mirror of
https://github.com/FFmpeg/FFmpeg.git
synced 2024-12-23 12:43:46 +02:00
libavfilter/dnn: add batch mode for async execution
the default number of batch_size is 1 Signed-off-by: Xie, Lin <lin.xie@intel.com> Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
This commit is contained in:
parent
57dae5723f
commit
64ea15f050
@ -37,6 +37,7 @@
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typedef struct OVOptions{
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char *device_type;
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int nireq;
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int batch_size;
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} OVOptions;
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typedef struct OVContext {
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@ -70,7 +71,8 @@ typedef struct TaskItem {
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typedef struct RequestItem {
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ie_infer_request_t *infer_request;
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TaskItem *task;
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TaskItem **tasks;
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int task_count;
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ie_complete_call_back_t callback;
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} RequestItem;
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@ -83,6 +85,7 @@ typedef struct RequestItem {
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static const AVOption dnn_openvino_options[] = {
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{ "device", "device to run model", OFFSET(options.device_type), AV_OPT_TYPE_STRING, { .str = "CPU" }, 0, 0, FLAGS },
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{ "nireq", "number of request", OFFSET(options.nireq), AV_OPT_TYPE_INT, { .i64 = 0 }, 0, INT_MAX, FLAGS },
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{ "batch_size", "batch size per request", OFFSET(options.batch_size), AV_OPT_TYPE_INT, { .i64 = 1 }, 1, 1000, FLAGS},
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{ NULL }
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};
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@ -100,7 +103,19 @@ static DNNDataType precision_to_datatype(precision_e precision)
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}
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}
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static DNNReturnType fill_model_input_ov(OVModel *ov_model, TaskItem *task, RequestItem *request)
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static int get_datatype_size(DNNDataType dt)
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{
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switch (dt)
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{
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case DNN_FLOAT:
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return sizeof(float);
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default:
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av_assert0(!"not supported yet.");
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return 1;
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}
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}
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static DNNReturnType fill_model_input_ov(OVModel *ov_model, RequestItem *request)
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{
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dimensions_t dims;
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precision_e precision;
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@ -109,6 +124,7 @@ static DNNReturnType fill_model_input_ov(OVModel *ov_model, TaskItem *task, Requ
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IEStatusCode status;
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DNNData input;
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ie_blob_t *input_blob = NULL;
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TaskItem *task = request->tasks[0];
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status = ie_infer_request_get_blob(request->infer_request, task->input_name, &input_blob);
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if (status != OK) {
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@ -134,12 +150,19 @@ static DNNReturnType fill_model_input_ov(OVModel *ov_model, TaskItem *task, Requ
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input.channels = dims.dims[1];
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input.data = blob_buffer.buffer;
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input.dt = precision_to_datatype(precision);
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if (task->do_ioproc) {
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if (ov_model->model->pre_proc != NULL) {
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ov_model->model->pre_proc(task->in_frame, &input, ov_model->model->filter_ctx);
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} else {
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proc_from_frame_to_dnn(task->in_frame, &input, ctx);
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av_assert0(request->task_count <= dims.dims[0]);
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for (int i = 0; i < request->task_count; ++i) {
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task = request->tasks[i];
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if (task->do_ioproc) {
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if (ov_model->model->pre_proc != NULL) {
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ov_model->model->pre_proc(task->in_frame, &input, ov_model->model->filter_ctx);
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} else {
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proc_from_frame_to_dnn(task->in_frame, &input, ctx);
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}
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}
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input.data = (uint8_t *)input.data
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+ input.width * input.height * input.channels * get_datatype_size(input.dt);
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}
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ie_blob_free(&input_blob);
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@ -152,7 +175,7 @@ static void infer_completion_callback(void *args)
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precision_e precision;
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IEStatusCode status;
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RequestItem *request = args;
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TaskItem *task = request->task;
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TaskItem *task = request->tasks[0];
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ie_blob_t *output_blob = NULL;
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ie_blob_buffer_t blob_buffer;
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DNNData output;
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@ -194,41 +217,56 @@ static void infer_completion_callback(void *args)
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output.width = dims.dims[3];
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output.dt = precision_to_datatype(precision);
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output.data = blob_buffer.buffer;
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if (task->do_ioproc) {
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if (task->ov_model->model->post_proc != NULL) {
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task->ov_model->model->post_proc(task->out_frame, &output, task->ov_model->model->filter_ctx);
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av_assert0(request->task_count <= dims.dims[0]);
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av_assert0(request->task_count >= 1);
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for (int i = 0; i < request->task_count; ++i) {
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task = request->tasks[i];
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if (task->do_ioproc) {
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if (task->ov_model->model->post_proc != NULL) {
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task->ov_model->model->post_proc(task->out_frame, &output, task->ov_model->model->filter_ctx);
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} else {
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proc_from_dnn_to_frame(task->out_frame, &output, ctx);
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}
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} else {
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proc_from_dnn_to_frame(task->out_frame, &output, ctx);
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task->out_frame->width = output.width;
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task->out_frame->height = output.height;
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}
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} else {
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task->out_frame->width = output.width;
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task->out_frame->height = output.height;
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task->done = 1;
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output.data = (uint8_t *)output.data
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+ output.width * output.height * output.channels * get_datatype_size(output.dt);
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}
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ie_blob_free(&output_blob);
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request->task_count = 0;
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if (task->async) {
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request->task = NULL;
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if (ff_safe_queue_push_back(task->ov_model->request_queue, request) < 0) {
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av_log(ctx, AV_LOG_ERROR, "Failed to push back request_queue.\n");
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return;
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}
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}
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task->done = 1;
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}
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static DNNReturnType execute_model_ov(TaskItem *task, RequestItem *request)
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static DNNReturnType execute_model_ov(RequestItem *request)
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{
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IEStatusCode status;
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DNNReturnType ret;
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TaskItem *task = request->tasks[0];
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OVContext *ctx = &task->ov_model->ctx;
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DNNReturnType ret = fill_model_input_ov(task->ov_model, task, request);
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if (ret != DNN_SUCCESS) {
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return ret;
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}
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if (task->async) {
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request->task = task;
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if (request->task_count < ctx->options.batch_size) {
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if (ff_safe_queue_push_front(task->ov_model->request_queue, request) < 0) {
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av_log(ctx, AV_LOG_ERROR, "Failed to push back request_queue.\n");
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return DNN_ERROR;
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}
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return DNN_SUCCESS;
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}
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ret = fill_model_input_ov(task->ov_model, request);
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if (ret != DNN_SUCCESS) {
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return ret;
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}
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status = ie_infer_set_completion_callback(request->infer_request, &request->callback);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to set completion callback for inference\n");
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@ -241,12 +279,15 @@ static DNNReturnType execute_model_ov(TaskItem *task, RequestItem *request)
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}
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return DNN_SUCCESS;
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} else {
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ret = fill_model_input_ov(task->ov_model, request);
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if (ret != DNN_SUCCESS) {
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return ret;
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}
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status = ie_infer_request_infer(request->infer_request);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to start synchronous model inference\n");
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return DNN_ERROR;
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}
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request->task = task;
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infer_completion_callback(request);
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return task->done ? DNN_SUCCESS : DNN_ERROR;
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}
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@ -319,6 +360,7 @@ static DNNReturnType get_output_ov(void *model, const char *input_name, int inpu
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RequestItem request;
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AVFrame *in_frame = av_frame_alloc();
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AVFrame *out_frame = NULL;
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TaskItem *ptask = &task;
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if (!in_frame) {
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av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for input frame\n");
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@ -343,8 +385,10 @@ static DNNReturnType get_output_ov(void *model, const char *input_name, int inpu
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task.ov_model = ov_model;
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request.infer_request = ov_model->infer_request;
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request.task_count = 1;
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request.tasks = &ptask;
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ret = execute_model_ov(&task, &request);
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ret = execute_model_ov(&request);
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*output_width = out_frame->width;
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*output_height = out_frame->height;
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@ -393,6 +437,24 @@ DNNModel *ff_dnn_load_model_ov(const char *model_filename, const char *options,
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if (status != OK)
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goto err;
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// batch size
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if (ctx->options.batch_size <= 0) {
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ctx->options.batch_size = 1;
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}
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if (ctx->options.batch_size > 1) {
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input_shapes_t input_shapes;
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status = ie_network_get_input_shapes(ov_model->network, &input_shapes);
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if (status != OK)
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goto err;
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for (int i = 0; i < input_shapes.shape_num; i++)
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input_shapes.shapes[i].shape.dims[0] = ctx->options.batch_size;
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status = ie_network_reshape(ov_model->network, input_shapes);
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ie_network_input_shapes_free(&input_shapes);
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if (status != OK)
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goto err;
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}
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status = ie_core_load_network(ov_model->core, ov_model->network, ctx->options.device_type, &config, &ov_model->exe_network);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to init OpenVINO model\n");
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@ -426,17 +488,24 @@ DNNModel *ff_dnn_load_model_ov(const char *model_filename, const char *options,
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}
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for (int i = 0; i < ctx->options.nireq; i++) {
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ie_infer_request_t *request;
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RequestItem *item = av_mallocz(sizeof(*item));
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if (!item) {
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goto err;
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}
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status = ie_exec_network_create_infer_request(ov_model->exe_network, &request);
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status = ie_exec_network_create_infer_request(ov_model->exe_network, &item->infer_request);
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if (status != OK) {
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av_freep(&item);
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goto err;
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}
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item->infer_request = request;
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item->tasks = av_malloc_array(ctx->options.batch_size, sizeof(*item->tasks));
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if (!item->tasks) {
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av_freep(&item);
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goto err;
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}
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item->task_count = 0;
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item->callback.completeCallBackFunc = infer_completion_callback;
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item->callback.args = item;
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if (ff_safe_queue_push_back(ov_model->request_queue, item) < 0) {
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@ -469,6 +538,7 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, const char *input_n
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OVContext *ctx = &ov_model->ctx;
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TaskItem task;
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RequestItem request;
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TaskItem *ptask = &task;
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if (!in_frame) {
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av_log(ctx, AV_LOG_ERROR, "in frame is NULL when execute model.\n");
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@ -487,6 +557,11 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, const char *input_n
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return DNN_ERROR;
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}
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if (ctx->options.batch_size > 1) {
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av_log(ctx, AV_LOG_ERROR, "do not support batch mode for sync execution.\n");
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return DNN_ERROR;
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}
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task.done = 0;
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task.do_ioproc = 1;
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task.async = 0;
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@ -497,8 +572,10 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, const char *input_n
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task.ov_model = ov_model;
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request.infer_request = ov_model->infer_request;
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request.task_count = 1;
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request.tasks = &ptask;
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return execute_model_ov(&task, &request);
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return execute_model_ov(&request);
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}
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DNNReturnType ff_dnn_execute_model_async_ov(const DNNModel *model, const char *input_name, AVFrame *in_frame,
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@ -545,7 +622,8 @@ DNNReturnType ff_dnn_execute_model_async_ov(const DNNModel *model, const char *i
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return DNN_ERROR;
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}
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return execute_model_ov(task, request);
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request->tasks[request->task_count++] = task;
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return execute_model_ov(request);
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}
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DNNAsyncStatusType ff_dnn_get_async_result_ov(const DNNModel *model, AVFrame **in, AVFrame **out)
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@ -569,6 +647,48 @@ DNNAsyncStatusType ff_dnn_get_async_result_ov(const DNNModel *model, AVFrame **i
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return DAST_SUCCESS;
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}
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DNNReturnType ff_dnn_flush_ov(const DNNModel *model)
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{
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OVModel *ov_model = (OVModel *)model->model;
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OVContext *ctx = &ov_model->ctx;
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RequestItem *request;
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IEStatusCode status;
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DNNReturnType ret;
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request = ff_safe_queue_pop_front(ov_model->request_queue);
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if (!request) {
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av_log(ctx, AV_LOG_ERROR, "unable to get infer request.\n");
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return DNN_ERROR;
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}
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if (request->task_count == 0) {
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// no pending task need to flush
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if (ff_safe_queue_push_back(ov_model->request_queue, request) < 0) {
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av_log(ctx, AV_LOG_ERROR, "Failed to push back request_queue.\n");
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return DNN_ERROR;
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}
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return DNN_SUCCESS;
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}
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ret = fill_model_input_ov(ov_model, request);
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if (ret != DNN_SUCCESS) {
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av_log(ctx, AV_LOG_ERROR, "Failed to fill model input.\n");
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return ret;
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}
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status = ie_infer_set_completion_callback(request->infer_request, &request->callback);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to set completion callback for inference\n");
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return DNN_ERROR;
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}
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status = ie_infer_request_infer_async(request->infer_request);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to start async inference\n");
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return DNN_ERROR;
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}
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return DNN_SUCCESS;
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}
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void ff_dnn_free_model_ov(DNNModel **model)
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{
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if (*model){
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@ -578,12 +698,15 @@ void ff_dnn_free_model_ov(DNNModel **model)
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if (item && item->infer_request) {
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ie_infer_request_free(&item->infer_request);
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}
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av_freep(&item->tasks);
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av_freep(&item);
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}
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ff_safe_queue_destroy(ov_model->request_queue);
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while (ff_queue_size(ov_model->task_queue) != 0) {
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TaskItem *item = ff_queue_pop_front(ov_model->task_queue);
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av_frame_free(&item->in_frame);
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av_frame_free(&item->out_frame);
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av_freep(&item);
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}
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ff_queue_destroy(ov_model->task_queue);
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@ -36,6 +36,7 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, const char *input_n
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DNNReturnType ff_dnn_execute_model_async_ov(const DNNModel *model, const char *input_name, AVFrame *in_frame,
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const char **output_names, uint32_t nb_output, AVFrame *out_frame);
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DNNAsyncStatusType ff_dnn_get_async_result_ov(const DNNModel *model, AVFrame **in, AVFrame **out);
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DNNReturnType ff_dnn_flush_ov(const DNNModel *model);
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void ff_dnn_free_model_ov(DNNModel **model);
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@ -60,6 +60,7 @@ DNNModule *ff_get_dnn_module(DNNBackendType backend_type)
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dnn_module->execute_model = &ff_dnn_execute_model_ov;
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dnn_module->execute_model_async = &ff_dnn_execute_model_async_ov;
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dnn_module->get_async_result = &ff_dnn_get_async_result_ov;
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dnn_module->flush = &ff_dnn_flush_ov;
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dnn_module->free_model = &ff_dnn_free_model_ov;
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#else
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av_freep(&dnn_module);
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@ -82,6 +82,8 @@ typedef struct DNNModule{
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const char **output_names, uint32_t nb_output, AVFrame *out_frame);
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// Retrieve inference result.
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DNNAsyncStatusType (*get_async_result)(const DNNModel *model, AVFrame **in, AVFrame **out);
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// Flush all the pending tasks.
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DNNReturnType (*flush)(const DNNModel *model);
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// Frees memory allocated for model.
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void (*free_model)(DNNModel **model);
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} DNNModule;
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@ -33,6 +33,7 @@
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#include "formats.h"
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#include "internal.h"
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#include "libswscale/swscale.h"
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#include "libavutil/time.h"
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typedef struct DnnProcessingContext {
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const AVClass *class;
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@ -369,6 +370,37 @@ static int activate_sync(AVFilterContext *filter_ctx)
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return FFERROR_NOT_READY;
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}
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static int flush_frame(AVFilterLink *outlink, int64_t pts, int64_t *out_pts)
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{
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DnnProcessingContext *ctx = outlink->src->priv;
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int ret;
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DNNAsyncStatusType async_state;
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ret = (ctx->dnn_module->flush)(ctx->model);
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if (ret != DNN_SUCCESS) {
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return -1;
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}
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do {
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AVFrame *in_frame = NULL;
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AVFrame *out_frame = NULL;
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async_state = (ctx->dnn_module->get_async_result)(ctx->model, &in_frame, &out_frame);
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if (out_frame) {
|
||||
if (isPlanarYUV(in_frame->format))
|
||||
copy_uv_planes(ctx, out_frame, in_frame);
|
||||
av_frame_free(&in_frame);
|
||||
ret = ff_filter_frame(outlink, out_frame);
|
||||
if (ret < 0)
|
||||
return ret;
|
||||
if (out_pts)
|
||||
*out_pts = out_frame->pts + pts;
|
||||
}
|
||||
av_usleep(5000);
|
||||
} while (async_state >= DAST_NOT_READY);
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
static int activate_async(AVFilterContext *filter_ctx)
|
||||
{
|
||||
AVFilterLink *inlink = filter_ctx->inputs[0];
|
||||
@ -396,7 +428,7 @@ static int activate_async(AVFilterContext *filter_ctx)
|
||||
av_frame_copy_props(out, in);
|
||||
if ((ctx->dnn_module->execute_model_async)(ctx->model, ctx->model_inputname, in,
|
||||
(const char **)&ctx->model_outputname, 1, out) != DNN_SUCCESS) {
|
||||
return FFERROR_NOT_READY;
|
||||
return AVERROR(EIO);
|
||||
}
|
||||
}
|
||||
} while (ret > 0);
|
||||
@ -423,14 +455,16 @@ static int activate_async(AVFilterContext *filter_ctx)
|
||||
|
||||
if (ff_inlink_acknowledge_status(inlink, &status, &pts)) {
|
||||
if (status == AVERROR_EOF) {
|
||||
ff_outlink_set_status(outlink, status, pts);
|
||||
int64_t out_pts = pts;
|
||||
ret = flush_frame(outlink, pts, &out_pts);
|
||||
ff_outlink_set_status(outlink, status, out_pts);
|
||||
return ret;
|
||||
}
|
||||
}
|
||||
|
||||
FF_FILTER_FORWARD_WANTED(outlink, inlink);
|
||||
|
||||
return FFERROR_NOT_READY;
|
||||
return 0;
|
||||
}
|
||||
|
||||
static int activate(AVFilterContext *filter_ctx)
|
||||
|
Loading…
Reference in New Issue
Block a user