Dynamsoft Barcode Reader SDK一款多功能的条码读取控件,只需要几行代码就可以将条码读取功能嵌入到Web或桌面应用程序。这可以节省数月的开发时间和成本。能支持多种图像文件格式以及从摄像机或扫描仪获取的DIB格式。使用Dynamsoft Barcode Reader SDK,你可以创建强大且实用的条形码扫描仪软件,以满足你的业务需求。
点击下载Dynamsoft Barcode Reader最新版
如果要使用Python和Qt构建跨平台的GUI应用程序,则可以使用PyQt或PySide。它们都是Python的Qt绑定。主要区别在于许可证:PyQt5是根据GPL还是商业PySide2发布,而根据则发布LGPL。由于正式建议使用PySide2,因此我将使用PySid2和Dynamsoft Python条形码SDK在Raspberry Pi上创建GUI条形码读取器应用程序。
要求
OpenCV Python
python3 -m pip install opencv-python
Dynamsoft Python条形码SDK
python3 -m pip install dbr
PySide2
sudo apt-get install python3-pyside2.qt3dcore python3-pyside2.qt3dinput python3-pyside2.qt3dlogic python3-pyside2.qt3drender python3-pyside2.qtcharts python3-pyside2.qtconcurrent python3-pyside2.qtcore python3-pyside2.qtgui python3-pyside2.qthelp python3-pyside2.qtlocation python3-pyside2.qtmultimedia python3-pyside2.qtmultimediawidgets python3-pyside2.qtnetwork python3-pyside2.qtopengl python3-pyside2.qtpositioning python3-pyside2.qtprintsupport python3-pyside2.qtqml python3-pyside2.qtquick python3-pyside2.qtquickwidgets python3-pyside2.qtscript python3-pyside2.qtscripttools python3-pyside2.qtsensors python3-pyside2.qtsql python3-pyside2.qtsvg python3-pyside2.qttest python3-pyside2.qttexttospeech python3-pyside2.qtuitools python3-pyside2.qtwebchannel python3-pyside2.qtwebsockets python3-pyside2.qtwidgets python3-pyside2.qtx11extras python3-pyside2.qtxml python3-pyside2.qtxmlpatterns python3-pyside2uic
Raspberry Pi OS的GUI条形码阅读器
让我们开始使用UI小部件:
- 用于加载图像文件的按钮:
self.btn = QPushButton("Load an image")
self.btn.clicked.connect(self.pickFile)
def pickFile(self):
filename = QFileDialog.getOpenFileName(self, 'Open file',
self._path, "Barcode images (*)")
if filename is None or filename[0] == '':
self.showMessageBox("No file selected")
return
- 用于打开实时摄像机流的按钮:
btnCamera = QPushButton("Open camera")
btnCamera.clicked.connect(self.openCamera)
self.timer = QTimer()
self.timer.timeout.connect(self.nextFrameUpdate)
def openCamera(self):
if not self._cap.isOpened():
self.showMessageBox("Failed to open camera.")
return
self.timer.start(1000./24)
- 用于停止摄像机流的按钮:
btnCamera = QPushButton("Stop camera")
btnCamera.clicked.connect(self.stopCamera)
def stopCamera(self):
self.timer.stop()
用于显示摄像机框架的标签和用于显示条形码解码结果的文本区域:
self.label = QLabel()
self.label.setFixedSize(self.WINDOW_WIDTH - 30, self.WINDOW_HEIGHT - 160)
self.results = QTextEdit()
def showResults(self, frame, results):
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
image = QImage(frame, frame.shape[1], frame.shape[0], frame.strides[0], QImage.Format_RGB888)
pixmap = QPixmap.fromImage(image)
pixmap = self.resizeImage(pixmap)
self.label.setPixmap(pixmap)
self.results.setText(results)
我们使用OpenCV读取图像文件并捕获网络摄像头帧:
frame = cv2.imread(filename)
self._cap = cv2.VideoCapture(0)
self._cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
self._cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
ret, frame = self._cap.read()
下一步很重要。我们需要考虑如何集成条形码解码API。
我们立即想到的最简单的方法是,一旦获得帧,便调用解码方法:
def nextFrameSlot(self):
ret, frame = self._cap.read()
if not ret:
self.showMessageBox('Failed to get camera frame!')
return
frame, results = self._manager.decode_frame(frame)
self.showResults(frame, results)
但是,我们无法在Raspberry Pi上执行此操作!条形码扫描是一项占用大量CPU的任务,如果花费太多时间,它将阻塞UI线程。因此,我们必须在不同的线程中分别执行UI代码和条形码识别代码。由于Python GIL的性能限制,Python线程也不可行。那QThread呢 QThread与Python线程的实现方式相同。为了验证QThread的性能,我们可以使用以下代码进行测试:
class WorkerSignals(QObject):
result = Signal(object)
class BarcodeManager(QThread):
def __init__(self, license):
super(BarcodeManager, self).__init__()
self.signals = WorkerSignals()
self._reader = BarcodeReader()
self._reader.init_license(license)
settings = self._reader.get_runtime_settings()
settings.max_algorithm_thread_count = 1
self._reader.update_runtime_settings(settings)
self.frameQueue = Queue(1)
def register_callback(self, fn):
self.signals.result.connect(fn)
def run(self):
while True:
try:
frame = self.frameQueue.get(False, 10)
if type(frame) is str:
break
except:
time.sleep(0.01)
continue
try:
results = self._reader.decode_buffer(frame)
self.signals.result.emit(results)
except BarcodeReaderError as error:
print(error)
事实证明,性能没有任何提高。因此,最可行的方法是在另一种方法中执行条形码解码任务Python Process:
from multiprocessing import Process, Queue
import time
import numpy as np
def process_barcode_frame(license, frameQueue, resultQueue):
# Create Dynamsoft Barcode Reader
reader = BarcodeReader()
# Apply for a trial license: https://www.dynamsoft.com/customer/license/trialLicense
reader.init_license(license)
settings = reader.get_runtime_settings()
settings.max_algorithm_thread_count = 1
reader.update_runtime_settings(settings)
while True:
results = None
try:
frame = frameQueue.get(False, 10)
if type(frame) is str:
break
except:
time.sleep(0.01)
continue
try:
frameHeight, frameWidth, channel = frame.shape[:3]
results = reader.decode_buffer_manually(np.array(frame).tobytes(), frameWidth, frameHeight, frame.strides[0], EnumImagePixelFormat.IPF_RGB_888)
except BarcodeReaderError as error:
print(error)
try:
resultQueue.put(results, False, 10)
except:
pass
def create_decoding_process(license):
size = 1
frameQueue = Queue(size)
resultQueue = Queue(size)
barcodeScanning = Process(target=process_barcode_frame, args=(license, frameQueue, resultQueue))
barcodeScanning.start()
return frameQueue, resultQueue, barcodeScanning
我们创建两个队列作为两个进程之间的数据隧道。
到目前为止,该应用程序已完成。另一件事是申请免费试用许可证并将其保存到本地磁盘。
将USB网络摄像头连接到Raspberry Pi,然后运行该应用程序:
GUI条码阅读器应用程序是跨平台的。它也可以工作Windows,Linux和macOS。