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https://github.com/open-mmlab/mmdeploy.git
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0ce7c83c63
* support mmrotate * fix name * windows default link to cudart_static.lib, which is not compatible with static build && python_api * python api * fix ci * fix type & remove unused meta info * fix doxygen, add [out] to @param * fix mmrotate-c-api * refactor naming * refactor naming * fix lint * fix lint * move replace_RResize -> get_preprocess * Update cuda.cmake On windows, make static lib and python api build success. * fix ptr * Use unique ptr to prevent memory leaks * move unique_ptr * remove deleter Co-authored-by: chenxin2 <chenxin2@sensetime.com> Co-authored-by: cx <cx@ubuntu20.04>
87 lines
2.9 KiB
C
87 lines
2.9 KiB
C
// Copyright (c) OpenMMLab. All rights reserved.
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/**
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* @file detector.h
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* @brief Interface to MMDetection task
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*/
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#ifndef MMDEPLOY_DETECTOR_H
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#define MMDEPLOY_DETECTOR_H
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#include "common.h"
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#ifdef __cplusplus
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extern "C" {
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#endif
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typedef struct mm_instance_mask_t {
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char* data;
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int height;
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int width;
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} mm_instance_mask_t;
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typedef struct mm_detect_t {
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int label_id;
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float score;
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mm_rect_t bbox;
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mm_instance_mask_t* mask;
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} mm_detect_t;
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/**
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* @brief Create detector's handle
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* @param[in] model an instance of mmdetection sdk model created by
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* \ref mmdeploy_model_create_by_path or \ref mmdeploy_model_create in \ref model.h
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* @param[in] device_name name of device, such as "cpu", "cuda", etc.
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* @param[in] device_id id of device.
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* @param[out] handle instance of a detector
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* @return status of creating detector's handle
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*/
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MMDEPLOY_API int mmdeploy_detector_create(mm_model_t model, const char* device_name, int device_id,
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mm_handle_t* handle);
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/**
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* @brief Create detector's handle
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* @param[in] model_path path of mmdetection sdk model exported by mmdeploy model converter
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* @param[in] device_name name of device, such as "cpu", "cuda", etc.
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* @param[in] device_id id of device.
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* @param[out] handle instance of a detector
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* @return status of creating detector's handle
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*/
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MMDEPLOY_API int mmdeploy_detector_create_by_path(const char* model_path, const char* device_name,
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int device_id, mm_handle_t* handle);
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/**
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* @brief Apply detector to batch images and get their inference results
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* @param[in] handle detector's handle created by \ref mmdeploy_detector_create_by_path
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* @param[in] mats a batch of images
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* @param[in] mat_count number of images in the batch
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* @param[out] results a linear buffer to save detection results of each image. It must be released
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* by \ref mmdeploy_detector_release_result
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* @param[out] result_count a linear buffer with length being \p mat_count to save the number of
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* detection results of each image. And it must be released by \ref
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* mmdeploy_detector_release_result
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* @return status of inference
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*/
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MMDEPLOY_API int mmdeploy_detector_apply(mm_handle_t handle, const mm_mat_t* mats, int mat_count,
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mm_detect_t** results, int** result_count);
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/** @brief Release the inference result buffer created by \ref mmdeploy_detector_apply
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* @param[in] results detection results buffer
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* @param[in] result_count \p results size buffer
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* @param[in] count length of \p result_count
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*/
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MMDEPLOY_API void mmdeploy_detector_release_result(mm_detect_t* results, const int* result_count,
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int count);
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/**
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* @brief Destroy detector's handle
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* @param[in] handle detector's handle created by \ref mmdeploy_detector_create_by_path
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*/
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MMDEPLOY_API void mmdeploy_detector_destroy(mm_handle_t handle);
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#ifdef __cplusplus
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}
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#endif
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#endif // MMDEPLOY_DETECTOR_H
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