txt   coverage.json
Total barcode(s) found: 13. Time cost: 844 ms
 
BarcodeReader.exe AllSupportedBarcodeTypes.png  license.txt   morecoverage.json
Total barcode(s) found: 13. Time cost: 1610 ms
 
BarcodeReader.exe AllSupportedBarcodeTypes.png  license.txt   mostcoverage.json
Total barcode(s) found: 13. Time cost: 3156 ms

使用多線程可以加快多條形碼解碼的性能嗎？

按照我們的常識，解碼單個條形碼的時間成本應小于解碼多個條形碼的時間成本。因此，讀取多個條形碼的一種可能的優化方法是創建多個工作線程，以同時處理不同的條形碼符號。

這是用于順序解碼一維和二維條形碼的代碼：

barcode_decoding(buffer, size, BF_CODE_39, 1, license, config);
barcode_decoding(buffer, size, BF_QR_CODE, 1, license, config);
barcode_decoding(buffer, size, BF_PDF417, 1, license, config);
barcode_decoding(buffer, size, BF_DATAMATRIX, 1, license, config);

Thread id: 22536. Type: CODE_39
Thread id: 22536. Total barcode(s) found: 1. Time cost: 235 ms
 
Thread id: 22536. Type: QR_CODE
Thread id: 22536. Total barcode(s) found: 1. Time cost: 47 ms
 
Thread id: 22536. Type: PDF417
Thread id: 22536. Total barcode(s) found: 1. Time cost: 62 ms
 
Thread id: 22536. Type: DATAMATRIX
Thread id: 22536. Total barcode(s) found: 1. Time cost: 63 ms

int starttime = gettime();
thread t1(barcode_decoding, buffer, size, BF_CODE_39, 1, license, config); 
thread t2(barcode_decoding, buffer, size, BF_QR_CODE, 1, license, config);
thread t3(barcode_decoding, buffer, size, BF_PDF417, 1, license, config);
thread t4(barcode_decoding, buffer, size, BF_DATAMATRIX, 1, license, config);
t1.join();
t2.join();
t3.join();
t4.join();
int endtime = gettime();
printf("Thread time cost: %d ms\n\n", (endtime - starttime));

Thread id: 24024. Type: QR_CODE
Thread id: 24024. Total barcode(s) found: 1. Time cost: 78 ms
 
Thread id: 17384. Type: DATAMATRIX
Thread id: 17384. Total barcode(s) found: 1. Time cost: 78 ms
 
Thread id: 24264. Type: PDF417
Thread id: 24264. Total barcode(s) found: 1. Time cost: 94 ms
 
Thread id: 4060. Type: CODE_39
Thread id: 4060. Total barcode(s) found: 1. Time cost: 265 ms
 
Thread time cost: 265 ms

barcode_decoding(buffer, size, BF_CODE_39 | BF_DATAMATRIX | BF_QR_CODE | BF_PDF417, 1, license, config);

Thread id: 20308. Type: PDF417
Thread id: 20308. Type: QR_CODE
Thread id: 20308. Type: DATAMATRIX
Thread id: 20308. Type: CODE_39
Thread id: 20308. Total barcode(s) found: 4. Time cost: 250 ms

您可能已經注意到，有一個名為maxAlgorithmThreadCount的參數。我們可以通過增加線程數來提高SDK性能嗎？

我根據硬件線程做了一個簡單的測試：

const auto processor_count = std::thread::hardware_concurrency();
int minimum_count = 1, minimum_timecost = 0;
    for (int i = 0; i < processor_count; i++) 
    {
        printf("Thread count: %d. ", i + 1);
        int timecost = barcode_decoding(buffer, size, formats, i, license, config);
        if (i == 0) 
        {
            minimum_count = 1; 
            if (timecost > 0)
            {
                minimum_timecost = timecost; 
            }
        }
        else {
            if (timecost < minimum_timecost)
            {
                minimum_count = i + 1;
                minimum_timecost = timecost; 
            }
        }
    }
    printf("Multi-thread best performance: thread_count = %d, timecost = %d \n\n", minimum_count, minimum_timecost);

Thread count: 1. Thread id: 26376. Total barcode(s) found: 13. Time cost: 141 ms
 
Thread count: 2. Thread id: 26376. Total barcode(s) found: 13. Time cost: 141 ms
 
Thread count: 3. Thread id: 26376. Total barcode(s) found: 13. Time cost: 125 ms
 
Thread count: 4. Thread id: 26376. Total barcode(s) found: 13. Time cost: 140 ms
 
Thread count: 5. Thread id: 26376. Total barcode(s) found: 13. Time cost: 157 ms
 
Thread count: 6. Thread id: 26376. Total barcode(s) found: 13. Time cost: 203 ms
 
Thread count: 7. Thread id: 26376. Total barcode(s) found: 13. Time cost: 156 ms
 
Thread count: 8. Thread id: 26376. Total barcode(s) found: 13. Time cost: 140 ms
 
Multi-thread best performance: thread_count = 3, timecost = 125