vitis::ai::FaceQuality5pt

Base class for evaluating the quality and five key points coordinate of a face image (cv::Mat).

Input is a face image (cv::Mat).

Output is the quality and five key points coordinate of a face in the input image.

Sample code : Display of the FaceQuality5pt model results:

cv:Mat image = cv::imread("sample_facequality5pt.jpg");
auto network =
      vitis::ai::FaceQuality5pt::create("face-quality", true);
auto result = network->run(image);
auto quality = result.score;
auto points = result.points;
for(int i = 0; i< 5 ; ++i){
    auto x = points[i].frist  * image.cols;
    auto y = points[j].second * image.rows;
}

Note: Default mode is day, if day night switch network is used and the background of the input image is night, please use API setMode

network->setMode(vitis::ai::FaceQuality5pt::Mode::NIGHT);

Image sample_facedetect_result.jpg — Figure 1: result image

Quick Function Reference

The following table lists all the functions defined in the vitis::ai::FaceQuality5pt class:

Table 1. Quick Function Reference
Type	Name	Arguments
std::unique_ptr< `FaceQuality5pt` >	create	const std::string & model_name bool need_preprocess
int	getInputWidth	void
int	getInputHeight	void
size_t	get_input_batch	void
`Mode`	getMode	void
void	setMode	`Mode` mode
`FaceQuality5ptResult`	run	const cv::Mat & img
std::vector< `FaceQuality5ptResult` >	run	const std::vector< cv::Mat > & images

create

Factory function to get an instance of derived classes of class FaceQuality5pt.

Prototype

std::unique_ptr< FaceQuality5pt > create(const std::string &model_name, bool need_preprocess=true);

Parameters

The following table lists the create function arguments.

Table 2. create Arguments
Type	Name	Description
const std::string &	model_name	Model name
bool	need_preprocess	Normalize with mean/scale or not, default value is true.

Returns

An instance of FaceQuality5pt class.

getInputWidth

Function to get InputWidth of the facequality5pt network (input image columns).

Prototype

int getInputWidth() const =0;

Returns

InputWidth of the facequality5pt network.

getInputHeight

Function to get InputHeight of the facequality5pt network (input image rows).

Prototype

int getInputHeight() const =0;

Returns

InputHeight of facequality5pt network.

get_input_batch

Function to get the number of images processed by the DPU at one time.

Note: Different DPU core the batch size may be different. This depends on the IP used.

Prototype

size_t get_input_batch() const =0;

Returns

Batch size.

getMode

Function to get Mode.

Prototype


            Mode getMode()=0;

setMode

Function to set Mode.

Prototype

void setMode(Mode mode)=0;

Parameters

The following table lists the setMode function arguments.

Table 3. setMode Arguments
Type	Name	Description
`Mode`	mode	Type::Mode

Returns

mode

run

Function of get running result of the facequality5pt network.

Prototype


            FaceQuality5ptResult run(const cv::Mat &img)=0;

Parameters

The following table lists the run function arguments.

Table 4. run Arguments
Type	Name	Description
const cv::Mat &	img	Input data of input image (cv::Mat) of detected counterpart and resized to InputWidth and InputHeight required by the network.

Returns

The result of the facequality5pt network.

run

Function of get running results of the facequality5pt network in batch mode.

Prototype

std::vector< FaceQuality5ptResult > run(const std::vector< cv::Mat > &images)=0;

Parameters

The following table lists the run function arguments.

Table 5. run Arguments
Type	Name	Description
const std::vector< cv::Mat > &	images	Input data of input images (std::vector<cv::Mat>). The size of input images equals batch size obtained by get_input_batch. The input images need to be resized to InputWidth and InputHeight required by the network.

Returns

The vector of the FaceQuality5ptResult.

Enumeration Mode

Scene of sending image.

Table 6. Enumeration Mode Values
Value	Description
DAY	Use DAY when the background of the image is daytime.
NIGHT	Use NIGHT when the background of the image is night.