vitis::ai::YOLOv2

Base class for detecting objects in the input image(cv::Mat). Input is an image(cv::Mat). Output is the position of the objects in the input image. Sample code:

 auto img = cv::imread("sample_yolov2.jpg");
 auto model = vitis::ai::YOLOv2::create("yolov2_voc");
 auto result = model->run(img);
 for (const auto &bbox : result.bboxes) {
   int label = bbox.label;
   float xmin = bbox.x * img.cols + 1;
   float ymin = bbox.y * img.rows + 1;
   float xmax = xmin + bbox.width * img.cols;
   float ymax = ymin + bbox.height * img.rows;
   if (xmax > img.cols)
     xmax = img.cols;
   if (ymax > img.rows)
     ymax = img.rows;
   float confidence = bbox.score;

   cout << "RESULT: " << label << "\t" << xmin << "\t" << ymin << "\t" << xmax
       << "\t" << ymax << "\t" << confidence << "\n";
   rectangle(img, Point(xmin, ymin), Point(xmax, ymax), Scalar(0, 255, 0), 1,
            1, 0);
}

Quick Function Reference

The following table lists all the functions defined in the vitis::ai::YOLOv2 class:

Table 1. Quick Function Reference
Type	Name	Arguments
std::unique_ptr< `YOLOv2` >	create	const std::string & model_name bool need_preprocess
`YOLOv2Result`	run	const cv::Mat & image
std::vector< `YOLOv2Result` >	run	const std::vector< cv::Mat > & images
int	getInputWidth	void
int	getInputHeight	void
size_t	get_input_batch	void

create

Factory function to get an instance of derived classes of class YOLOv2.

Prototype

std::unique_ptr< YOLOv2 > 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 YOLOv2 class.

run

Function to get running result of the YOLOv2 neuron network.

Prototype


            YOLOv2Result run(const cv::Mat &image)=0;

Parameters

The following table lists the run function arguments.

Table 3. run Arguments
Type	Name	Description
const cv::Mat &	image	Input data of input image (cv::Mat).

Returns

A Struct of YOLOv2Result.

run

Function to get running result of the YOLOv2 neuron network in batch mode.

Prototype

std::vector< YOLOv2Result > run(const std::vector< cv::Mat > &images)=0;

Parameters

The following table lists the run function arguments.

Table 4. 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.

Returns

The vector of YOLOv2Result.

getInputWidth

Function to get InputWidth of the YOLOv2 network (input image columns).

Prototype

int getInputWidth() const =0;

Returns

InputWidth of the YOLOv2 network

getInputHeight

Function to get InputHeight of the YOLOv2 network (input image rows).

Prototype

int getInputHeight() const =0;

Returns

InputHeight of the YOLOv2 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.