Tizen Native API  5.5

The NNStreamer function provides interfaces to create and execute stream pipelines with neural networks and sensors.

Required Header

#include <nnstreamer/nnstreamer.h>

Overview

The NNStreamer function provides interfaces to create and execute stream pipelines with neural networks and sensors.

This function allows the following operations with NNStreamer:

  • Create a stream pipeline with NNStreamer plugins, GStreamer plugins, and sensor/camera/mic inputs.
  • Interfaces to push data to the pipeline from the application.
  • Interfaces to pull data from the pipeline to the application.
  • Interfaces to start/stop/destroy the pipeline.
  • Interfaces to control switches and valves in the pipeline.
  • Utility functions to handle data from the pipeline.

Note that this function set is supposed to be thread-safe.

Pipeline State Diagram

capi_nnstreamer_pipeline_state.jpg
Figure1. Pipeline State

Related Features

This function is related with the following features:

It is recommended to probe features in your application for reliability.
You can check if a device supports the related features for this function by using System Information, thereby controlling the procedure of your application.
To ensure your application is only running on the device with specific features, please define the features in your manifest file using the manifest editor in the SDK.
For example, your application accesses to the camera device, then you have to add 'http://tizen.org/privilege/camera' into the manifest of your application.
More details on featuring your application can be found from Feature Element.

Functions

int ml_pipeline_construct (const char *pipeline_description, ml_pipeline_state_cb cb, void *user_data, ml_pipeline_h *pipe)
 Constructs the pipeline (GStreamer + NNStreamer).
int ml_pipeline_destroy (ml_pipeline_h pipe)
 Destroys the pipeline.
int ml_pipeline_get_state (ml_pipeline_h pipe, ml_pipeline_state_e *state)
 Gets the state of pipeline.
int ml_pipeline_start (ml_pipeline_h pipe)
 Starts the pipeline, asynchronously.
int ml_pipeline_stop (ml_pipeline_h pipe)
 Stops the pipeline, asynchronously.
int ml_pipeline_sink_register (ml_pipeline_h pipe, const char *sink_name, ml_pipeline_sink_cb cb, void *user_data, ml_pipeline_sink_h *sink_handle)
 Registers a callback for sink node of NNStreamer pipelines.
int ml_pipeline_sink_unregister (ml_pipeline_sink_h sink_handle)
 Unregisters a callback for sink node of NNStreamer pipelines.
int ml_pipeline_src_get_handle (ml_pipeline_h pipe, const char *src_name, ml_pipeline_src_h *src_handle)
 Gets a handle to operate as a src node of NNStreamer pipelines.
int ml_pipeline_src_release_handle (ml_pipeline_src_h src_handle)
 Releases the given src handle.
int ml_pipeline_src_input_data (ml_pipeline_src_h src_handle, ml_tensors_data_h data, ml_pipeline_buf_policy_e policy)
 Adds an input data frame.
int ml_pipeline_src_get_tensors_info (ml_pipeline_src_h src_handle, ml_tensors_info_h *info)
 Gets a handle for the tensors information of given src node.
int ml_pipeline_switch_get_handle (ml_pipeline_h pipe, const char *switch_name, ml_pipeline_switch_e *switch_type, ml_pipeline_switch_h *switch_handle)
 Gets a handle to operate a "GstInputSelector / GstOutputSelector" node of NNStreamer pipelines.
int ml_pipeline_switch_release_handle (ml_pipeline_switch_h switch_handle)
 Releases the given switch handle.
int ml_pipeline_switch_select (ml_pipeline_switch_h switch_handle, const char *pad_name)
 Controls the switch with the given handle to select input/output nodes(pads).
int ml_pipeline_switch_get_pad_list (ml_pipeline_switch_h switch_handle, char ***list)
 Gets the pad names of a switch.
int ml_pipeline_valve_get_handle (ml_pipeline_h pipe, const char *valve_name, ml_pipeline_valve_h *valve_handle)
 Gets a handle to operate a "GstValve" node of NNStreamer pipelines.
int ml_pipeline_valve_release_handle (ml_pipeline_valve_h valve_handle)
 Releases the given valve handle.
int ml_pipeline_valve_set_open (ml_pipeline_valve_h valve_handle, bool open)
 Controls the valve with the given handle.
int ml_tensors_info_create (ml_tensors_info_h *info)
 Creates a tensors information handle with default value.
int ml_tensors_info_destroy (ml_tensors_info_h info)
 Frees the given handle of a tensors information.
int ml_tensors_info_validate (const ml_tensors_info_h info, bool *valid)
 Validates the given tensors information.
int ml_tensors_info_clone (ml_tensors_info_h dest, const ml_tensors_info_h src)
 Copies the tensors information.
int ml_tensors_info_set_count (ml_tensors_info_h info, unsigned int count)
 Sets the number of tensors with given handle of tensors information.
int ml_tensors_info_get_count (ml_tensors_info_h info, unsigned int *count)
 Gets the number of tensors with given handle of tensors information.
int ml_tensors_info_set_tensor_name (ml_tensors_info_h info, unsigned int index, const char *name)
 Sets the tensor name with given handle of tensors information.
int ml_tensors_info_get_tensor_name (ml_tensors_info_h info, unsigned int index, char **name)
 Gets the tensor name with given handle of tensors information.
int ml_tensors_info_set_tensor_type (ml_tensors_info_h info, unsigned int index, const ml_tensor_type_e type)
 Sets the tensor type with given handle of tensors information.
int ml_tensors_info_get_tensor_type (ml_tensors_info_h info, unsigned int index, ml_tensor_type_e *type)
 Gets the tensor type with given handle of tensors information.
int ml_tensors_info_set_tensor_dimension (ml_tensors_info_h info, unsigned int index, const ml_tensor_dimension dimension)
 Sets the tensor dimension with given handle of tensors information.
int ml_tensors_info_get_tensor_dimension (ml_tensors_info_h info, unsigned int index, ml_tensor_dimension dimension)
 Gets the tensor dimension with given handle of tensors information.
int ml_tensors_info_get_tensor_size (ml_tensors_info_h info, int index, size_t *data_size)
 Gets the size of tensors data in the given tensors information handle in bytes.
int ml_tensors_data_create (const ml_tensors_info_h info, ml_tensors_data_h *data)
 Creates a tensor data frame with the given tensors information.
int ml_tensors_data_destroy (ml_tensors_data_h data)
 Frees the given tensors' data handle.
int ml_tensors_data_get_tensor_data (ml_tensors_data_h data, unsigned int index, void **raw_data, size_t *data_size)
 Gets a tensor data of given handle.
int ml_tensors_data_set_tensor_data (ml_tensors_data_h data, unsigned int index, const void *raw_data, const size_t data_size)
 Copies a tensor data to given handle.
int ml_check_nnfw_availability (ml_nnfw_type_e nnfw, ml_nnfw_hw_e hw, bool *available)
 Checks the availability of the given execution environments.

Typedefs

typedef unsigned int ml_tensor_dimension [(4)]
 The dimensions of a tensor that NNStreamer supports.
typedef void * ml_tensors_info_h
 A handle of a tensors metadata instance.
typedef void * ml_tensors_data_h
 A handle of input or output frames. ml_tensors_info_h is the handle for tensors metadata.
typedef void * ml_pipeline_h
 A handle of an NNStreamer pipeline.
typedef void * ml_pipeline_sink_h
 A handle of a "sink node" of an NNStreamer pipeline.
typedef void * ml_pipeline_src_h
 A handle of a "src node" of an NNStreamer pipeline.
typedef void * ml_pipeline_switch_h
 A handle of a "switch" of an NNStreamer pipeline.
typedef void * ml_pipeline_valve_h
 A handle of a "valve node" of an NNStreamer pipeline.
typedef enum _ml_tensor_type_e ml_tensor_type_e
 Possible data element types of Tensor in NNStreamer.
typedef void(* ml_pipeline_sink_cb )(const ml_tensors_data_h data, const ml_tensors_info_h info, void *user_data)
 Callback for sink element of NNStreamer pipelines (pipeline's output).
typedef void(* ml_pipeline_state_cb )(ml_pipeline_state_e state, void *user_data)
 Callback for the change of pipeline state.

Defines

#define ML_TIZEN_CAM_VIDEO_SRC   "tizencamvideosrc"
 The virtual name to set the video source of camcorder in Tizen.
#define ML_TIZEN_CAM_AUDIO_SRC   "tizencamaudiosrc"
 The virtual name to set the audio source of camcorder in Tizen.
#define ML_TENSOR_RANK_LIMIT   (4)
 The maximum rank that NNStreamer supports with Tizen APIs.
#define ML_TENSOR_SIZE_LIMIT   (16)
 The maximum number of other/tensor instances that other/tensors may have.

Define Documentation

#define ML_TENSOR_RANK_LIMIT   (4)

The maximum rank that NNStreamer supports with Tizen APIs.

Since :
5.5
#define ML_TENSOR_SIZE_LIMIT   (16)

The maximum number of other/tensor instances that other/tensors may have.

Since :
5.5
#define ML_TIZEN_CAM_AUDIO_SRC   "tizencamaudiosrc"

The virtual name to set the audio source of camcorder in Tizen.

If an application needs to access the recorder device to construct the pipeline, set the virtual name as an audio source element. Note that you have to add 'http://tizen.org/privilege/recorder' into the manifest of your application.

Since :
5.5
#define ML_TIZEN_CAM_VIDEO_SRC   "tizencamvideosrc"

The virtual name to set the video source of camcorder in Tizen.

If an application needs to access the camera device to construct the pipeline, set the virtual name as a video source element. Note that you have to add 'http://tizen.org/privilege/camera' into the manifest of your application.

Since :
5.5

Typedef Documentation

typedef void* ml_pipeline_h

A handle of an NNStreamer pipeline.

Since :
5.5
typedef void(* ml_pipeline_sink_cb)(const ml_tensors_data_h data, const ml_tensors_info_h info, void *user_data)

Callback for sink element of NNStreamer pipelines (pipeline's output).

If an application wants to accept data outputs of an NNStreamer stream, use this callback to get data from the stream. Note that the buffer may be deallocated after the return and this is synchronously called. Thus, if you need the data afterwards, copy the data to another buffer and return fast. Do not spend too much time in the callback. It is recommended to use very small tensors at sinks.

Since :
5.5
Remarks:
The data can be used only in the callback. To use outside, make a copy.
The info can be used only in the callback. To use outside, make a copy.
Parameters:
[out]dataThe handle of the tensor output (a single frame. tensor/tensors). Number of tensors is determined by ml_tensors_info_get_count() with the handle 'info'. Note that max num_tensors is 16 (ML_TENSOR_SIZE_LIMIT).
[out]infoThe handle of tensors information (cardinality, dimension, and type of given tensor/tensors).
[out]user_dataUser application's private data.
typedef void* ml_pipeline_sink_h

A handle of a "sink node" of an NNStreamer pipeline.

Since :
5.5
typedef void* ml_pipeline_src_h

A handle of a "src node" of an NNStreamer pipeline.

Since :
5.5
typedef void(* ml_pipeline_state_cb)(ml_pipeline_state_e state, void *user_data)

Callback for the change of pipeline state.

If an application wants to get the change of pipeline state, use this callback. This callback can be registered when constructing the pipeline using ml_pipeline_construct(). Do not spend too much time in the callback.

Since :
5.5
Parameters:
[out]stateThe new state of the pipeline.
[out]user_dataUser application's private data.
typedef void* ml_pipeline_switch_h

A handle of a "switch" of an NNStreamer pipeline.

Since :
5.5
typedef void* ml_pipeline_valve_h

A handle of a "valve node" of an NNStreamer pipeline.

Since :
5.5
typedef unsigned int ml_tensor_dimension[(4)]

The dimensions of a tensor that NNStreamer supports.

Since :
5.5

Possible data element types of Tensor in NNStreamer.

Since :
5.5
typedef void* ml_tensors_data_h

A handle of input or output frames. ml_tensors_info_h is the handle for tensors metadata.

Since :
5.5
typedef void* ml_tensors_info_h

A handle of a tensors metadata instance.

Since :
5.5

Enumeration Type Documentation

Possible data element types of Tensor in NNStreamer.

Since :
5.5
Enumerator:
ML_TENSOR_TYPE_INT32 

Integer 32bit

ML_TENSOR_TYPE_UINT32 

Unsigned integer 32bit

ML_TENSOR_TYPE_INT16 

Integer 16bit

ML_TENSOR_TYPE_UINT16 

Unsigned integer 16bit

ML_TENSOR_TYPE_INT8 

Integer 8bit

ML_TENSOR_TYPE_UINT8 

Unsigned integer 8bit

ML_TENSOR_TYPE_FLOAT64 

Float 64bit

ML_TENSOR_TYPE_FLOAT32 

Float 32bit

ML_TENSOR_TYPE_INT64 

Integer 64bit

ML_TENSOR_TYPE_UINT64 

Unsigned integer 64bit

ML_TENSOR_TYPE_UNKNOWN 

Unknown type

enum ml_error_e

Enumeration for the error codes of NNStreamer Pipelines.

Since :
5.5
Enumerator:
ML_ERROR_NONE 

Success!

ML_ERROR_INVALID_PARAMETER 

Invalid parameter

ML_ERROR_STREAMS_PIPE 

Cannot create or access GStreamer pipeline.

ML_ERROR_TRY_AGAIN 

The pipeline is not ready, yet (not negotiated, yet)

ML_ERROR_UNKNOWN 

Unknown error

ML_ERROR_TIMED_OUT 

Time out

ML_ERROR_NOT_SUPPORTED 

The feature is not supported

ML_ERROR_PERMISSION_DENIED 

Permission denied

Types of hardware resources to be used for NNFWs. Note that if the affinity (nnn) is not supported by the driver or hardware, it is ignored.

Since :
5.5
Enumerator:
ML_NNFW_HW_ANY 

Hardware resource is not specified.

ML_NNFW_HW_AUTO 

Try to schedule and optimize if possible.

ML_NNFW_HW_CPU 

0x1000: any CPU. 0x1nnn: CPU # nnn-1.

ML_NNFW_HW_GPU 

0x2000: any GPU. 0x2nnn: GPU # nnn-1.

ML_NNFW_HW_NPU 

0x3000: any NPU. 0x3nnn: NPU # nnn-1.

Types of NNFWs.

Since :
5.5
Enumerator:
ML_NNFW_TYPE_ANY 

NNHW is not specified (Try to determine the NNFW with file extension).

ML_NNFW_TYPE_CUSTOM_FILTER 

Custom filter (Independent shared object).

ML_NNFW_TYPE_TENSORFLOW_LITE 

Tensorflow-lite (.tflite).

ML_NNFW_TYPE_TENSORFLOW 

Tensorflow (.pb).

ML_NNFW_TYPE_NNFW 

Neural Network Inference framework, which is developed by SR

Enumeration for buffer deallocation policies.

Since :
5.5
Enumerator:
ML_PIPELINE_BUF_POLICY_AUTO_FREE 

Default. Application should not deallocate this buffer. NNStreamer will deallocate when the buffer is no more needed

ML_PIPELINE_BUF_POLICY_DO_NOT_FREE 

This buffer is not to be freed by NNStreamer (i.e., it's a static object). However, be careful: NNStreamer might be accessing this object after the return of the API call.

ML_PIPELINE_BUF_POLICY_MAX 

Max size of ml_pipeline_buf_policy_e structure

Enumeration for pipeline state.

The pipeline state is described on Pipeline State Diagram. Refer to https://gstreamer.freedesktop.org/documentation/plugin-development/basics/states.html.

Since :
5.5
Enumerator:
ML_PIPELINE_STATE_UNKNOWN 

Unknown state. Maybe not constructed?

ML_PIPELINE_STATE_NULL 

GST-State "Null"

ML_PIPELINE_STATE_READY 

GST-State "Ready"

ML_PIPELINE_STATE_PAUSED 

GST-State "Paused"

ML_PIPELINE_STATE_PLAYING 

GST-State "Playing"

Enumeration for switch types.

This designates different GStreamer filters, "GstInputSelector"/"GetOutputSelector".

Since :
5.5
Enumerator:
ML_PIPELINE_SWITCH_OUTPUT_SELECTOR 

GstOutputSelector

ML_PIPELINE_SWITCH_INPUT_SELECTOR 

GstInputSelector


Function Documentation

int ml_check_nnfw_availability ( ml_nnfw_type_e  nnfw,
ml_nnfw_hw_e  hw,
bool *  available 
)

Checks the availability of the given execution environments.

If the function returns an error, available is not changed.

Since :
5.5
Parameters:
[in]nnfwCheck if the nnfw is available in the system. Set ML_NNFW_TYPE_ANY to skip checking nnfw.
[in]hwCheck if the hardware is available in the system. Set ML_NNFW_HW_ANY to skip checking hardware.
[out]availabletrue if it's available, false if if it's not available.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful and the environments are available.
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_pipeline_construct ( const char *  pipeline_description,
ml_pipeline_state_cb  cb,
void *  user_data,
ml_pipeline_h pipe 
)

Constructs the pipeline (GStreamer + NNStreamer).

Use this function to create gst_parse_launch compatible NNStreamer pipelines.

Since :
5.5
Remarks:
If the function succeeds, pipe handle must be released using ml_pipeline_destroy().
http://tizen.org/privilege/mediastorage is needed if pipeline_description is relevant to media storage.
http://tizen.org/privilege/externalstorage is needed if pipeline_description is relevant to external storage.
http://tizen.org/privilege/camera is needed if pipeline_description accesses the camera device.
http://tizen.org/privilege/recorder is needed if pipeline_description accesses the recorder device.
Parameters:
[in]pipeline_descriptionThe pipeline description compatible with GStreamer gst_parse_launch(). Refer to GStreamer manual or NNStreamer (https://github.com/nnsuite/nnstreamer) documentation for examples and the grammar.
[in]cbThe function to be called when the pipeline state is changed. You may set NULL if it's not required.
[in]user_dataPrivate data for the callback. This value is passed to the callback when it's invoked.
[out]pipeThe NNStreamer pipeline handler from the given description.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid. (Pipeline is not negotiated yet.)
ML_ERROR_STREAMS_PIPEPipeline construction is failed because of wrong parameter or initialization failure.
ML_ERROR_PERMISSION_DENIEDThe application does not have the required privilege to access to the media storage, external storage, microphone, or camera.
Precondition:
The pipeline state should be ML_PIPELINE_STATE_UNKNOWN or ML_PIPELINE_STATE_NULL.
Postcondition:
The pipeline state will be ML_PIPELINE_STATE_PAUSED in the same thread.

Destroys the pipeline.

Use this function to destroy the pipeline constructed with ml_pipeline_construct().

Since :
5.5
Parameters:
[in]pipeThe pipeline to be destroyed.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERThe parameter is invalid (Pipeline is not negotiated yet.)
ML_ERROR_STREAMS_PIPECannot access the pipeline status.
Precondition:
The pipeline state should be ML_PIPELINE_STATE_PLAYING or ML_PIPELINE_STATE_PAUSED.
Postcondition:
The pipeline state will be ML_PIPELINE_STATE_NULL.

Gets the state of pipeline.

Gets the state of the pipeline handle returned by ml_pipeline_construct().

Since :
5.5
Parameters:
[in]pipeThe pipeline handle.
[out]stateThe pipeline state.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid. (Pipeline is not negotiated yet.)
ML_ERROR_STREAMS_PIPEFailed to get state from the pipeline.
int ml_pipeline_sink_register ( ml_pipeline_h  pipe,
const char *  sink_name,
ml_pipeline_sink_cb  cb,
void *  user_data,
ml_pipeline_sink_h sink_handle 
)

Registers a callback for sink node of NNStreamer pipelines.

Since :
5.5
Remarks:
If the function succeeds, sink_handle handle must be unregistered using ml_pipeline_sink_unregister().
Parameters:
[in]pipeThe pipeline to be attached with a sink node.
[in]sink_nameThe name of sink node, described with ml_pipeline_construct().
[in]cbThe function to be called by the sink node.
[in]user_dataPrivate data for the callback. This value is passed to the callback when it's invoked.
[out]sink_handleThe sink handle.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid. (Not negotiated, sink_name is not found, or sink_name has an invalid type.)
ML_ERROR_STREAMS_PIPEFailed to connect a signal to sink element.
Precondition:
The pipeline state should be ML_PIPELINE_STATE_PAUSED.

Unregisters a callback for sink node of NNStreamer pipelines.

Since :
5.5
Parameters:
[in]sink_handleThe sink handle to be unregistered.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
Precondition:
The pipeline state should be ML_PIPELINE_STATE_PAUSED.
int ml_pipeline_src_get_handle ( ml_pipeline_h  pipe,
const char *  src_name,
ml_pipeline_src_h src_handle 
)

Gets a handle to operate as a src node of NNStreamer pipelines.

Since :
5.5
Remarks:
If the function succeeds, src_handle handle must be released using ml_pipeline_src_release_handle().
Parameters:
[in]pipeThe pipeline to be attached with a src node.
[in]src_nameThe name of src node, described with ml_pipeline_construct().
[out]src_handleThe src handle.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
ML_ERROR_STREAMS_PIPEFail to get SRC element.
ML_ERROR_TRY_AGAINThe pipeline is not ready yet.

Gets a handle for the tensors information of given src node.

If the mediatype is not other/tensor or other/tensors, info handle may not be correct. If want to use other media types, you MUST set the correct properties.

Since :
5.5
Remarks:
If the function succeeds, info handle must be released using ml_tensors_info_destroy().
Parameters:
[in]src_handleThe source handle returned by ml_pipeline_src_get_handle().
[out]infoThe handle of tensors information.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
ML_ERROR_STREAMS_PIPEThe pipeline has inconsistent padcaps. (Pipeline is not negotiated yet.)
ML_ERROR_TRY_AGAINThe pipeline is not ready yet.

Adds an input data frame.

Since :
5.5
Parameters:
[in]src_handleThe source handle returned by ml_pipeline_src_get_handle().
[in]dataThe handle of input tensors, in the format of tensors info given by ml_pipeline_src_get_tensors_info(). This function takes ownership of the data if policy is ML_PIPELINE_BUF_POLICY_AUTO_FREE.
[in]policyThe policy of buf deallocation.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
ML_ERROR_STREAMS_PIPEThe pipeline has inconsistent padcaps. (Pipeline is not negotiated yet.)
ML_ERROR_TRY_AGAINThe pipeline is not ready yet.

Releases the given src handle.

Since :
5.5
Parameters:
[in]src_handleThe src handle to be released.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.

Starts the pipeline, asynchronously.

The pipeline handle returned by ml_pipeline_construct() is started. Note that this is asynchronous function. State might be "pending". If you need to get the changed state, add a callback while constructing a pipeline with ml_pipeline_construct().

Since :
5.5
Parameters:
[in]pipeThe pipeline handle.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid. (NPipeline is not negotiated yet.)
ML_ERROR_STREAMS_PIPEFailed to start the pipeline.
Precondition:
The pipeline state should be ML_PIPELINE_STATE_PAUSED.
Postcondition:
The pipeline state will be ML_PIPELINE_STATE_PLAYING.

Stops the pipeline, asynchronously.

The pipeline handle returned by ml_pipeline_construct() is stopped. Note that this is asynchronous function. State might be "pending". If you need to get the changed state, add a callback while constructing a pipeline with ml_pipeline_construct().

Since :
5.5
Parameters:
[in]pipeThe pipeline to be stopped.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid. (Pipeline is not negotiated yet.)
ML_ERROR_STREAMS_PIPEFailed to stop the pipeline.
Precondition:
The pipeline state should be ML_PIPELINE_STATE_PLAYING.
Postcondition:
The pipeline state will be ML_PIPELINE_STATE_PAUSED.
int ml_pipeline_switch_get_handle ( ml_pipeline_h  pipe,
const char *  switch_name,
ml_pipeline_switch_e switch_type,
ml_pipeline_switch_h switch_handle 
)

Gets a handle to operate a "GstInputSelector / GstOutputSelector" node of NNStreamer pipelines.

Refer to https://gstreamer.freedesktop.org/data/doc/gstreamer/head/gstreamer-plugins/html/gstreamer-plugins-input-selector.html for input selectors. Refer to https://gstreamer.freedesktop.org/data/doc/gstreamer/head/gstreamer-plugins/html/gstreamer-plugins-output-selector.html for output selectors.

Since :
5.5
Remarks:
If the function succeeds, switch_handle handle must be released using ml_pipeline_switch_release_handle().
Parameters:
[in]pipeThe pipeline to be managed.
[in]switch_nameThe name of switch (InputSelector/OutputSelector).
[out]switch_typeThe type of the switch. If NULL, it is ignored.
[out]switch_handleThe switch handle.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_pipeline_switch_get_pad_list ( ml_pipeline_switch_h  switch_handle,
char ***  list 
)

Gets the pad names of a switch.

Since :
5.5
Remarks:
If the function succeeds, list and its contents should be released using g_free(). Refer the below sample code.
Parameters:
[in]switch_handleThe switch handle returned by ml_pipeline_switch_get_handle().
[out]listNULL terminated array of char*. The caller must free each string (char*) in the list and free the list itself.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
ML_ERROR_STREAMS_PIPEThe element is not both input and output switch (Internal data inconsistency).

Here is an example of the usage:

 int status;
 gchar *pipeline;
 ml_pipeline_h handle;
 ml_pipeline_switch_e switch_type;
 ml_pipeline_switch_h switch_handle;
 gchar **node_list = NULL;

 // pipeline description
 pipeline = g_strdup ("videotestsrc is-live=true ! videoconvert ! tensor_converter ! output-selector name=outs "
     "outs.src_0 ! tensor_sink name=sink0 async=false "
     "outs.src_1 ! tensor_sink name=sink1 async=false");

 status = ml_pipeline_construct (pipeline, NULL, NULL, &handle);
 if (status != ML_ERROR_NONE) {
   // handle error case
   goto error;
 }

 status = ml_pipeline_switch_get_handle (handle, "outs", &switch_type, &switch_handle);
 if (status != ML_ERROR_NONE) {
   // handle error case
   goto error;
 }

 status = ml_pipeline_switch_get_pad_list (switch_handle, &node_list);
 if (status != ML_ERROR_NONE) {
   // handle error case
   goto error;
 }

 if (node_list) {
   gchar *name = NULL;
   guint idx = 0;

   while ((name = node_list[idx++]) != NULL) {
     // node name is 'src_0' or 'src_1'

     // release name
     g_free (name);
   }
   // release list of switch pads
   g_free (node_list);
 }

 error:
 ml_pipeline_switch_release_handle (switch_handle);
 ml_pipeline_destroy (handle);
 g_free (pipeline);

Releases the given switch handle.

Since :
5.5
Parameters:
[in]switch_handleThe handle to be released.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_pipeline_switch_select ( ml_pipeline_switch_h  switch_handle,
const char *  pad_name 
)

Controls the switch with the given handle to select input/output nodes(pads).

Since :
5.5
Parameters:
[in]switch_handleThe switch handle returned by ml_pipeline_switch_get_handle().
[in]pad_nameThe name of the chosen pad to be activated. Use ml_pipeline_switch_get_pad_list() to list the available pad names.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_pipeline_valve_get_handle ( ml_pipeline_h  pipe,
const char *  valve_name,
ml_pipeline_valve_h valve_handle 
)

Gets a handle to operate a "GstValve" node of NNStreamer pipelines.

Refer to https://gstreamer.freedesktop.org/data/doc/gstreamer/head/gstreamer-plugins/html/gstreamer-plugins-valve.html for more info.

Since :
5.5
Remarks:
If the function succeeds, valve_handle handle must be released using ml_pipeline_valve_release_handle().
Parameters:
[in]pipeThe pipeline to be managed.
[in]valve_nameThe name of valve (Valve).
[out]valve_handleThe valve handle.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.

Releases the given valve handle.

Since :
5.5
Parameters:
[in]valve_handleThe handle to be released.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_pipeline_valve_set_open ( ml_pipeline_valve_h  valve_handle,
bool  open 
)

Controls the valve with the given handle.

Since :
5.5
Parameters:
[in]valve_handleThe valve handle returned by ml_pipeline_valve_get_handle().
[in]opentrue to open(let the flow pass), false to close (drop & stop the flow).
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.

Creates a tensor data frame with the given tensors information.

Since :
5.5
Parameters:
[in]infoThe handle of tensors information for the allocation.
[out]dataThe handle of tensors data. The caller is responsible for freeing the allocated data with ml_tensors_data_destroy().
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
ML_ERROR_STREAMS_PIPEFailed to allocate new memory.

Frees the given tensors' data handle.

Since :
5.5
Parameters:
[in]dataThe handle of tensors data.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_tensors_data_get_tensor_data ( ml_tensors_data_h  data,
unsigned int  index,
void **  raw_data,
size_t *  data_size 
)

Gets a tensor data of given handle.

This returns the pointer of memory block in the handle. Do not deallocate the returned tensor data.

Since :
5.5
Parameters:
[in]dataThe handle of tensors data.
[in]indexThe index of the tensor.
[out]raw_dataRaw tensor data in the handle.
[out]data_sizeByte size of tensor data.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_tensors_data_set_tensor_data ( ml_tensors_data_h  data,
unsigned int  index,
const void *  raw_data,
const size_t  data_size 
)

Copies a tensor data to given handle.

Since :
5.5
Parameters:
[in]dataThe handle of tensors data.
[in]indexThe index of the tensor.
[in]raw_dataRaw tensor data to be copied.
[in]data_sizeByte size of raw data.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.

Copies the tensors information.

Since :
5.5
Parameters:
[out]destA destination handle of tensors information.
[in]srcThe tensors information to be copied.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.

Creates a tensors information handle with default value.

Since :
5.5
Parameters:
[out]infoThe handle of tensors information.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.

Frees the given handle of a tensors information.

Since :
5.5
Parameters:
[in]infoThe handle of tensors information.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_tensors_info_get_count ( ml_tensors_info_h  info,
unsigned int *  count 
)

Gets the number of tensors with given handle of tensors information.

Since :
5.5
Parameters:
[in]infoThe handle of tensors information.
[out]countThe number of tensors.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_tensors_info_get_tensor_dimension ( ml_tensors_info_h  info,
unsigned int  index,
ml_tensor_dimension  dimension 
)

Gets the tensor dimension with given handle of tensors information.

Since :
5.5
Parameters:
[in]infoThe handle of tensors information.
[in]indexThe index of the tensor.
[out]dimensionThe tensor dimension.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_tensors_info_get_tensor_name ( ml_tensors_info_h  info,
unsigned int  index,
char **  name 
)

Gets the tensor name with given handle of tensors information.

Since :
5.5
Parameters:
[in]infoThe handle of tensors information.
[in]indexThe index of the tensor.
[out]nameThe tensor name.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_tensors_info_get_tensor_size ( ml_tensors_info_h  info,
int  index,
size_t *  data_size 
)

Gets the size of tensors data in the given tensors information handle in bytes.

If an application needs to get the total byte size of tensors, set the index '-1'. Note that the maximum number of tensors is 16 (ML_TENSOR_SIZE_LIMIT).

Since :
5.5
Parameters:
[in]infoThe handle of tensors information.
[in]indexThe index of the tensor.
[out]data_sizeThe byte size of tensor data.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_tensors_info_get_tensor_type ( ml_tensors_info_h  info,
unsigned int  index,
ml_tensor_type_e type 
)

Gets the tensor type with given handle of tensors information.

Since :
5.5
Parameters:
[in]infoThe handle of tensors information.
[in]indexThe index of the tensor.
[out]typeThe tensor type.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_tensors_info_set_count ( ml_tensors_info_h  info,
unsigned int  count 
)

Sets the number of tensors with given handle of tensors information.

Since :
5.5
Parameters:
[in]infoThe handle of tensors information.
[in]countThe number of tensors.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_tensors_info_set_tensor_dimension ( ml_tensors_info_h  info,
unsigned int  index,
const ml_tensor_dimension  dimension 
)

Sets the tensor dimension with given handle of tensors information.

Since :
5.5
Parameters:
[in]infoThe handle of tensors information.
[in]indexThe index of the tensor to be updated.
[in]dimensionThe tensor dimension to be set.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_tensors_info_set_tensor_name ( ml_tensors_info_h  info,
unsigned int  index,
const char *  name 
)

Sets the tensor name with given handle of tensors information.

Since :
5.5
Parameters:
[in]infoThe handle of tensors information.
[in]indexThe index of the tensor to be updated.
[in]nameThe tensor name to be set.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_tensors_info_set_tensor_type ( ml_tensors_info_h  info,
unsigned int  index,
const ml_tensor_type_e  type 
)

Sets the tensor type with given handle of tensors information.

Since :
5.5
Parameters:
[in]infoThe handle of tensors information.
[in]indexThe index of the tensor to be updated.
[in]typeThe tensor type to be set.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.
int ml_tensors_info_validate ( const ml_tensors_info_h  info,
bool *  valid 
)

Validates the given tensors information.

If the function returns an error, valid is not changed.

Since :
5.5
Parameters:
[in]infoThe handle of tensors information to be validated.
[out]validtrue if it's valid, false if if it's invalid.
Returns:
0 on success. Otherwise a negative error value.
Return values:
ML_ERROR_NONESuccessful
ML_ERROR_NOT_SUPPORTEDNot supported.
ML_ERROR_INVALID_PARAMETERGiven parameter is invalid.