100 lines
3.9 KiB
C
100 lines
3.9 KiB
C
// Copyright (c) OpenMMLab. All rights reserved.
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/**
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* @file segmentor.h
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* @brief Interface to MMSegmentation task
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*/
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#ifndef MMDEPLOY_SEGMENTOR_H
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#define MMDEPLOY_SEGMENTOR_H
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#include "common.h"
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#include "executor.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_segment_t {
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int height; ///< height of \p mask that equals to the input image's height
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int width; ///< width of \p mask that equals to the input image's width
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int classes; ///< the number of labels in \p mask
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int* mask; ///< segmentation mask of the input image, in which mask[i * width + j] indicates
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///< the label id of pixel at (i, j)
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} mm_segment_t;
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/**
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* @brief Create segmentor's handle
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* @param[in] model an instance of mmsegmentation 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 segmentor, which must be destroyed
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* by \ref mmdeploy_segmentor_destroy
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* @return status of creating segmentor's handle
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*/
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MMDEPLOY_API int mmdeploy_segmentor_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 segmentor's handle
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* @param[in] model_path path of mmsegmentation 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 segmentor, which must be destroyed
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* by \ref mmdeploy_segmentor_destroy
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* @return status of creating segmentor's handle
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*/
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MMDEPLOY_API int mmdeploy_segmentor_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 segmentor to batch images and get their inference results
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* @param[in] handle segmentor's handle created by \ref mmdeploy_segmentor_create_by_path or \ref
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* mmdeploy_segmentor_create
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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 of length \p mat_count to save segmentation result of each
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* image. It must be released by \ref mmdeploy_segmentor_release_result
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* @return status of inference
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*/
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MMDEPLOY_API int mmdeploy_segmentor_apply(mm_handle_t handle, const mm_mat_t* mats, int mat_count,
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mm_segment_t** results);
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/**
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* @brief Release result buffer returned by \ref mmdeploy_segmentor_apply
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* @param[in] results result buffer
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* @param[in] count length of \p results
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*/
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MMDEPLOY_API void mmdeploy_segmentor_release_result(mm_segment_t* results, int count);
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/**
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* @brief Destroy segmentor's handle
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* @param[in] handle segmentor's handle created by \ref mmdeploy_segmentor_create_by_path
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*/
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MMDEPLOY_API void mmdeploy_segmentor_destroy(mm_handle_t handle);
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/******************************************************************************
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* Experimental asynchronous APIs */
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MMDEPLOY_API int mmdeploy_segmentor_create_v2(mm_model_t model, const char* device_name,
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int device_id, mmdeploy_exec_info_t exec_info,
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mm_handle_t* handle);
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MMDEPLOY_API int mmdeploy_segmentor_create_input(const mm_mat_t* mats, int mat_count,
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mmdeploy_value_t* value);
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MMDEPLOY_API int mmdeploy_segmentor_apply_v2(mm_handle_t handle, mmdeploy_value_t input,
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mmdeploy_value_t* output);
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MMDEPLOY_API int mmdeploy_segmentor_apply_async(mm_handle_t handle, mmdeploy_sender_t input,
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mmdeploy_sender_t* output);
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MMDEPLOY_API int mmdeploy_segmentor_get_result(mmdeploy_value_t output, mm_segment_t** results);
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#ifdef __cplusplus
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}
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#endif
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#endif // MMDEPLOY_SEGMENTOR_H
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