Dynamic Web TWAIN是一个专为Web应用程序设计的TWAIN扫描识别控件。你只需在TWAIN接口写几行代码,就可以用兼容TWAIN的扫描仪扫描文档或从数码相机/采集卡中获取图像。然后用户可以编辑图像并将图像保存为多种格式,用户可保存图像到远程数据库或者SharePoint。该TWAIN控件还支持上传和处理本地图像。
本文汇集了一些Dynamic Web TWAIN编程方面的常见问题,并且针对这些问题进行了回答,感兴趣的朋友快来了解一下吧~
慧都网下载Dynamic Web TWAIN正式版
将Dynamsoft Barcode SDK的C / C ++ API与JavaScript绑定
让我们开始使用Node.js条码C / C ++插件。
为了支持OpenCV Mat,我创建了一个新的API encodingBufferAsync()。C / C ++代码如下:
void DecodeBufferAsync(const FunctionCallbackInfo& args) {
if (!createDBR()) {return;}
Isolate* isolate = Isolate::GetCurrent();
Local context = isolate->GetCurrentContext();
// get arguments
unsigned char* buffer = (unsigned char*) node::Buffer::Data(args[0]); // file stream
int width = args[1]->Int32Value(context).ToChecked(); // image width
int height = args[2]->Int32Value(context).ToChecked(); // image height
int stride = args[3]->Int32Value(context).ToChecked(); // stride
int iFormat = args[4]->Int32Value(context).ToChecked(); // barcode types
Local cb = Local::Cast(args[5]); // javascript callback function
String::Utf8Value templateName(isolate, args[6]); // template name
char *pTemplateName = *templateName;
// initialize BarcodeWorker
BarcodeWorker *worker = new BarcodeWorker;
worker->request.data = worker;
worker->callback.Reset(isolate, cb);
worker->iFormat = iFormat;
worker->pResults = NULL;
worker->buffer = buffer;
worker->width = width;
worker->height = height;
worker->bufferType = RGB_BUFFER;
worker->stride = stride;
if (hasTemplate(pTemplateName)) {
// Load the template.
char szErrorMsg[256];
DBR_InitRuntimeSettingsWithString(hBarcode, pTemplateName, CM_OVERWRITE, szErrorMsg, 256);
worker->useTemplate = true;
}
else {
worker->useTemplate = false;
}
uv_queue_work(uv_default_loop(), &worker->request, (uv_work_cb)DetectionWorking, (uv_after_work_cb)DetectionDone);
}
第一个参数是Node.js缓冲区指针。您可以调用getData()从Mat获取字节数组:
const vCap = new cv.VideoCapture(0);
var img = vCap.read();
dbr.decodeBufferAsync(img.getData(), img.cols, img.rows, img.step, barcodeTypes, function (err, msg) {
results = msg
}, "");
注意:macOS的构建配置与binding.gyp文件中的Linux配置略有不同:
'copies': [
{
'destination': '/usr/local/lib/',
'files': [
'./platforms/macos/libDynamsoftBarcodeReader.dylib'
]
}
]
与在Linux上不同,一旦构建完成,动态库文件将被复制到/ usr / local / lib /目录。原因是RPATH无法在macOS上运行。我们可以使用“ otool -L dbr.node ”来检查依赖库,然后获取路径/usr/local/lib/libDynamsoftBarcodeReader.dylib。
如果要将库文件和dbr.node保留在同一文件夹中,则可以手动更改库路径:
cd build/Release
install_name_tool -change /usr/local/lib/libDynamsoftBarcodeReader.dylib @loader_path/libDynamsoftBarcodeReader.dylib dbr.node
我已经将该软件包发布到https://www.evget.com/product/1313。要安装该软件包,您需要安装C ++开发工具,然后运行:
npm install -g node-gyp
npm install barcode4nodejs
在5分钟内为桌面和Web构建Node.js条形码阅读器
桌面
基本上,我们可以使用无限循环来捕获摄像头帧并将其显示在窗口中:
const cv = require('opencv4nodejs');
const vCap = new cv.VideoCapture(0);
const delay = 10;
while (true) {
let frame = vCap.read();
if (frame.empty) {
vCap.reset();
frame = vCap.read();
}
cv.imshow('OpenCV Node.js', frame);
const key = cv.waitKey(delay); // Press ESC to quit
if (key == 27) {break;}
}
但是,如果我们在循环中调用异步条形码解码功能,则回调函数将永远不会返回。为了使其工作,我们可以使用setTimeout() 代替:
const dbr = require('barcode4nodejs');
const cv = require('opencv4nodejs');
dbr.initLicense("LICENSE-KEY")
barcodeTypes = dbr.barcodeTypes
const vCap = new cv.VideoCapture(0);
const drawParams = { color: new cv.Vec(0, 255, 0), thickness: 2 }
const fontFace = cv.FONT_HERSHEY_SIMPLEX;
const fontScale = 0.5;
const textColor = new cv.Vec(255, 0, 0);
const thickness = 2;
results = null;
function getframe() {
let img = vCap.read();
dbr.decodeBufferAsync(img.getData(), img.cols, img.rows, img.step, barcodeTypes, function (err, msg) {
results = msg
}, "", 1);
cv.imshow('Webcam', img);
const key = cv.waitKey(10); // Press ESC to quit
if (key != 27) {
setTimeout(getframe, 30);
}
}
getframe()
由于连续的网络摄像头图像相似,因此可以在不同的帧上绘制结果:
if (results != null) {
for (index in results) {
let result = results[index];
let upperLeft = new cv.Point(result.x1, result.y1)
let bottomLeft = new cv.Point(result.x2, result.y2)
let upperRight = new cv.Point(result.x3, result.y3)
let bottomRight = new cv.Point(result.x4, result.y4)
img.drawLine(
upperLeft,
bottomLeft,
drawParams
)
img.drawLine(
bottomLeft,
upperRight,
drawParams
)
img.drawLine(
upperRight,
bottomRight,
drawParams
)
img.drawLine(
bottomRight,
upperLeft,
drawParams
)
img.putText(result.value, new cv.Point(result.x1, result.y1 + 10), fontFace, fontScale, textColor, thickness);
}
}
网页
将条形码检测代码复制到web.js文件中:
function capture() {
var frame = wCap.read()
if (frame.empty) {
wCap.reset();
frame = wCap.read();
}
dbr.decodeBufferAsync(frame.getData(), frame.cols, frame.rows, frame.step, barcodeTypes, function (err, msg) {
// console.log(results)
results = msg
}, "", 1);
if (results != null) {
for (index in results) {
let result = results[index];
let upperLeft = new cv.Point(result.x1, result.y1)
let bottomLeft = new cv.Point(result.x2, result.y2)
let upperRight = new cv.Point(result.x3, result.y3)
let bottomRight = new cv.Point(result.x4, result.y4)
frame.drawLine(
upperLeft,
bottomLeft,
drawParams
)
frame.drawLine(
bottomLeft,
upperRight,
drawParams
)
frame.drawLine(
upperRight,
bottomRight,
drawParams
)
frame.drawLine(
bottomRight,
upperLeft,
drawParams
)
frame.putText(result.value, new cv.Point(result.x1, result.y1 + 10), fontFace, fontScale, textColor, thickness);
}
}
img = cv.imencode('.jpg', frame);
setTimeout(capture, 30);
}
capture();
现在我们可以运行服务器端条形码检测。它与任何Web浏览器完全兼容。这是Microsoft Internet Explorer的屏幕截图。
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