4. API Reference

4.1. Handle

【Syntax】

typedef void *cvitdl_handle_t;
typedef void *cvitdl_service_handle_t;

【Description】

In TDL SDK, each module has its own handle, but when creating the cvitdl_service_handle_t module, the cvitdl_handle_t is required as an input.

4.2. CVI_TDL_Core

4.2.1. Common

4.2.1.1. CVI_TDL_CreateHandle

【Syntax】

CVI_S32 CVI_TDL_CreateHandle(cvitdl_handle_t *handle);

【Description】

Create handle to use TDL SDK. The TDL SDK automatically creates a VPSS Group.

【Parameter】

	Data Type	Parameter	Description
Input/Output	cvitdl_handle_t*	handle	Input handle pointer

4.2.1.2. CVI_TDL_CreateHandle2

【Syntax】

CVI_S32 CVI_TDL_CreateHandle2(cvitdl_handle_t *handle, const VPSS_GRP vpssGroupId, const CVI_U8 vpssDev);

【Description】

Create a handle to use the TDL SDK and use the specified VPSS Group ID and Dev ID to create a VPSS.

【Parameter】

	Data Type	Parameter	Description
Output	cvitdl_handle_t*	handle	Input handle pointer
Input	VPSS_GRP	vpssGroupId	Group ID used by VPSS
Input	CVI_U8	vpssDev	VPSS Device id

4.2.1.3. CVI_TDL_DestroyHandle

【Syntax】

CVI_S32 CVI_TDL_DestroyHandle(cvitdl_handle_t handle);

【Description】

Destroy the created handle cvitdl_handle_t. Destroy all open models at the same time

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Input handle pointer

4.2.1.4. CVI_TDL_GetModelPath

const char *CVI_TDL_GetModelPath(cvitdl_handle_t handle, CVI_TDL_SUPPORTED_MODEL_E model);

【Description】

Gets the model path of the model that has been set up internally to support. Release the filepath variable after use.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Input handle pointer
Input	CVI_TDL_SUPPORTED_MODEL_E	model	Model ID

【Output】

	Data Type	Description
Output	char*	Model path pointer

4.2.1.5. CVI_TDL_OpenModel

【Syntax】

CVI_S32 CVI_TDL_OpenModel(cvitdl_handle_t handle, CVI_TDL_SUPPORTED_MODEL_E model, const char *filepath);

【Description】

Enable and initialize the model.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Input handle pointer
Input	CVI_TDL_SUPPORTED_MODEL_E	model	Model index
Input	const char*	filepath	cvimodel model path

4.2.1.6. CVI_TDL_SetSkipVpssPreprocess

【Syntax】

CVI_S32 CVI_TDL_SetSkipVpssPreprocess(cvitdl_handle_t handle, CVI_TDL_SUPPORTED_MODEL_E model, bool skip);

【Description】

Disable preprocessing for a specified model.

By default, TDL SDK uses the internally created VPSS to preprocess the model (skip = false).

When skip is set to true, TDL SDK will not preprocess the model.

The model input must be preprocessed externally before being input to the model.

This is usually used when directly binding VPSS to VI and using only a single model.

CVI_TDL_GetVpssChnConfig can be used to obtain the VPSS preprocessing parameters for the model.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handel
Input	CVI_TDL_SUPPORTED_MODEL_E	model	Model ID
Input	bool	skip	Whether to skip pre-processing

4.2.1.7. CVI_TDL_GetSkipVpssPreprocess

【Syntax】

CVI_S32 CVI_TDL_GetSkipVpssPreprocess(cvitdl_handle_t handle, CVI_TDL_SUPPORTED_MODEL_E model, bool *skip);

【Description】

Inquire whether the model will be preprocessed within TDL SDK.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handel
Input	CVI_TDL_SUPPORTED_MODEL_E	model	Model ID
Output	bool*	skip	Inquire whether the model will be preprocessed within TDL SDK.

4.2.1.8. CVI_TDL_SetVpssThread

【Syntax】

CVI_S32 CVI_TDL_SetVpssThread(cvitdl_handle_t handle, CVI_TDL_SUPPORTED_MODEL_E model, const uint32_t thread);

【Description】

Set the thread ID used by a specific model. In TDL SDK, a VPSS thread represents a set of VPSS group settings. Thread 0 is used by default for the VPSS group used by the model. When multiple threads use the same TDL SDK handle for model inference, this API must be used to specify different VPSS threads to avoid race conditions.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handel
Input	CVI_TDL_SUPPORTED_MODEL_E	model	Model ID
Input	uint32_t	thread	Thread ID

4.2.1.9. CVI_TDL_SetVpssThread2

【Syntax】

CVI_S32 CVI_TDL_SetVpssThread2(cvitdl_handle_t handle, CVI_TDL_SUPPORTED_MODEL_E model, const uint32_t thread, const VPSS_GRP vpssGroupId, const CVI_U8 dev);

【Description】

Same as CVI_TDL_SetVpssThread. You can specify the Vpss Group ID.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handel
Input	CVI_TDL_SUPPORTED_MODEL_E	model	Model ID
Input	uint32_t	thread	Thread ID
Input	VPSS_GRP	vpssGroupId	VPSS Group id
Input	const CVI_U8	dev	VPSS Device id

4.2.1.10. CVI_TDL_GetVpssThread

【Syntax】

CVI_S32 CVI_TDL_GetVpssThread(cvitdl_handle_t handle, CVI_TDL_SUPPORTED_MODEL_E model, uint32_t *thread);

【Description】

Gets the thread id used by the model.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handel
Input	CVI_TDL_SUPPORTED_MODEL_E	model	Model ID
Output	uint32_t*	thread	VPSS thread ID

4.2.1.11. CVI_TDL_GetVpssGrpIds

【Syntax】

CVI_S32 CVI_TDL_GetVpssGrpIds(cvitdl_handle_t handle, VPSS_GRP **groups, uint32_t *num);

【Description】

Get all the VPSS group IDs used in the handle. After use, the groups must be released manually.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handel
Output	VPSS_GRP **	groups	Reference to a null pointer
Output	uint32_t*	num	Length of groups

4.2.1.12. CVI_TDL_SetVpssTimeout

【Syntax】

CVI_S32 CVI_TDL_SetVpssTimeout(cvitdl_handle_t handle, uint32_t timeout);

【Description】

Set the TDL SDK to wait for VPSS hardware timeout, with a default setting of 100ms. This setting applies to all VPSS threads within TDL SDK.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handel
Input	uint32_t	timeout	timeout

4.2.1.13. CVI_TDL_SetVBPool

【Syntax】

CVI_S32 CVI_TDL_SetVBPool(cvitdl_handle_t handle, uint32_t thread, VB_POOL pool_id);

【Description】

Specify a VBPool for the internal VPSS in TDL SDK. After being specified, the internal VPSS in TDL SDK will directly obtain memory from this pool. If this API is not used to specify a pool, the system will allocate one automatically.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle
Input	uint32_t	thread	VPSS thread ID
Input	VB_POOL	pool_id	VB Pool Id. If INVALID_POOLID is set, the Pool is not specified and is automatically allocated by the system.

4.2.1.14. CVI_TDL_GetVBPool

【Syntax】

CVI_S32 CVI_TDL_GetVBPool(cvitdl_handle_t handle, uint32_t thread, VB_POOL *pool_id);

【Description】

Get the VBPool ID used by the specified VPSS. If CVI_TDL_SetVBPool is not used to specify a pool, INVALID_POOLID will be returned.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle
Input	uint32_t	thread	VPSS thread ID
Output	VB_POOL*	pool_id	The current VB Pool Id is used.

4.2.1.15. CVI_TDL_CloseAllModel

【Syntax】

CVI_S32 CVI_TDL_CloseAllModel(cvitdl_handle_t handle);

【Description】

Unload all models that have been loaded in the handle.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle

4.2.1.16. CVI_TDL_CloseModel

【Syntax】

CVI_S32 CVI_TDL_CloseModel(cvitdl_handle_t handle, CVI_TDL_SUPPORTED_MODEL_E model);

【Description】

Dismount the specific model that has been loaded in the handle.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle
Input	CVI_TDL_SUPPORTED_MODEL_E	model	Model index

4.2.1.17. CVI_TDL_Dequantize

【Syntax】

CVI_S32 CVI_TDL_Dequantize(const int8_t *quantizedData, float *data, const uint32_t bufferSize, const float dequantizeThreshold);

【Description】

Dequantize int8 values to float.

【Parameter】

	Data Type	Parameter	Description
Input	const int8_t*	quantizedData	Int8 data
Output	float*	data	Float output data
Input	const uint32_t	bufferSize	Int8 data quantity
Input	const float	dequantizeThreshold	Quantization threshold

4.2.1.18. CVI_TDL_ObjectNMS

【Syntax】

CVI_S32 CVI_TDL_ObjectNMS(const cvtdl_object_t *obj, cvtdl_object_t *objNMS, const float threshold, const char method);

【Description】

Run the Non-Maximum Suppression algorithm for bboxes in cvtdl_object_t.

【Parameter】

	Data Type	Parameter	Description
Input	const cvtdl_object_t*	obj	Object Meta of the NMS
Output	cvtdl_object_t*	objNMS	Result after NMS
Input	const float	threshold	IOU threshold
Input	const char	method	‘u’: Intersection over Union ‘m’: Intersection over min area

4.2.1.19. CVI_TDL_FaceNMS

【Syntax】

CVI_S32 CVI_TDL_ObjectNMS(const cvtdl_face_t *face, cvtdl_face_t *faceNMS, const float threshold, const char method);

【Description】

Run the Non-Maximum Suppression algorithm for bboxes in cvtdl_face_t.

【Parameter】

	Data Type	Parameter	Description
Input	const cvtdl_face_t*	face	face meta of the NMS
Output	cvtdl_face_t*	faceNMS	Result after NMS
Input	const float	threshold	IOU threshold
Input	const char	method	‘u’: Intersection over Union ‘m’: Intersection over min area

4.2.1.20. CVI_TDL_FaceAlignment

【Syntax】

CVI_S32 CVI_TDL_FaceAlignment(VIDEO_FRAME_INFO_S *inFrame, const uint32_t metaWidth, const uint32_t metaHeight, const cvtdl_face_info_t *info, VIDEO_FRAME_INFO_S *outFrame, const bool enableGDC);

【Description】

InsightFace Alignment parameter was used to perform Face Alignment for inFrame image Face.

【Parameter】

	Data Type	Parameter	Description
Input	VIDEO_FRAME_INFO_S*	inFrame	Input image
Input	const uint32_t metaWidth	metaWidth	The width of the frame in Info
Input	const uint32_t metaHeight	metaHeight	The height of the frame in Info
Input	const cvtdl_face_info_t*	info	Face info
Output	VIDEO_FRAME_INFO_S*	outFrame	The face image after face alignment.
Input	const bool	enableGDC	Whether to use GDC hardware

4.2.1.21. CVI_TDL_CropImage

【Syntax】

CVI_S32 CVI_TDL_CropImage(VIDEO_FRAME_INFO_S *srcFrame, cvtdl_image_t *dst, cvtdl_bbox_t *bbox, bool cvtRGB888);

【Description】

Retrieves the Bbox-specified region image from the srcFrame image.

【Parameter】

	Data Type	Parameter	Description
Input	VIDEO_FRAME_INFO_S*	srcFrame	Input image, currently only supports RGB packed format.
Output	cvtdl_image_t*	dst	Output image.
Input	cvtdl_bbox_t*	bbox	Bounding box
Input	bool	cvtRGB888	Whether to convert to RGB888 format for output.

4.2.1.22. CVI_TDL_CropImage_Face

【Syntax】

CVI_S32 CVI_TDL_CropImage_Face(VIDEO_FRAME_INFO_S *srcFrame, cvtdl_image_t *dst, cvtdl_face_info_t *face_info, bool align, bool cvtRGB888);

【Description】

Extract the image within the specified face bbox from the srcFrame image.

【Parameter】

	Data Type	Parameter	Description
Input	VIDEO_FRAME_INFO_S*	srcFrame	Input image, currently only supports RGB packed format.
Output	cvtdl_image_t*	dst	Output image.
Input	cvtdl_face_info_t*	face_info	Specified face info.
Input	bool	align	Whether to perform face alignment. Using InsightFace alignment parameters.
Input	bool	cvtRGB888	Whether to convert the output format to RGB888.

4.2.1.23. CVI_TDL_SoftMax

【Syntax】

CVI_S32 CVI_TDL_SoftMax(const float *inputBuffer, float *outputBuffer, const uint32_t bufferSize);

【Description】

Compute Softmax for the inputBuffer.

【Parameter】

	Data Type	Parameter	Description
Input	const float*	inputBuffer	Buffer to be softmaxed
Output	const float*	outputBuffer	resulting softmax buffer
Input	const uint32_t	bufferSize	buffer size

4.2.1.24. CVI_TDL_GetVpssChnConfig

【Syntax】

CVI_S32 CVI_TDL_GetVpssChnConfig(cvitdl_handle_t handle, CVI_TDL_SUPPORTED_MODEL_E model, const CVI_U32 frameWidth, const CVI_U32 frameHeight, const CVI_U32 idx, cvtdl_vpssconfig_t *chnConfig);

【Description】

Get the VPSS parameters used in model pre-processing.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle
Input	CVI_TDL_SUPPORTED_MODEL_E	model	Model ID
Input	CVI_U32	frameWidth	Input image width
Input	CVI_U32	fra meHeight	Input image height
Input	CVI_U32	idx	The input index of the model
Output	cvtdl_vpssconfig_t*	chnConfig	The specified parameter value to be returned.

4.2.1.25. CVI_TDL_Free

CVI_TDL_Free(X)

【Description】

Free the data structure generated by the model results. Some data structures may contain sub-items allocated by malloc, so they need to be released.

【Parameter】

The following are the supported input variables:

• cvtdl_feature_t

• cvtdl_pts_t

• cvtdl_tracker_t

• cvtdl_face_info_t

• cvtdl_face_t

• cvtdl_object_info_t

• cvtdl_object_t

4.2.1.26. CVI_TDL_CopyInfo

CVI_TDL_CopyInfo(IN, OUT)

【Description】

Generic API for copying CVI_TDL structures. This API will allocate the pointer memory for the copied structure and perform a complete copy.

【Parameter】

	Data Type	Parameter	Description
Input	Support type: cvtdl_face_info_t cvtdl_object_info_t cvtdl_image_t	IN	Replication source
Output	Support type: cvtdl_face_info_t cvtdl_object_info_t cvtdl_image_t	OUT	Replication purpose

4.2.1.27. CVI_TDL_RescaleMetaCenter

【Description】

Rescale the coordinates in the structure to the size of the input image with padding on top, bottom, left, and right.

【Parameter】

Here are the supported input variables:

• cvtdl_face_t

• cvtdl_object_t

4.2.1.28. CVI_TDL_RescaleMetaRB

【Description】

In the padding image, the coordinates in the structure are restored to the same size as the input image.

【Parameter】

Here are the supported input variables:

• cvtdl_face_t

• cvtdl_object_t

4.2.1.29. getFeatureTypeSize

int getFeatureTypeSize(feature_type_e type);

【Description】

Gets the unit size of the eigenvalue.

【Parameter】

	Data Type	Parameter	Description
Input	feature_type_e	type	Unit

【Output】

	Data Type	Parameter	Description
Output	int	X	The unit size is byte

4.2.1.30. CVI_TDL_SetModelThreshold

【Syntax】

CVI_S32 CVI_TDL_SetModelThreshold(cvitdl_handle_t handle, CVI_TDL_SUPPORTED_MODEL_E model, float threshold);

【Description】

Set the threshold value for the model, currently only supported for models of the detection type.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle
Input	CVI_TDL_SUPPORTED_MODEL_E	model	Model index
Input	float	threshold	Threshold (0.0~1.0)

4.2.1.31. CVI_TDL_GetModelThreshold

【Syntax】

CVI_S32 CVI_TDL_GetModelThreshold(cvitdl_handle_t handle, CVI_TDL_SUPPORTED_MODEL_E model, float *threshold);

【Description】

Take out the model threshold, and only the Detection type model is supported at present.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle
Input	CVI_TDL_SUPPORTED_MODEL_E	model	Model index
Output	float*	threshold	Threshold

4.2.2. Object Detection

4.2.2.1. CVI_TDL_Detection

【Syntax】

CVI_S32 CVI_TDL_Detection(const cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, CVI_TDL_SUPPORTED_MODEL_E model_id, cvtdl_object_t *obj)

【Description】

Use the specified model ID to call the corresponding target detection algorithm.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle
Input	VIDEO_FRAME_INFO_S*	frame	Input image
Input	CVI_TDL_SUPPORTED_MODEL_E	model_id	model id
Output	cvtdl_object_t*	obj	Detected objects

【Optional model ID list】

model_id	description
CVI_TDL_SUPPORTED_MODEL_YOLOV3	YoloV3
CVI_TDL_SUPPORTED_MODEL_YOLOV5	YoloV5
CVI_TDL_SUPPORTED_MODEL_YOLOV6	YoloV6
CVI_TDL_SUPPORTED_MODEL_YOLOV7	YoloV7
CVI_TDL_SUPPORTED_MODEL_YOLOV8 _DETECTION	YoloV8
CVI_TDL_SUPPORTED_MODEL_YOLOX	Yolo X
CVI_TDL_SUPPORTED_MODEL_PPYOLOE	PP-YoloE
CVI_TDL_SUPPORTED_MODEL_YOLOV10 _DETECTION	YoloV10
CVI_TDL_SUPPORTED_MODEL_YOLOV8 _HARDHAT	YOLOV8 Ciffic detection
CVI_TDL_SUPPORTED_MODEL_HAND _DETECTION	hand detection
CVI_TDL_SUPPORTED_MODEL_PERSON _PETS_DETECTION	Person, cat, dog target detection
CVI_TDL_SUPPORTED_MODEL_PERSON _VEHICLE_DETECTION	Person and car target detection
CVI_TDL_SUPPORTED_MODEL_HAND _FACE_PERSON_DETECTION	Person, face, hand target detection
CVI_TDL_SUPPORTED_MODEL_HEAD _PERSON_DETECTION	Person, face, head target detection
CVI_TDL_SUPPORTED_MODEL_MOBILEDETV2 _COCO80	Mobiledet model trained on the COCO80 dataset
CVI_TDL_SUPPORTED_MODEL_MOBILEDETV2 _VEHICLE	MOBILEDET model of vehicle detection
CVI_TDL_SUPPORTED_MODEL_MOBILEDETV2 _PEDESTRIAN	Pedestrian detection MobileDET model

4.2.3. Face detection

4.2.3.1. CVI_TDL_FaceDetection

【Syntax】

CVI_S32 CVI_TDL_FaceDetection(const cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, CVI_TDL_SUPPORTED_MODEL_E model_id, cvtdl_face_t *face_meta)

【Description】

Use the specified model to detect the face.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle
Input	VIDEO_FRAME_INFO_S*	frame	Input image
Input	CVI_TDL_SUPPORTED_MODEL_E	model_id	model id
Output	cvtdl_face_t*	faces	The faces we detected

【Optional model ID list】

model_id	description
CVI_TDL_SUPPORTED_MODEL_RETINAFACE	Face detection (RetinaFace), Caffe reasoning framework
CVI_TDL_SUPPORTED_MODEL_SCRFDFACE	ScrFDFace
CVI_TDL_SUPPORTED_MODEL_RETINAFACE _IR	Infrared face detection (Reti-naFace)，PYTORCH reasoning framework
CVI_TDL_SUPPORTED_MODEL _FACEMASKDETECTION	RetinafaceYolox，Detect the face of the mask.Face score stored in “faces->info[i].bbox.score”，Wearing mask face score stored in “faces->info[i].mask_score”。

4.2.3.2. CVI_TDL_FaceLandmarkerDet2

【Syntax】

CVI_S32 CVI_TDL_FaceLandmarkerDet2(cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_face_t *faces);

【Description】

Evaluate the face punctuation of the person in the Faces structure.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle
Input	VIDEO_FRAME_INFO_S*	frame	The faces we detected
Output	cvtdl_face_t*	faces	faces punctuation

4.2.3.3. CVI_TDL_FaceQuality

【Syntax】

CVI_S32 CVI_TDL_FaceQuality(cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_face_t *faces, bool *skip);

【Description】

Evaluate the quality of the faces in the given “faces” structure and detect their angles. The quality is affected by the clarity of the face and whether it is occluded. The quality score of a face is stored in “faces->info[i].face_quality”, while the angle is stored in “faces->info[i].head_pose”.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	Input image
Input	cvtdl_face_t*	face	The faces we detected
Input	bool*	skip	Bool array: Specifies the face quality required for the face. NULL indicates that all faces do this.

4.2.3.4. CVI_TDL_MaskClassification

【Syntax】

CVI_S32 CVI_TDL_MaskClassification(cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_face_t *face);

【Description】

Check if all faces in the input faces are masked faces. A face detection must be performed before calling this interface. The score of masked face is stored in faces->info[i].mask_score.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	Input image
Input	cvtdl_face_t*	faces	The faces we detected

4.2.4. Face Recognition.

4.2.4.1. CVI_TDL_FaceRecognition

【Syntax】

CVI_S32 CVI_TDL_FaceRecognition(cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_face_t *faces);

【Description】

Extract facial features. This interface will extract features for all faces in the face variable and store them in faces->info[i].feature.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	Input image
Input/Output	cvtdl_face_t*	faces	The faces we detected

4.2.4.2. CVI_TDL_FaceAttribute_cls

【Syntax】

CVI_S32 CVI_TDL_FaceAttribute_cls(cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_face_t *faces);

【Description】

Face attribute classification. This interface will classify the attributes of the face in the picture.

Face attributes include: gender, age, whether to wear glasses and whether to wear a mask， the results are placed infaces->info[i].gender_score, faces->info[i].age, faces->info[i].glass, faces->info[i].mask_score。

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	input image
Input/Output	cvtdl_face_t*	faces	face attribute

4.2.5. Gesture Recognition

4.2.5.1. CVI_TDL_HandClassification

【Syntax】

CVI_S32 CVI_TDL_HandClassification(const cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_object_t *meta);

【Description】

This gesture classification algorithm is used for recognizing gestures on the specified ‘frame’. The results will be stored in ‘meta->info[i].name’ and ‘meta->info[i].bbox.score’.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	The handle for the TDL model.
Input	VIDEO_FRAME_INFO_S*	frame	The input image.
Input/Output	cvtdl_object_t*	meta	Detected hand bounding boxes and gesture classifications.

4.2.5.2. CVI_TDL_HandKeypoint

【Syntax】

CVI_S32 CVI_TDL_HandKeypoint(const cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_handpose21_meta_ts *meta);

【Description】

This function is used for outputting hand key points and storing them in ‘meta->info[i]’.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	The handle for the TDL model.
Input	VIDEO_FRAME_INFO_S*	frame	Input image.
Input/Output	cvtdl_handpose21_meta_ts*	meta	Detected hand bounding boxes and 21 hand key points.

4.2.5.3. CVI_TDL_HandKeypointClassification

【Syntax】

CVI_S32 CVI_TDL_HandKeypointClassification(const cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_handpose21_meta_t *meta);

【Description】

This function is used for extracting hand keypoint information. The keypoint information will be stored in ‘meta->info[i]’.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	The handle for the TDL model.
Input	VIDEO_FRAME_INFO_S*	frame	Input 21 key points of the hand. The x and y coordinates are sequentially stored in ‘frame->stVFrame.pu8VirAddr[0]’, ‘frame->stVFrame.u32Height=1’, ‘frame->stVFrame.u32Width=42*sizeof(float)’.
Output	cvtdl_handpose21_meta_t*	meta	The output of hand gestures, including the gesture label in ‘meta->label’ and the gesture score in ‘meta->score’.

4.2.6. Object Tracking

4.2.6.1. CVI_TDL_DeepSORT_Init

【Syntax】

CVI_S32 CVI_TDL_DeepSORT_Init(const cvitdl_handle_t handle, bool use_specific_counter);

【Description】

Initialize the DeepSORT algorithm.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	bool	use_specific_counter	Whether each object class is assigned its own id

4.2.6.2. CVI_TDL_DeepSORT_GetDefaultConfig

【Syntax】

CVI_S32 CVI_TDL_DeepSORT_GetDefaultConfig(cvtdl_deepsort_config_t *ds_conf);

【Description】

Get the default parameters for DeepSORT.

【Parameter】

	Data Type	Parameter	Description
Input	cvtdl_deepsort_config_t*	ds_conf	DeepSORT parameter

4.2.6.3. CVI_TDL_DeepSORT_SetConfig

【Syntax】

CVI_S32 CVI_TDL_DeepSORT_SetConfig(const cvitdl_handle_t handle , cvtdl_deepsort_config_t *ds_conf, int cvi_tdl_obj_type, bool show_config);

【Description】

Setting DeepSORT parameters.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle
Input	cvtdl_deepsort_config_t*	ds_conf	DeepSORT parameter
Input	int	cvi_tdl_obj_type	“-1” indicates default settings. Non-negative values indicate setting parameters for cvi_tdl_obj_type.
Input	bool	show_config	Display Settings.

4.2.6.4. CVI_TDL_DeepSORT_GetConfig

【Syntax】

CVI_S32 CVI_TDL_DeepSORT_GetConfig(const cvitdl_handle_t handle , cvtdl_deepsort_config_t *ds_conf, int cvi_tdl_obj_type);

【Description】

To inquire about the DeepSORT parameters that have been set, please call the corresponding function or method provided by the DeepSORT implementation being used in your system. The specific method or function name may vary depending on the DeepSORT implementation you are using.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	TDL SDK handle
Output	cvtdl_deepsort_config_t*	ds_conf	DeepSORT parameter
Input	int	cvi_tdl_obj_type	-1 indicates that the default parameter is obtained. Non-1 values represent parameters set against the category of cvi_tdl_obj_type

4.2.6.5. CVI_TDL_DeepSORT_CleanCounter

【Syntax】

CVI_S32 CVI_TDL_DeepSORT_CleanCounter(const cvitdl_handle_t handle);

【Description】

Reset the ID counter recorded in DeepSORT.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle

4.2.6.6. CVI_TDL_DeepSORT_Obj

【Syntax】

CVI_S32 CVI_TDL_DeepSORT_Obj(const cvitdl_handle_t handle, cvtdl_object_t *obj, cvtdl_tracker_t *tracker, bool use_reid);

【Description】

Track objects and update the tracker status. This interface will assign a unique ID to each Object, which can be obtained from obj->info[i].unique_id. The tracker_t will record the tracking status of each object and the current predicted Bounding Box. If you want to use object appearance features for tracking, set use_reid to true, and use CVI_TDL_OSNet for feature extraction before tracking. Currently, feature extraction only supports human-shaped objects.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	cvtdl_object_t*	obj	The object to be tracked
Output	cvtdl_tracker_t*	tracker	The trace state of the object
Input	bool	use_reid	Whether object appearance characteristics are used for tracing

4.2.6.7. CVI_TDL_DeepSORT_Face

【Syntax】

CVI_S32 CVI_TDL_DeepSORT_Face(const cvitdl_handle_t handle, cvtdl_face_t *face, cvtdl_tracker_t *tracker, bool use_reid);

【Description】

Track faces and update the Tracker state. This function assigns a unique ID to each face, which can be retrieved from face->info[i].unique_id. The tracker_t will record the tracking status and the predicted bounding box of each face. If you want to use face features for tracking, set use_reid to true and call CVI_TDL_FaceRecognition to compute face features before tracking.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	cvtdl_face_t*	face	The face you want to track
Output	cvtdl_tracker_t*	tracker	The tracking state of a face
Input	bool	use_reid	Whether to use appearance characteristics for tracing. Currently, only false can be set

4.2.7. Motion Detection

4.2.7.1. CVI_TDL_Set_MotionDetection_Background

【Syntax】

CVI_S32 CVI_TDL_Set_MotionDetection_Background(const cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame);

【Description】

Set the background for Motion Detection. The first time this function is called, it will initialize the Motion Detection module. Subsequent calls will only update the background. The Motion Detection module in TDL SDK uses frame difference method.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle
Input	VIDEO_FRAME_INFO_S*	frame	Background

4.2.7.2. CVI_TDL_MotionDetection

【Syntax】

CVI_S32 CVI_TDL_MotionDetection(const cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_object_t *objects, uint8_t threshold, double min_area);

【Description】

Detect objects using frame difference method. The detection results will be stored in “objects”.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	image
Output	cvtdl_object_t*	object	Motion detection result
Input	uint8_t	threshold	The frame difference threshold must be 0-255
Input	double	min_area	Minimum object area (Pixels). Filters out objects smaller than this value.

4.2.7.3. CVI_TDL_Set_MotionDetection_ROI

【Syntax】

CVI_S32 CVI_TDL_Set_MotionDetection_ROI(const cvitdl_handle_t handle, MDROI_t *roi_s);

【Description】

This function is used for object detection using frame difference method. The detection results will be stored in ‘objects’.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	The handle for the TDL model.
Input	MDROI_t*	roi_s	Set the region of interest for motion detection.

4.2.8. License Plate Recognition

4.2.8.1. CVI_TDL_LicensePlateDetection

【Syntax】

CVI_S32 CVI_TDL_LicensePlateDetection(cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_object_t *vehicle_meta);

【Description】

License plate detection. Before calling this API, vehicle detection must be performed first. This algorithm will perform license plate detection on the already detected objects. The location of the license plate will be stored in obj->info[i].vehicle_properity->license_pts.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	image
Input	cvtdl_object_t*	obj	Object (vehicle) detection result

4.2.8.2. CVI_TDL_LicensePlateRecognition_TW

CVI_S32 CVI_TDL_LicensePlateRecognition_TW(const cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_object_t *obj);

【Description】

Perform license plate recognition (Taiwan) on all vehicles in the input obj. Prior to calling this API, CVI_TDL_LicensePlateDetection must be called once for license plate detection. The license plate number is stored in obj->info[i].vehicle_properity->license_char.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	The input image
Input	cvtdl_object_t*	obj	License plate detection results

4.2.8.3. CVI_TDL_LicensePlateRecognition_CN

CVI_S32 CVI_TDL_LicensePlateRecognition_CN(const cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_object_t *obj);

【Description】

Perform license plate recognition (Mainland China) for all vehicles in the input obj. CVI_TDL_LicensePlateDetection must be called before calling this API for license plate detection. The license plate number is stored in obj->info[i].vehicle_properity->license_char.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	image
Input/Output	cvtdl_object_t*	obj	icense plate detection results

4.2.9. Liveness Detection

4.2.9.1. CVI_TDL_IrLiveness

【Syntax】

CVI_S32 CVI_TDL_IrLiveness(const cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *irFrame, cvtdl_face_t *ir_faces);

【Description】

This function performs IR (infrared) monocular liveness detection.

It determines whether the detected faces in ‘ir_faces’ are real or not.

The liveness scores for each face will be stored in ‘ir_faces->info[i].liveness_score’.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle
Input	VIDEO_FRAME_INFO_S*	irFrame	The ir image
Input/Output	cvtdl_face_t*	ir_faces	Detected IR face/ liveness score

4.2.10. Pose Estimation

4.2.10.1. CVI_TDL_PoseDetection

【Syntax】

CVI_S32 CVI_TDL_PoseDetection(const cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, CVI_TDL_SUPPORTED_MODEL_E model_id, cvtdl_object_t *obj_meta)

【Description】

Use the model ID to call the attitude detection algorithm to detect 17 key points of the human body.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	input image
Input	CVI_TDL_SUPPORTED_MODEL_E	model_id	model id
Output	cvtdl_object_t*	obj_meta	The detected objects and key points

【Optional model ID list】

id	name	description
34	CVI_TDL_SUPPORTED_MODEL_YOLOV8POSE	Optional model ID list
35	CVI_TDL_SUPPORTED_MODEL_SIMCC_POSE	simcc model

4.2.11. Semantic Segmentation

4.2.11.1. CVI_TDL_YoloV8_Seg

【Syntax】

CVI_S32 CVI_TDL_YoloV8_Seg(const cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_object_t *obj_meta);

【Description】

Use the YOLOV8 model for example segmentation.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	input image
Output	cvtdl_object_t*	obj_meta	The detected object and boundary point

4.2.11.2. CVI_TDL_Topformer_Seg

【Syntax】

CVI_S32 CVI_TDL_Topformer_Seg(const cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_seg_t *seg_ann);

【Description】

Use the TopFormer model for semantic segmentation.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	input image
Output	cvtdl_seg_t *	seg_ann	the id of input image

4.2.12. Fall Detection

4.2.12.1. CVI_TDL_Fall_Monitor

【Syntax】

CVI_S32 CVI_TDL_Fall_Monitor(cvitdl_handle_t handle, cvtdl_object_t *obj);

【Description】

To judge the fall state, you need to call the attitude detection model before use.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Output	cvtdl_object_t*	obj	the result of fall detection

4.2.13. Driver Fatigue Detection

4.2.13.1. CVI_TDL_FaceLandmarker

【Syntax】

CVI_S32 CVI_TDL_FaceLandmarker(cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_face_t *faces);

【Description】

Before using this API, the face detection API should be called to obtain the detection result of 106 facial landmarks, which should be placed in face->dms[i].landmarks_106 and update the 5 facial landmarks in face->dms[i].landmarks_5.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	Input image
Input	cvtdl_face_t*	face	Human face

4.2.13.2. CVI_TDL_EyeClassification

【Syntax】

CVI_S32 CVI_TDL_EyeClassification (cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_face_t *faces);

【Description】

The closed state of the eyes is determined based on the results of face detection and facial landmark detection. The scores of the right and left eyes are stored in face->dms[i].reye_score and face->dms[i].leye_score, respectively.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	Input image
Input	cvtdl_face_t*	face	Human face

4.2.13.3. CVI_TDL_YawnClassification

【Syntax】

CVI_S32 CVI_TDL_YawnClassification (cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, cvtdl_face_t *faces);

【Description】

Detect yawning based on the results of face detection and facial landmark detection. CVI_FaceRecognition must be called first to obtain the results of face detection and facial landmark detection. The yawning score will be placed in face->dms[i].yawn_score, ranging from 0.0 to 1.0.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	Input image
Input	cvtdl_face_t*	face	Human face

4.2.14. Sound Classification

4.2.14.1. CVI_TDL_SoundClassification

【Syntax】

CVI_S32 CVI_TDL_SoundClassification(cvitdl_handle_t handle, VIDEO_FRAME_INFO_S *frame, int *index);

【Description】

Classify the audio in the frame into different categories and output the scores of each category in sorted order.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	frame	Input image
Input	int*	index	Scores in each category

4.2.14.2. CVI_TDL_Get_SoundClassification_ClassesNum

【Syntax】

CVI_S32 CVI_TDL_Get_SoundClassification_ClassesNum(cvitdl_handle_t handle);

【Description】

Get the number of audio categories.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle

【Output】

	Data Type	Description
Output	int	The number of category

4.2.14.3. CVI_TDL_Set_SoundClassification_Threshold

【Syntax】

CVI_S32 CVI_TDL_Set_SoundClassification_Threshold(cvitdl_handle_t handle, const float th);

【Description】

Set the audio category threshold.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_handle_t	handle	Handle
Input	const float	th	Similarity threshold, the similarity higher than this threshold will be taken out.

4.3. CVI_TDL_Service

4.3.1. Common

4.3.1.1. CVI_TDL_Service_CreateHandle

【Syntax】

CVI_S32 CVI_TDL_Service_CreateHandle(cvitdl_service_handle_t *handle, cvtdl_handle tdl_handle);

【Description】

Create a Service handle

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t*	handle	handle
Input	cvitdl_handle_t	tdl_handle	cvi_tdl_core handle

4.3.1.2. CVI_TDL_Service_DestroyHandle

【Syntax】

CVI_S32 CVI_TDL_Service_DestroyHandle(cvitdl_service_handle_t *handle);

【Description】

Destroy the Service handle

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t*	handle	Handle

4.3.1.3. CVI_TDL_Service_Polygon_SetTarget

【Syntax】

CVI_S32 CVI_TDL_Service_Polygon_SetTarget(cvitdl_service_handle_t handle, const cvtdl_pts_t *pts);

【Description】

Set up a region of interest for intrusion detection with pts as the coordinates of the convex polygon. The order of the points should be clockwise or counterclockwise. Call CVI_TDL_Service_Polygon_Intersect to check if a bounding box intersects with the defined region.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t	handle	handle
Input	cvtdl_pts_t*	pts	Convex polygon point

4.3.1.4. CVI_TDL_Service_Polygon_Intersect

【Syntax】

CVI_S32 CVI_TDL_Service_Polygon_Intersect(cvitdl_service_handle_t handle, const cvtdl_bbox_t *bbox, bool *has_intersect);

【Description】

Detect if a given bounding box is within the targeted intrusion area previously set by calling CVI_TDL_Service_Polygon_SetTarget.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t	handle	handle
Input	cvtdl_bbox_t*	bbox	Bounding box
Output	bool*	ha s_intersect	Intrusion or not

4.3.1.5. CVI_TDL_Service_RegisterFeatureArray

【Syntax】

CVI_S32 CVI_TDL_Service_RegisterFeatureArray(cvitdl_service_handle_t handle, const cvtdl_service_feature_array_t featureArray, const cvtdl_service_feature_matching_e method);

【Description】

Register a feature database by precomputing and loading the features in the featureArray into memory.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t	handle	handle
Input	const cvtdl_service_feature_array_t	featureArray	Feature array structure
Input	const cvtdl_service_feature_matching_e	method	Currently, only COS_SIMILARITY is supported

4.3.1.6. CVI_TDL_Service_CalculateSimilarity

【Syntax】

CVI_S32 CVI_TDL_Service_CalculateSimilarity(cvitdl_service_handle_t handle, const cvtdl_feature_t *feature_rhs, const cvtdl_feature_t *feature_lhs, float *score);

【Description】

Compute the cosine similarity between two feature vectors using the RISC-V. The cosine similarity is calculated using the following formula:

\[sim(\theta) = \frac{A \bullet B}{\left\| A \right\| \bullet \left\| B \right\|} = \frac{\sum_{i = 1}^{n}{A_{i}B_{i}}}{\sqrt{\sum_{i = 1}^{n}A_{i}^{2}}\sqrt{\sum_{i = 1}^{n}B_{i}^{2}}}\]

The Cosine Similarity between two features of length n is calculated using the following formula. Currently, only INT8 features are supported.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t	handle	handle
Input	const cvtdl_feature_t*	feature_rhs	The first feature
Input	const cvtdl_feature_t*	feature_lhs	Second feature
Output	float*	score	Similarity

4.3.1.7. CVI_TDL_Service_ObjectInfoMatching

【Syntax】

CVI_S32 CVI_TDL_Service_ObjectInfoMatching(cvitdl_service_handle_t handle, const cvtdl_object_info_t *object_info, const uint32_t topk, float threshold, uint32_t *indices, float *sims, uint32_t *size);

【Description】

Compute the cosine similarity between the object feature in object_info and the pre-calculated object features in the registered object feature library. Retrieve the top-K similarities that are greater than threshold. The calculation formula is as follows:

\[sim(\theta) = \frac{A \bullet B}{\left\| A \right\| \bullet \left\| B \right\|} = \frac{\sum_{i = 1}^{n}{A_{i}B_{i}}}{\sqrt{\sum_{i = 1}^{n}A_{i}^{2}}\sqrt{\sum_{i = 1}^{n}B_{i}^{2}}}\]

Calculate the Cosine Similarity between the object feature in object_info and the registered object feature in the feature library.

The top-K similarities greater than the given threshold will be returned.

If the number of features in the library is less than 1000, RISC-V will be used for calculation, otherwise TPU will be launched for computation.

Feature registration can be done through CVI_TDL_Service_RegisterFeatureArray.

Note that the feature length n must be consistent and INT8 features are currently supported.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t	handle	handle
Input	const cvtdl_object_info_t*	object_info	Object Info
Input	const uint32_t	topk	Take topk similarity
Output	float	threshold	Similarity threshold, above which the similarity will be taken out
Output	uint32_t*	indices	The Index of the similarity that satisfies the condition in the library
Output	float*	sims	The similarity of the condition
Output	uint32_t*	size	The number of similarities that are finally extracted

4.3.1.8. CVI_TDL_Service_FaceInfoMatching

【Syntax】

CVI_S32 CVI_TDL_Service_FaceInfoMatching(cvitdl_service_handle_t handle, const cvtdl_face_info_t *face_info, const uint32_t topk, float threshold, uint32_t *indices, float *sims, uint32_t *size);

【Description】

Calculate the Cosine Similarity between the face features in face_info and the registered face feature library, and output the top-K similarities that are greater than the given threshold.

The calculation formula is as follows:

\[sim(\theta) = \frac{A \bullet B}{\left\| A \right\| \bullet \left\| B \right\|} = \frac{\sum_{i = 1}^{n}{A_{i}B_{i}}}{\sqrt{\sum_{i = 1}^{n}A_{i}^{2}}\sqrt{\sum_{i = 1}^{n}B_{i}^{2}}}\]

Where n is the feature length.

If the number of features in the library is less than 1000, the calculation will be performed on the RISC-V.

Otherwise, the TPU will be used for calculation.

Feature registration requires calling CVI_TDL_Service_RegisterFeatureArray.

Currently, only INT8 features are supported.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t	handle	handle
Input	const cvtdl_face_info_t*	face_info	Face info
Input	const uint32_t	topk	Take topk similarity
Output	float	threshold	Similarity threshold, above which the similarity will be taken out
Output	uint32_t*	indices	The Index of the similarity that satisfies the condition in the library
Output	float*	sims	The similarity of the condition
Output	uint32_t*	size	The number of similarities that are finally extracted

4.3.1.9. CVI_TDL_Service_RawMatching

【Syntax】

CVI_S32 CVI_TDL_Service_RawMatching(cvitdl_service_handle_t handle, const void *feature, const feature_type_e type, const uint32_t topk, float threshold, uint32_t *indices, float *scores, uint32_t *size);

【Description】

Compute the Cosine Similarity between a given feature and the registered feature library.

Retrieve the top-K similarities greater than the specified threshold.

The computation is done using the following formula:

\[sim(\theta) = \frac{A \bullet B}{\left\| A \right\| \bullet \left\| B \right\|} = \frac{\sum_{i = 1}^{n}{A_{i}B_{i}}}{\sqrt{\sum_{i = 1}^{n}A_{i}^{2}}\sqrt{\sum_{i = 1}^{n}B_{i}^{2}}}\]

where n is the length of the feature.

If the number of registered feature arrays is less than 1000, the calculation will be performed on RISC-V.

Otherwise, TPU will be launched for calculation.

The feature arrays need to be registered using CVI_TDL_Service_RegisterFeatureArray.

Unlike CVI_TDL_Service_FaceInfoMatching and CVI_TDL_Service_ObjectInfoMatching, this API directly uses the feature array for comparison and does not require cvtdl_face_info_t or cvtdl_object_info_t to be passed in.

This API limits the feature type to be the same as the feature type in the feature arrays.

Currently, only INT8 features are supported.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t	handle	handle
Input	const void*	feature	Feature array
Input	const feature_type_e	type	Feature type, currently only TYPE_INT8 is supported
Input	const uint32_t	topk	Take topk similarity
Output	float	threshold	Similarity threshold, above which the similarity will be taken out
Output	uint32_t*	indices	The Index of the similarity that satisfies the condition in the library
Output	float*	scores	The similarity of the condition
Output	uint32_t*	size	The number of similarities that are finally extracted

4.3.1.10. CVI_TDL_Service_FaceAngle

【Syntax】

CVI_S32 CVI_TDL_Service_FaceAngle(const cvtdl_pts_t *pts, cvtdl_head_pose_t *hp);

【Description】

Estimate the pose of a single face.

【Parameter】

	Data Type	Parameter	Description
Input	cvtdl_pts_t*	pts	Face landmark
Output	cvtdl_head_pose_t*	hp	Face posture

4.3.1.11. CVI_TDL_Service_FaceAngleForAll

【Syntax】

CVI_S32 CVI_TDL_Service_FaceAngleForAll(const cvtdl_face_t *meta);

【Description】

Calculate pose for multiple faces

【Parameter】

	Data Type	Parameter	Description
Input	cvtdl_face_t*	meta	Face data

4.3.2. Image Scaling

4.3.2.1. CVI_TDL_Service_FaceDigitalZoom

【Syntax】

CVI_S32 CVI_TDL_Service_FaceDigitalZoom(

cvitdl_service_handle_t handle,

const VIDEO_FRAME_INFO_S *inFrame,

const cvtdl_face_t *meta,

const float face_skip_ratio,

const float trans_ratio,

const float padding_ratio,

VIDEO_FRAME_INFO_S *outFrame);

【Description】

Resizing (zooming in) the detected face.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	inFrame	Input image
Input	cvtdl_face_t*	meta	Face data
Input	float	face_skip_ratio	Neglect ratio
Input	float	trans_ratio	Amplification ratio
Input	float	padding_ratio	Expand bounding box ratio
Output	VIDEO_FRAME_INFO_S*	outFrame	Output image

4.3.2.2. CVI_TDL_Service_ObjectDigitalZoom

【Syntax】

CVI_S32 CVI_TDL_Service_ObjectDigitalZoom(cvitdl_service_handle_t handle,

const VIDEO_FRAME_INFO_S *inFrame, const cvtdl_object_t *meta, const float obj_skip_ratio, const float trans_ratio, const float padding_ratio,

VIDEO_FRAME_INFO_S *outFrame);

【Description】

The object detected in the detection result is zoomed in.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t	handle	handle
Input	const VIDEO_FRAME_INFO_S*	inFrame	Input image
Input	const cvtdl_object_t*	meta	Object data
Input	const float	obj_skip_ratio	Neglect ratio
Input	const float	trans_ratio	Amplification ratio
Input	const float	padding_ratio	Expand bounding box ratio
Output	VIDEO_FRAME_INFO_S*	outFrame	Output image

4.3.2.3. CVI_TDL_Service_ObjectDitgitalZoomExt

【Syntax】

CVI_S32 CVI_TDL_Service_ObjectDigitalZoomExt(cvitdl_service_handle_t handle, const VIDEO_FRAME_INFO_S *inFrame, const cvtdl_object_t *meta,

const float obj_skip_ratio, const float trans_ratio, const float pad_ratio_left, const float pad_ratio_right, const float pad_ratio_top,

const float pad_ratio_bottom, VIDEO_FRAME_INFO_S *outFrame);

【Description】

Zoom in on the object in the detection results

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t	handle	handle
Input	VIDEO_FRAME_INFO_S*	inFrame	Input image
Input	const cvtdl_object_t*	meta	Object data
Input	const float	obj_skip_ratio	Neglect ratio
Input	const float	trans_ratio	Amplification ratio
Input	const float	pad_ratio_left	Expansion rate (left)
Input	const float	pad_ratio_right	Expansion rate (right)
Input	const float	pad_ratio_top	Expansion rate (top)
Input	const float	pad_ratio_bottom	Expansion rate (lower)
Output	VIDEO_FRAME_INFO_S*	outFrame	Output image

4.3.3. Image drawing

4.3.3.1. CVI_TDL_Service_FaceDrawPts

【Syntax】

CVI_S32 CVI_TDL_Service_FaceDrawPts(cvtdl_pts_t *pts, VIDEO_FRAME_INFO_S *frame);

【Description】

Drawing face landmarks.

【Parameter】

	Data Type	Parameter	Description
Input	cvtdl_pts_t*	pts	Face landmark
Input	VIDEO_FRAME_INFO_S*	hp	Input/output image

4.3.3.2. CVI_TDL_Service_FaceDrawRect

【Syntax】

CVI_S32 CVI_TDL_Service_FaceDrawRect(cvitdl_service_handle_t handle, const cvtdl_face_t *meta, VIDEO_FRAME_INFO_S *frame, const bool drawText, cvtdl_service_brush_t brush);

【Description】

Drawing a bounding box around a detected face.

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t	handle	handle
Input	cvtdl_face_t*	meta	Face data
Input	VIDEO_FRAME_INFO_S*	frame	Input/output image
Input	bool	drawText	Whether to draw face names
Input	cvtdl_service_brush_t	brush	color

4.3.3.3. CVI_TDL_Service_ObjectDrawPose

【Syntax】

CVI_S32 CVI_TDL_Service_ObjectDrawPose(const cvtdl_object_t *meta, VIDEO_FRAME_INFO_S *frame);

【Description】

Draw 17 skeletal points detected by pose estimation.

【Parameter】

	Data Type	Parameter	Description
Input	cvtdl_object_t*	meta	Skeletal points detection result
Input	VIDEO_FRAME_INFO_S*	frame	Input image

4.3.3.4. CVI_TDL_Service_ObjectDrawRect

【Syntax】

CVI_S32 CVI_TDL_Service_ObjectDrawRect(cvitdl_service_handle_t handle, const cvtdl_object_t *meta, VIDEO_FRAME_INFO_S *frame, const bool drawText);

【Description】

Draw bounding box of detected objects

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t	handle	handle
Input	cvtdl_object_t*	meta	Object detection result
Input	VIDEO_FRAME_INFO_S*	frame	Input/output image
Input	const bool	drawText	Whether to draw class text

4.3.3.5. CVI_TDL_Service_ObjectWriteText

【Syntax】

CVI_S32 CVI_TDL_Service_ObjectWriteText(char *name, int x, int y, VIDEO_FRAME_INFO_S *frame, float r, float g, float b);

【Description】

Draw specified text

【Parameter】

	Data Type	Parameter	Description
Input	char*	name	Drawn text
Input	int	x	The x coordinate is drawn
Input	int	y	The y coordinate is drawn
Input/Output	IDEO_FRAME_INFO_S*	rame	Input/output image
Input	float	r	Draw the color r channel value
Input	float	g	Draw the color g channel value
Input	float	b	Draw the color b channel value

4.3.3.6. CVI_TDL_Service_Incar_ObjectDrawRect

【Syntax】

CVI_S32 CVI_TDL_Service_Incar_ObjectDrawRect(cvitdl_service_handle_t handle, const cvtdl_dms_od_t *meta, VIDEO_FRAME_INFO_S *frame, const bool drawText, cvtdl_service_brush_t brush);

【Description】

Draw specified text

【Parameter】

	Data Type	Parameter	Description
Input	cvitdl_service_handle_t	handle	handle
Input	const cvtdl_dms_od_t*	meta	Object detection result
Input/Output	IDEO_FRAME_INFO_S*	rame	Input/output image
Input	const bool	drawText	Whether to draw class text
Input	cvtdl_service_brush_t	brush	color