#pragma once #include "vp_infer_node.h" namespace vp_nodes { // secondary infer node, it is the base class of infer node which MUST infer on small cropped image. // note: detector such as yolo can be also applied on small cropped images. class vp_secondary_infer_node: public vp_infer_node { private: protected: // define how to prepare data virtual void prepare(const std::vector>& frame_meta_with_batch, std::vector& mats_to_infer) override; bool need_apply(int primary_class_id, int target_width, int target_height); public: vp_secondary_infer_node(std::string node_name, std::string model_path, std::string model_config_path = "", std::string labels_path = "", int input_width = 640, int input_height = 640, int batch_size = 1, std::vector p_class_ids_applied_to = std::vector(), int min_width_applied_to = 0, int min_height_applied_to = 0, int crop_padding = 10, float scale = 1.0, cv::Scalar mean = cv::Scalar(123.675, 116.28, 103.53), // imagenet dataset cv::Scalar std = cv::Scalar(1), bool swap_rb = true, bool swap_chn = false); ~vp_secondary_infer_node(); // we do secondary infer logic only if the primary class-id of target is in this vector. // not all targets in frame should be handled by vp_secondary_infer_node. std::vector p_class_ids_applied_to; int crop_padding; // min height of target to be handled by vp_secondary_infer_node, 0 means no restriction int min_height_applied_to = 0; // min width of target to be handled by vp_secondary_infer_node,0 means no restriction int min_width_applied_to = 0; }; }