diff options
Diffstat (limited to 'source/use_case/object_detection/include/DetectorPostProcessing.hpp')
| -rw-r--r-- | source/use_case/object_detection/include/DetectorPostProcessing.hpp | 88 |
1 files changed, 42 insertions, 46 deletions
diff --git a/source/use_case/object_detection/include/DetectorPostProcessing.hpp b/source/use_case/object_detection/include/DetectorPostProcessing.hpp index cdb14f5..b3ddb2c 100644 --- a/source/use_case/object_detection/include/DetectorPostProcessing.hpp +++ b/source/use_case/object_detection/include/DetectorPostProcessing.hpp @@ -21,11 +21,13 @@ #include "ImageUtils.hpp" #include "DetectionResult.hpp" #include "YoloFastestModel.hpp" +#include "BaseProcessing.hpp" #include <forward_list> namespace arm { namespace app { + namespace object_detection { struct Branch { @@ -46,42 +48,55 @@ namespace object_detection { int topN; }; +} /* namespace object_detection */ + /** - * @brief Helper class to manage tensor post-processing for "object_detection" - * output. + * @brief Post-processing class for Object Detection use case. + * Implements methods declared by BasePostProcess and anything else needed + * to populate result vector. */ - class DetectorPostprocessing { + class DetectorPostProcess : public BasePostProcess { public: /** - * @brief Constructor. - * @param[in] threshold Post-processing threshold. - * @param[in] nms Non-maximum Suppression threshold. - * @param[in] numClasses Number of classes. - * @param[in] topN Top N for each class. + * @brief Constructor. + * @param[in] outputTensor0 Pointer to the TFLite Micro output Tensor at index 0. + * @param[in] outputTensor1 Pointer to the TFLite Micro output Tensor at index 1. + * @param[out] results Vector of detected results. + * @param[in] inputImgRows Number of rows in the input image. + * @param[in] inputImgCols Number of columns in the input image. + * @param[in] threshold Post-processing threshold. + * @param[in] nms Non-maximum Suppression threshold. + * @param[in] numClasses Number of classes. + * @param[in] topN Top N for each class. **/ - explicit DetectorPostprocessing(float threshold = 0.5f, - float nms = 0.45f, - int numClasses = 1, - int topN = 0); + explicit DetectorPostProcess(TfLiteTensor* outputTensor0, + TfLiteTensor* outputTensor1, + std::vector<object_detection::DetectionResult>& results, + int inputImgRows, + int inputImgCols, + float threshold = 0.5f, + float nms = 0.45f, + int numClasses = 1, + int topN = 0); /** - * @brief Post processing part of YOLO object detection CNN. - * @param[in] imgRows Number of rows in the input image. - * @param[in] imgCols Number of columns in the input image. - * @param[in] modelOutput Output tensors after CNN invoked. - * @param[out] resultsOut Vector of detected results. + * @brief Should perform YOLO post-processing of the result of inference then + * populate Detection result data for any later use. + * @return true if successful, false otherwise. **/ - void RunPostProcessing(uint32_t imgRows, - uint32_t imgCols, - TfLiteTensor* modelOutput0, - TfLiteTensor* modelOutput1, - std::vector<DetectionResult>& resultsOut); + bool DoPostProcess() override; private: - float m_threshold; /* Post-processing threshold */ - float m_nms; /* NMS threshold */ - int m_numClasses; /* Number of classes */ - int m_topN; /* TopN */ + TfLiteTensor* m_outputTensor0; /* Output tensor index 0 */ + TfLiteTensor* m_outputTensor1; /* Output tensor index 1 */ + std::vector<object_detection::DetectionResult>& m_results; /* Single inference results. */ + int m_inputImgRows; /* Number of rows for model input. */ + int m_inputImgCols; /* Number of cols for model input. */ + float m_threshold; /* Post-processing threshold. */ + float m_nms; /* NMS threshold. */ + int m_numClasses; /* Number of classes. */ + int m_topN; /* TopN. */ + object_detection::Network m_net; /* YOLO network object. */ /** * @brief Insert the given Detection in the list. @@ -98,32 +113,13 @@ namespace object_detection { * @param[in] threshold Detections threshold. * @param[out] detections Detection boxes. **/ - void GetNetworkBoxes(Network& net, + void GetNetworkBoxes(object_detection::Network& net, int imageWidth, int imageHeight, float threshold, std::forward_list<image::Detection>& detections); - - /** - * @brief Draw on the given image a bounding box starting at (boxX, boxY). - * @param[in/out] imgIn Image. - * @param[in] imWidth Image width. - * @param[in] imHeight Image height. - * @param[in] boxX Axis X starting point. - * @param[in] boxY Axis Y starting point. - * @param[in] boxWidth Box width. - * @param[in] boxHeight Box height. - **/ - void DrawBoxOnImage(uint8_t* imgIn, - int imWidth, - int imHeight, - int boxX, - int boxY, - int boxWidth, - int boxHeight); }; -} /* namespace object_detection */ } /* namespace app */ } /* namespace arm */ |