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| #pragma once
|
| #include <opencv2/opencv.hpp>
| #include "NvInfer.h"
| #include "types.h"
|
| cv::Rect get_rect(cv::Mat& img, float bbox[4]);
|
| cv::Mat scale_mask(cv::Mat mask, cv::Mat img);
|
| cv::Rect get_rect_adapt_landmark(cv::Mat& img, float bbox[4], float lmk[51]);
|
| void nms(std::vector<Detection>& res, float* output, float conf_thresh, float nms_thresh = 0.5);
|
| void batch_nms(std::vector<std::vector<Detection>>& batch_res, float* output, int batch_size, int output_size,
| float conf_thresh, float nms_thresh = 0.5);
|
| void draw_bbox(std::vector<cv::Mat>& img_batch, std::vector<std::vector<Detection>>& res_batch);
|
| void draw_bbox_keypoints_line(std::vector<cv::Mat>& img_batch, std::vector<std::vector<Detection>>& res_batch);
|
| void batch_process(std::vector<std::vector<Detection>>& res_batch, const float* decode_ptr_host, int batch_size,
| int bbox_element, const std::vector<cv::Mat>& img_batch);
|
| void process_decode_ptr_host(std::vector<Detection>& res, const float* decode_ptr_host, int bbox_element, cv::Mat& img,
| int count);
|
| void cuda_decode(float* predict, int num_bboxes, float confidence_threshold, float* parray, int max_objects,
| cudaStream_t stream);
|
| void cuda_nms(float* parray, float nms_threshold, int max_objects, cudaStream_t stream);
|
| void draw_mask_bbox(cv::Mat& img, std::vector<Detection>& dets, std::vector<cv::Mat>& masks,
| std::unordered_map<int, std::string>& labels_map);
|
|