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27 #define DNN_ASYNC_SUCCESS (void *)0
28 #define DNN_ASYNC_FAIL (void *)-1
51 if (task ==
NULL || exec_params ==
NULL || backend_model ==
NULL)
53 if (do_ioproc != 0 && do_ioproc != 1)
55 if (async != 0 && async != 1)
63 task->
model = backend_model;
77 void *request = async_module->
args;
92 #if HAVE_PTHREAD_CANCEL
115 #if HAVE_PTHREAD_CANCEL
174 in_frame->
width = input_width;
175 in_frame->
height = input_height;
static av_always_inline int pthread_join(pthread_t thread, void **value_ptr)
Filter the word “frame” indicates either a video frame or a group of audio as stored in an AVFrame structure Format for each input and each output the list of supported formats For video that means pixel format For audio that means channel sample they are references to shared objects When the negotiation mechanism computes the intersection of the formats supported at each end of a all references to both lists are replaced with a reference to the intersection And when a single format is eventually chosen for a link amongst the remaining all references to the list are updated That means that if a filter requires that its input and output have the same format amongst a supported all it has to do is use a reference to the same list of formats query_formats can leave some formats unset and return AVERROR(EAGAIN) to cause the negotiation mechanism toagain later. That can be used by filters with complex requirements to use the format negotiated on one link to set the formats supported on another. Frame references ownership and permissions
Common Async Execution Mechanism for the DNN Backends.
void * ff_queue_pop_front(Queue *q)
Remove and free first element from the Queue.
int ff_check_exec_params(void *ctx, DNNBackendType backend, DNNFunctionType func_type, DNNExecBaseParams *exec_params)
#define DNN_GENERIC_ERROR
void av_frame_free(AVFrame **frame)
Free the frame and any dynamically allocated objects in it, e.g.
This structure describes decoded (raw) audio or video data.
void(* callback)(void *args)
Completion Callback for the backend.
#define DNN_ASYNC_SUCCESS
Linear double-ended data structure.
AVFrame * av_frame_alloc(void)
Allocate an AVFrame and set its fields to default values.
#define AV_LOG_ERROR
Something went wrong and cannot losslessly be recovered.
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.
static av_always_inline int pthread_create(pthread_t *thread, const pthread_attr_t *attr, void *(*start_routine)(void *), void *arg)
int ff_dnn_async_module_cleanup(DNNAsyncExecModule *async_module)
Join the Async Execution thread and set module pointers to NULL.
int ff_dnn_fill_task(TaskItem *task, DNNExecBaseParams *exec_params, void *backend_model, int async, int do_ioproc)
Fill the Task for Backend Execution.
int(* start_inference)(void *request)
Synchronous inference function for the backend with corresponding request item as the argument.
void * args
Argument for the execution functions.
const char ** output_names
static void * async_thread_routine(void *args)
Thread routine for async execution.
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.
void * ff_queue_peek_front(Queue *q)
Return a pointer to the data at the head of the queue.
const char ** output_names
int ff_dnn_start_inference_async(void *ctx, DNNAsyncExecModule *async_module)
Start asynchronous inference routine for the TensorFlow model on a detached thread.