This class represents high-level API for text detection DL networks compatible with DB model.
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| TextDetectionModel_DB (Net network) |
| Create text detection algorithm from deep learning network.
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| TextDetectionModel_DB (string model) |
| Create text detection model from network represented in one of the supported formats. An order of model and config arguments does not matter.
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| TextDetectionModel_DB (string model, string config) |
| Create text detection model from network represented in one of the supported formats. An order of model and config arguments does not matter.
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float | getBinaryThreshold () |
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int | getMaxCandidates () |
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float | getPolygonThreshold () |
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double | getUnclipRatio () |
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TextDetectionModel_DB | setBinaryThreshold (float binaryThreshold) |
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TextDetectionModel_DB | setMaxCandidates (int maxCandidates) |
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TextDetectionModel_DB | setPolygonThreshold (float polygonThreshold) |
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TextDetectionModel_DB | setUnclipRatio (double unclipRatio) |
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void | detect (Mat frame, List< MatOfPoint > detections) |
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void | detect (Mat frame, List< MatOfPoint > detections, MatOfFloat confidences) |
| Performs detection.
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void | detectTextRectangles (Mat frame, MatOfRotatedRect detections) |
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void | detectTextRectangles (Mat frame, MatOfRotatedRect detections, MatOfFloat confidences) |
| Performs detection.
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| Model (Net network) |
| Create model from deep learning network.
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| Model (string model) |
| Create model from deep learning network represented in one of the supported formats. An order of model and config arguments does not matter.
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| Model (string model, string config) |
| Create model from deep learning network represented in one of the supported formats. An order of model and config arguments does not matter.
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Model | enableWinograd (bool useWinograd) |
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IntPtr | getNativeObjAddr () |
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void | predict (Mat frame, List< Mat > outs) |
| Given the input frame, create input blob, run net and return the output blobs .
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Model | setInputCrop (bool crop) |
| Set flag crop for frame.
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Model | setInputMean (in Vec4d mean) |
| Set mean value for frame.
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Model | setInputMean (in(double v0, double v1, double v2, double v3) mean) |
| Set mean value for frame.
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Model | setInputMean (Scalar mean) |
| Set mean value for frame.
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void | setInputParams () |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, in Vec2d size) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, in Vec2d size, in Vec4d mean) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, in Vec2d size, in Vec4d mean, bool swapRB) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, in Vec2d size, in Vec4d mean, bool swapRB, bool crop) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, in(double width, double height) size) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB, bool crop) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, Size size) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, Size size, Scalar mean) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, Size size, Scalar mean, bool swapRB) |
| Set preprocessing parameters for frame.
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void | setInputParams (double scale, Size size, Scalar mean, bool swapRB, bool crop) |
| Set preprocessing parameters for frame.
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Model | setInputScale (in Vec4d scale) |
| Set scalefactor value for frame.
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Model | setInputScale (in(double v0, double v1, double v2, double v3) scale) |
| Set scalefactor value for frame.
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Model | setInputScale (Scalar scale) |
| Set scalefactor value for frame.
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Model | setInputSize (in Vec2d size) |
| Set input size for frame.
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Model | setInputSize (in(double width, double height) size) |
| Set input size for frame.
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Model | setInputSize (int width, int height) |
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Model | setInputSize (Size size) |
| Set input size for frame.
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Model | setInputSwapRB (bool swapRB) |
| Set flag swapRB for frame.
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Model | setOutputNames (List< string > outNames) |
| Set output names for frame.
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Model | setPreferableBackend (int backendId) |
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Model | setPreferableTarget (int targetId) |
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void | Dispose () |
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void | ThrowIfDisposed () |
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This class represents high-level API for text detection DL networks compatible with DB model.
Related publications: [liao2020real] Paper: https://arxiv.org/abs/1911.08947 For more information about the hyper-parameters setting, please refer to https://github.com/MhLiao/DB
Configurable parameters:
- (float) binaryThreshold - The threshold of the binary map. It is usually set to 0.3.
- (float) polygonThreshold - The threshold of text polygons. It is usually set to 0.5, 0.6, and 0.7. Default is 0.5f
- (double) unclipRatio - The unclip ratio of the detected text region, which determines the output size. It is usually set to 2.0.
- (int) maxCandidates - The max number of the output results.