Package org.opencv.dnn
Class TextDetectionModel
java.lang.Object
org.opencv.dnn.Model
org.opencv.dnn.TextDetectionModel
- Direct Known Subclasses:
TextDetectionModel_DB,TextDetectionModel_EAST
Base class for text detection networks
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Method Summary
Modifier and TypeMethodDescriptionstatic TextDetectionModel__fromPtr__(long addr) voiddetect(Mat frame, List<MatOfPoint> detections) voiddetect(Mat frame, List<MatOfPoint> detections, MatOfFloat confidences) Performs detection Given the inputframe, prepare network input, run network inference, post-process network output and return result detections.voiddetectTextRectangles(Mat frame, MatOfRotatedRect detections) voiddetectTextRectangles(Mat frame, MatOfRotatedRect detections, MatOfFloat confidences) Performs detection Given the inputframe, prepare network input, run network inference, post-process network output and return result detections.Methods inherited from class org.opencv.dnn.Model
enableWinograd, getNativeObjAddr, predict, setInputCrop, setInputMean, setInputParams, setInputParams, setInputParams, setInputParams, setInputParams, setInputParams, setInputScale, setInputSize, setInputSize, setInputSwapRB, setOutputNames, setPreferableBackend, setPreferableTarget
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Method Details
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__fromPtr__
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detect
Performs detection Given the inputframe, prepare network input, run network inference, post-process network output and return result detections. Each result is quadrangle's 4 points in this order: - bottom-left - top-left - top-right - bottom-right Use cv::getPerspectiveTransform function to retrieve image region without perspective transformations. Note: If DL model doesn't support that kind of output then result may be derived from detectTextRectangles() output.- Parameters:
frame- The input imagedetections- array with detections' quadrangles (4 points per result)confidences- array with detection confidences
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detect
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detectTextRectangles
Performs detection Given the inputframe, prepare network input, run network inference, post-process network output and return result detections. Each result is rotated rectangle. Note: Result may be inaccurate in case of strong perspective transformations.- Parameters:
frame- the input imagedetections- array with detections' RotationRect resultsconfidences- array with detection confidences
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detectTextRectangles
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