first commit

nodes/infers/vp_mask_rcnn_detector_node.h

@@ -0,0 +1,41 @@
+
+#pragma once
+
+#include "../vp_primary_infer_node.h"
+#include "../../objects/vp_frame_target.h"
+
+
+
+namespace vp_nodes {
+    // image segmentation based on Mask RCNN
+    // https://github.com/matterport/Mask_RCNN
+    class vp_mask_rcnn_detector_node: public vp_primary_infer_node
+    {
+    private:
+        /* data */
+        // names of output layers in mask_rcnn
+        const std::vector<std::string> out_names = {"detection_out_final", "detection_masks"};
+        float score_threshold = 0.5;
+    protected:
+        // override infer and preprocess as mask_rcnn has a different logic
+        virtual void infer(const cv::Mat& blob_to_infer, std::vector<cv::Mat>& raw_outputs) override;
+        virtual void preprocess(const std::vector<cv::Mat>& mats_to_infer, cv::Mat& blob_to_infer) override;
+
+        virtual void postprocess(const std::vector<cv::Mat>& raw_outputs, const std::vector<std::shared_ptr<vp_objects::vp_frame_meta>>& frame_meta_with_batch) override;
+    public:
+        vp_mask_rcnn_detector_node(std::string node_name, 
+                            std::string model_path, 
+                            std::string model_config_path = "", 
+                            std::string labels_path = "", 
+                            int input_width = 416, 
+                            int input_height = 416, 
+                            int batch_size = 1,
+                            int class_id_offset = 0,
+                            float score_threshold = 0.5,
+                            float scale = 1 / 255.0,
+                            cv::Scalar mean = cv::Scalar(0),
+                            cv::Scalar std = cv::Scalar(1),
+                            bool swap_rb = true);
+        ~vp_mask_rcnn_detector_node();
+    };    
+}