FFmpeg: libavfilter/dnn/dnn_backend_common.h File Reference

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dnn_backend_common.h File Reference

#include "queue.h"
#include "../dnn_interface.h"
#include "libavutil/thread.h"

Go to the source code of this file.

Data Structures

struct TaskItem

struct LastLevelTaskItem

struct DNNAsyncExecModule

Common Async Execution Mechanism for the DNN Backends. More...

Macros

#define DNN_DEFINE_CLASS_EXT(name, desc, options)

#define DNN_DEFINE_CLASS(fname) DNN_DEFINE_CLASS_EXT(fname, #fname, fname##_options)

Functions

int ff_check_exec_params (void *ctx, DNNBackendType backend, DNNFunctionType func_type, DNNExecBaseParams *exec_params)

int ff_dnn_fill_task (TaskItem *task, DNNExecBaseParams *exec_params, void *backend_model, int async, int do_ioproc)

Fill the Task for Backend Execution. More...

int ff_dnn_async_module_cleanup (DNNAsyncExecModule *async_module)

Join the Async Execution thread and set module pointers to NULL. More...

int ff_dnn_start_inference_async (void *ctx, DNNAsyncExecModule *async_module)

Start asynchronous inference routine for the TensorFlow model on a detached thread. More...

DNNAsyncStatusType ff_dnn_get_result_common (Queue *task_queue, AVFrame **in, AVFrame **out)

Extract input and output frame from the Task Queue after asynchronous inference. More...

int ff_dnn_fill_gettingoutput_task (TaskItem *task, DNNExecBaseParams *exec_params, void *backend_model, int input_height, int input_width, void *ctx)

Allocate input and output frames and fill the Task with execution parameters. More...

Detailed Description

DNN common functions different backends.

Definition in file dnn_backend_common.h.

Macro Definition Documentation

◆ DNN_DEFINE_CLASS_EXT

#define DNN_DEFINE_CLASS_EXT ( name,

desc,

options

)

Value:

{ \

.class_name = desc, \

.item_name = av_default_item_name, \

.option = options, \

.version = LIBAVUTIL_VERSION_INT, \

.category = AV_CLASS_CATEGORY_FILTER, \

}

Definition at line 31 of file dnn_backend_common.h.

◆ DNN_DEFINE_CLASS

#define DNN_DEFINE_CLASS ( fname ) DNN_DEFINE_CLASS_EXT(fname, #fname, fname##_options)

Definition at line 39 of file dnn_backend_common.h.

Function Documentation

◆ ff_check_exec_params()

int ff_check_exec_params ( void * ctx,

DNNBackendType backend,

DNNFunctionType func_type,

DNNExecBaseParams * exec_params

)

Definition at line 30 of file dnn_backend_common.c.

Referenced by dnn_execute_model_tf(), dnn_execute_model_th(), and get_output_ov().

◆ ff_dnn_fill_task()

int ff_dnn_fill_task ( TaskItem * task,

DNNExecBaseParams * exec_params,

void * backend_model,

int async,

int do_ioproc

)

Fill the Task for Backend Execution.

It should be called after checking execution parameters using ff_check_exec_params.

Parameters: task pointer to the allocated task

exec_param pointer to execution parameters

backend_model void pointer to the backend model

async flag for async execution. Must be 0 or 1

do_ioproc flag for IO processing. Must be 0 or 1

Returns: 0 if successful or error code otherwise.

Definition at line 50 of file dnn_backend_common.c.

Referenced by dnn_execute_model_tf(), dnn_execute_model_th(), ff_dnn_fill_gettingoutput_task(), and get_output_ov().

◆ ff_dnn_async_module_cleanup()

int ff_dnn_async_module_cleanup ( DNNAsyncExecModule * async_module )

Join the Async Execution thread and set module pointers to NULL.

Parameters: async_module pointer to DNNAsyncExecModule module

Returns: 0 if successful or error code otherwise.

Definition at line 86 of file dnn_backend_common.c.

Referenced by destroy_request_item().

◆ ff_dnn_start_inference_async()

int ff_dnn_start_inference_async ( void * ctx,

DNNAsyncExecModule * async_module

)

Start asynchronous inference routine for the TensorFlow model on a detached thread.

It calls the completion callback after the inference completes. Completion callback and inference function must be set before calling this function.

If POSIX threads aren't supported, the execution rolls back to synchronous mode, calling completion callback after inference.

Parameters: ctx pointer to the backend context

async_module pointer to DNNAsyncExecModule module

Returns: 0 on the start of async inference or error code otherwise.

Definition at line 105 of file dnn_backend_common.c.

Referenced by dnn_flush_tf(), and execute_model_tf().

◆ ff_dnn_get_result_common()

DNNAsyncStatusType ff_dnn_get_result_common ( Queue * task_queue,

AVFrame ** in,

AVFrame ** out

)

Extract input and output frame from the Task Queue after asynchronous inference.

Parameters: task_queue pointer to the task queue of the backend

in double pointer to the input frame

out double pointer to the output frame

Return values: DAST_EMPTY_QUEUE if task queue is empty

DAST_NOT_READY if inference not completed yet.

DAST_SUCCESS if result successfully extracted

Definition at line 136 of file dnn_backend_common.c.

Referenced by dnn_get_result_tf(), dnn_get_result_th(), and get_output_ov().

◆ ff_dnn_fill_gettingoutput_task()

int ff_dnn_fill_gettingoutput_task ( TaskItem * task,

DNNExecBaseParams * exec_params,

void * backend_model,

int input_height,

int input_width,

void * ctx

)

Allocate input and output frames and fill the Task with execution parameters.

Parameters: task pointer to the allocated task

exec_params pointer to execution parameters

backend_model void pointer to the backend model

input_height height of input frame

input_width width of input frame

ctx pointer to the backend context

Returns: 0 if successful or error code otherwise.

Definition at line 156 of file dnn_backend_common.c.

Referenced by get_output_ov(), get_output_tf(), and get_output_th().

LIBAVUTIL_VERSION_INT

#define LIBAVUTIL_VERSION_INT

Definition: version.h:85

av_default_item_name

const char * av_default_item_name(void *ptr)

Return the context name.

Definition: log.c:237

AV_CLASS_CATEGORY_FILTER

@ AV_CLASS_CATEGORY_FILTER

Definition: log.h:36

options

const OptionDef options[]

desc

const char * desc

Definition: libsvtav1.c:79

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