fastdeploy::vision::detection::PPDetBase Class Reference

Base model object used when to load a model exported by PaddleDetection. More...

#include <base.h>

Inheritance diagram for fastdeploy::vision::detection::PPDetBase:

Collaboration diagram for fastdeploy::vision::detection::PPDetBase:

Public Member Functions
	PPDetBase (const std::string &model_file, const std::string &params_file, const std::string &config_file, const RuntimeOption &custom_option=RuntimeOption(), const ModelFormat &model_format=ModelFormat::PADDLE)
	Set path of model file and configuration file, and the configuration of runtime. More...
virtual std::unique_ptr< PPDetBase >	Clone () const
	Clone a new PaddleDetModel with less memory usage when multiple instances of the same model are created. More...
virtual std::string	ModelName () const
	Get model's name.
virtual bool	Predict (cv::Mat *im, DetectionResult *result)
	DEPRECATED Predict the detection result for an input image. More...
virtual bool	Predict (const cv::Mat &im, DetectionResult *result)
	Predict the detection result for an input image. More...
virtual bool	BatchPredict (const std::vector< cv::Mat > &imgs, std::vector< DetectionResult > *results)
	Predict the detection result for an input image list. More...
Public Member Functions inherited from fastdeploy::FastDeployModel
virtual bool	Infer (std::vector< FDTensor > &input_tensors, std::vector< FDTensor > *output_tensors)
	Inference the model by the runtime. This interface is included in the Predict() function, so we don't call Infer() directly in most common situation.
virtual bool	Infer ()
	Inference the model by the runtime. This interface is using class member reused_input_tensors_ to do inference and writing results to reused_output_tensors_.
virtual int	NumInputsOfRuntime ()
	Get number of inputs for this model.
virtual int	NumOutputsOfRuntime ()
	Get number of outputs for this model.
virtual TensorInfo	InputInfoOfRuntime (int index)
	Get input information for this model.
virtual TensorInfo	OutputInfoOfRuntime (int index)
	Get output information for this model.
virtual bool	Initialized () const
	Check if the model is initialized successfully.
virtual void	EnableRecordTimeOfRuntime ()
	This is a debug interface, used to record the time of runtime (backend + h2d + d2h) More...
virtual void	DisableRecordTimeOfRuntime ()
	Disable to record the time of runtime, see EnableRecordTimeOfRuntime() for more detail.
virtual std::map< std::string, float >	PrintStatisInfoOfRuntime ()
	Print the statistic information of runtime in the console, see function EnableRecordTimeOfRuntime() for more detail.
virtual bool	EnabledRecordTimeOfRuntime ()
	Check if the EnableRecordTimeOfRuntime() method is enabled.
virtual double	GetProfileTime ()
	Get profile time of Runtime after the profile process is done.
virtual void	ReleaseReusedBuffer ()
	Release reused input/output buffers.

Additional Inherited Members
Public Attributes inherited from fastdeploy::FastDeployModel
std::vector< Backend >	valid_cpu_backends = {Backend::ORT}
	Model's valid cpu backends. This member defined all the cpu backends have successfully tested for the model.
std::vector< Backend >	valid_gpu_backends = {Backend::ORT}
std::vector< Backend >	valid_ipu_backends = {}
std::vector< Backend >	valid_timvx_backends = {}
std::vector< Backend >	valid_directml_backends = {}
std::vector< Backend >	valid_ascend_backends = {}
std::vector< Backend >	valid_kunlunxin_backends = {}
std::vector< Backend >	valid_rknpu_backends = {}
std::vector< Backend >	valid_sophgonpu_backends = {}

Detailed Description

Base model object used when to load a model exported by PaddleDetection.

Constructor & Destructor Documentation

PPDetBase()

fastdeploy::vision::detection::PPDetBase::PPDetBase	(	const std::string &	model_file,
		const std::string &	params_file,
		const std::string &	config_file,
		const RuntimeOption &	custom_option = RuntimeOption(),
		const ModelFormat &	model_format = ModelFormat::PADDLE
	)

Set path of model file and configuration file, and the configuration of runtime.

Parameters

[in]	model_file	Path of model file, e.g ppyoloe/model.pdmodel
[in]	params_file	Path of parameter file, e.g ppyoloe/model.pdiparams, if the model format is ONNX, this parameter will be ignored
[in]	config_file	Path of configuration file for deployment, e.g ppyoloe/infer_cfg.yml
[in]	custom_option	RuntimeOption for inference, the default will use cpu, and choose the backend defined in valid_cpu_backends
[in]	model_format	Model format of the loaded model, default is Paddle format

Member Function Documentation

BatchPredict()

bool fastdeploy::vision::detection::PPDetBase::BatchPredict ( const std::vector< cv::Mat > &  imgs, std::vector< DetectionResult > *  results  )

virtual

Predict the detection result for an input image list.

Parameters

[in]	im	The input image list, all the elements come from cv::imread(), is a 3-D array with layout HWC, BGR format
[in]	results	The output detection result list

Returns

true if the prediction successed, otherwise false

Clone()

std::unique_ptr< PPDetBase > fastdeploy::vision::detection::PPDetBase::Clone ( ) const

virtual

Clone a new PaddleDetModel with less memory usage when multiple instances of the same model are created.

Returns

new PaddleDetModel* type unique pointer

Predict() [1/2]

bool fastdeploy::vision::detection::PPDetBase::Predict ( cv::Mat *  im, DetectionResult *  result  )

virtual

DEPRECATED Predict the detection result for an input image.

Parameters

[in]	im	The input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
[in]	result	The output detection result

Returns

true if the prediction successed, otherwise false

Predict() [2/2]

bool fastdeploy::vision::detection::PPDetBase::Predict ( const cv::Mat &  im, DetectionResult *  result  )

virtual

Predict the detection result for an input image.

Parameters

[in]	im	The input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
[in]	result	The output detection result

Returns

true if the prediction successed, otherwise false

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The documentation for this class was generated from the following files:

• /fastdeploy/my_work/FastDeploy/fastdeploy/vision/detection/ppdet/base.h
• /fastdeploy/my_work/FastDeploy/fastdeploy/vision/detection/ppdet/base.cc