Base class for text detection networks [詳解]
#include <dnn.hpp>
cv::dnn::Modelを継承しています。
cv::dnn::TextDetectionModel_DB, cv::dnn::TextDetectionModel_EASTに継承されています。
公開メンバ関数 | |
| CV_WRAP void | detect (InputArray frame, CV_OUT std::vector< std::vector< Point > > &detections, CV_OUT std::vector< float > &confidences) const |
| Performs detection [詳解] | |
| CV_WRAP void | detect (InputArray frame, CV_OUT std::vector< std::vector< Point > > &detections) const |
| CV_WRAP void | detectTextRectangles (InputArray frame, CV_OUT std::vector< cv::RotatedRect > &detections, CV_OUT std::vector< float > &confidences) const |
| Performs detection [詳解] | |
| CV_WRAP void | detectTextRectangles (InputArray frame, CV_OUT std::vector< cv::RotatedRect > &detections) const |
 基底クラス cv::dnn::Model に属する継承公開メンバ関数 | |
| Model (const Model &)=default | |
| Model (Model &&)=default | |
| Model & | operator= (const Model &)=default |
| Model & | operator= (Model &&)=default |
| CV_WRAP | Model (const String &model, const 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. [詳解] | |
| CV_WRAP | Model (const Net &network) |
| Create model from deep learning network. [詳解] | |
| CV_WRAP Model & | setInputSize (const Size &size) |
| Set input size for frame. [詳解] | |
| CV_WRAP Model & | setInputSize (int width, int height) |
| CV_WRAP Model & | setInputMean (const Scalar &mean) |
| Set mean value for frame. [詳解] | |
| CV_WRAP Model & | setInputScale (double scale) |
| Set scalefactor value for frame. [詳解] | |
| CV_WRAP Model & | setInputCrop (bool crop) |
| Set flag crop for frame. [詳解] | |
| CV_WRAP Model & | setInputSwapRB (bool swapRB) |
| Set flag swapRB for frame. [詳解] | |
| CV_WRAP void | setInputParams (double scale=1.0, const Size &size=Size(), const Scalar &mean=Scalar(), bool swapRB=false, bool crop=false) |
| Set preprocessing parameters for frame. [詳解] | |
| CV_WRAP void | predict (InputArray frame, OutputArrayOfArrays outs) const |
Given the input frame, create input blob, run net and return the output blobs. [詳解] | |
| CV_WRAP Model & | setPreferableBackend (dnn::Backend backendId) |
| CV_WRAP Model & | setPreferableTarget (dnn::Target targetId) |
| CV_DEPRECATED_EXTERNAL | operator Net & () const |
| Net & | getNetwork_ () const |
| Net & | getNetwork_ () |
| Impl * | getImpl () const |
| Impl & | getImplRef () const |
その他の継承メンバ | |
| 基底クラス cv::dnn::Model に属する継承限定公開変数類 | |
| Ptr< Impl > | impl |
詳解
Base class for text detection networks
関数詳解
◆ detect() [1/2]
| CV_WRAP void cv::dnn::TextDetectionModel::detect | ( | InputArray | frame, |
| CV_OUT std::vector< std::vector< Point > > & | detections | ||
| ) | const |
これはオーバーロードされたメンバ関数です。利便性のために用意されています。元の関数との違いは引き数のみです。
◆ detect() [2/2]
| CV_WRAP void cv::dnn::TextDetectionModel::detect | ( | InputArray | frame, |
| CV_OUT std::vector< std::vector< Point > > & | detections, | ||
| CV_OUT std::vector< float > & | confidences | ||
| ) | const |
Performs detection
Given the input frame, 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 retrive image region without perspective transformations.
- 覚え書き
- If DL model doesn't support that kind of output then result may be derived from detectTextRectangles() output.
- 引数
-
[in] frame The input image [out] detections array with detections' quadrangles (4 points per result) [out] confidences array with detection confidences
◆ detectTextRectangles() [1/2]
| CV_WRAP void cv::dnn::TextDetectionModel::detectTextRectangles | ( | InputArray | frame, |
| CV_OUT std::vector< cv::RotatedRect > & | detections | ||
| ) | const |
これはオーバーロードされたメンバ関数です。利便性のために用意されています。元の関数との違いは引き数のみです。
◆ detectTextRectangles() [2/2]
| CV_WRAP void cv::dnn::TextDetectionModel::detectTextRectangles | ( | InputArray | frame, |
| CV_OUT std::vector< cv::RotatedRect > & | detections, | ||
| CV_OUT std::vector< float > & | confidences | ||
| ) | const |
Performs detection
Given the input frame, prepare network input, run network inference, post-process network output and return result detections.
Each result is rotated rectangle.
- 覚え書き
- Result may be inaccurate in case of strong perspective transformations.
- 引数
-
[in] frame the input image [out] detections array with detections' RotationRect results [out] confidences array with detection confidences
このクラス詳解は次のファイルから抽出されました:
