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author | Shubhanshu Saxena <shubhanshu.e01@gmail.com> | 2021-06-05 23:38:02 +0530 |
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committer | Guo Yejun <yejun.guo@intel.com> | 2021-06-12 15:18:58 +0800 |
commit | f5ab8905fddee7a772998058e8cf18f93649fc5a (patch) | |
tree | 691393a95e556b6009fe058f67022f59ac552e33 /libavfilter/dnn | |
parent | 580e168a945b65100ec2c25433f33bfacfe9f7be (diff) | |
download | ffmpeg-f5ab8905fddee7a772998058e8cf18f93649fc5a.tar.gz |
lavfi/dnn: Extract TaskItem and InferenceItem from OpenVino Backend
Extract TaskItem and InferenceItem from OpenVino backend and convert
ov_model to void in TaskItem.
Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
Diffstat (limited to 'libavfilter/dnn')
-rw-r--r-- | libavfilter/dnn/dnn_backend_common.h | 19 | ||||
-rw-r--r-- | libavfilter/dnn/dnn_backend_openvino.c | 58 |
2 files changed, 40 insertions, 37 deletions
diff --git a/libavfilter/dnn/dnn_backend_common.h b/libavfilter/dnn/dnn_backend_common.h index cd9c0f5339..0c043e51f0 100644 --- a/libavfilter/dnn/dnn_backend_common.h +++ b/libavfilter/dnn/dnn_backend_common.h @@ -26,6 +26,25 @@ #include "../dnn_interface.h" +// one task for one function call from dnn interface +typedef struct TaskItem { + void *model; // model for the backend + AVFrame *in_frame; + AVFrame *out_frame; + const char *input_name; + const char *output_name; + int async; + int do_ioproc; + uint32_t inference_todo; + uint32_t inference_done; +} TaskItem; + +// one task might have multiple inferences +typedef struct InferenceItem { + TaskItem *task; + uint32_t bbox_index; +} InferenceItem; + int ff_check_exec_params(void *ctx, DNNBackendType backend, DNNFunctionType func_type, DNNExecBaseParams *exec_params); #endif diff --git a/libavfilter/dnn/dnn_backend_openvino.c b/libavfilter/dnn/dnn_backend_openvino.c index 58c4ec9c9b..a84370d689 100644 --- a/libavfilter/dnn/dnn_backend_openvino.c +++ b/libavfilter/dnn/dnn_backend_openvino.c @@ -59,25 +59,6 @@ typedef struct OVModel{ Queue *inference_queue; // holds InferenceItem } OVModel; -// one task for one function call from dnn interface -typedef struct TaskItem { - OVModel *ov_model; - const char *input_name; - AVFrame *in_frame; - const char *output_name; - AVFrame *out_frame; - int do_ioproc; - int async; - uint32_t inference_todo; - uint32_t inference_done; -} TaskItem; - -// one task might have multiple inferences -typedef struct InferenceItem { - TaskItem *task; - uint32_t bbox_index; -} InferenceItem; - // one request for one call to openvino typedef struct RequestItem { ie_infer_request_t *infer_request; @@ -184,7 +165,7 @@ static DNNReturnType fill_model_input_ov(OVModel *ov_model, RequestItem *request request->inferences[i] = inference; request->inference_count = i + 1; task = inference->task; - switch (task->ov_model->model->func_type) { + switch (ov_model->model->func_type) { case DFT_PROCESS_FRAME: if (task->do_ioproc) { if (ov_model->model->frame_pre_proc != NULL) { @@ -220,11 +201,12 @@ static void infer_completion_callback(void *args) RequestItem *request = args; InferenceItem *inference = request->inferences[0]; TaskItem *task = inference->task; - SafeQueue *requestq = task->ov_model->request_queue; + OVModel *ov_model = task->model; + SafeQueue *requestq = ov_model->request_queue; ie_blob_t *output_blob = NULL; ie_blob_buffer_t blob_buffer; DNNData output; - OVContext *ctx = &task->ov_model->ctx; + OVContext *ctx = &ov_model->ctx; status = ie_infer_request_get_blob(request->infer_request, task->output_name, &output_blob); if (status != OK) { @@ -233,9 +215,9 @@ static void infer_completion_callback(void *args) char *all_output_names = NULL; size_t model_output_count = 0; av_log(ctx, AV_LOG_ERROR, "Failed to get model output data\n"); - status = ie_network_get_outputs_number(task->ov_model->network, &model_output_count); + status = ie_network_get_outputs_number(ov_model->network, &model_output_count); for (size_t i = 0; i < model_output_count; i++) { - status = ie_network_get_output_name(task->ov_model->network, i, &model_output_name); + status = ie_network_get_output_name(ov_model->network, i, &model_output_name); APPEND_STRING(all_output_names, model_output_name) } av_log(ctx, AV_LOG_ERROR, @@ -271,11 +253,11 @@ static void infer_completion_callback(void *args) task = request->inferences[i]->task; task->inference_done++; - switch (task->ov_model->model->func_type) { + switch (ov_model->model->func_type) { case DFT_PROCESS_FRAME: if (task->do_ioproc) { - if (task->ov_model->model->frame_post_proc != NULL) { - task->ov_model->model->frame_post_proc(task->out_frame, &output, task->ov_model->model->filter_ctx); + if (ov_model->model->frame_post_proc != NULL) { + ov_model->model->frame_post_proc(task->out_frame, &output, ov_model->model->filter_ctx); } else { ff_proc_from_dnn_to_frame(task->out_frame, &output, ctx); } @@ -285,18 +267,18 @@ static void infer_completion_callback(void *args) } break; case DFT_ANALYTICS_DETECT: - if (!task->ov_model->model->detect_post_proc) { + if (!ov_model->model->detect_post_proc) { av_log(ctx, AV_LOG_ERROR, "detect filter needs to provide post proc\n"); return; } - task->ov_model->model->detect_post_proc(task->out_frame, &output, 1, task->ov_model->model->filter_ctx); + ov_model->model->detect_post_proc(task->out_frame, &output, 1, ov_model->model->filter_ctx); break; case DFT_ANALYTICS_CLASSIFY: - if (!task->ov_model->model->classify_post_proc) { + if (!ov_model->model->classify_post_proc) { av_log(ctx, AV_LOG_ERROR, "classify filter needs to provide post proc\n"); return; } - task->ov_model->model->classify_post_proc(task->out_frame, &output, request->inferences[i]->bbox_index, task->ov_model->model->filter_ctx); + ov_model->model->classify_post_proc(task->out_frame, &output, request->inferences[i]->bbox_index, ov_model->model->filter_ctx); break; default: av_assert0(!"should not reach here"); @@ -445,6 +427,7 @@ static DNNReturnType execute_model_ov(RequestItem *request, Queue *inferenceq) InferenceItem *inference; TaskItem *task; OVContext *ctx; + OVModel *ov_model; if (ff_queue_size(inferenceq) == 0) { return DNN_SUCCESS; @@ -452,10 +435,11 @@ static DNNReturnType execute_model_ov(RequestItem *request, Queue *inferenceq) inference = ff_queue_peek_front(inferenceq); task = inference->task; - ctx = &task->ov_model->ctx; + ov_model = task->model; + ctx = &ov_model->ctx; if (task->async) { - ret = fill_model_input_ov(task->ov_model, request); + ret = fill_model_input_ov(ov_model, request); if (ret != DNN_SUCCESS) { return ret; } @@ -471,7 +455,7 @@ static DNNReturnType execute_model_ov(RequestItem *request, Queue *inferenceq) } return DNN_SUCCESS; } else { - ret = fill_model_input_ov(task->ov_model, request); + ret = fill_model_input_ov(ov_model, request); if (ret != DNN_SUCCESS) { return ret; } @@ -694,7 +678,7 @@ static DNNReturnType get_output_ov(void *model, const char *input_name, int inpu task.in_frame = in_frame; task.output_name = output_name; task.out_frame = out_frame; - task.ov_model = ov_model; + task.model = ov_model; if (extract_inference_from_task(ov_model->model->func_type, &task, ov_model->inference_queue, NULL) != DNN_SUCCESS) { av_frame_free(&out_frame); @@ -814,7 +798,7 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, DNNExecBaseParams * task.in_frame = exec_params->in_frame; task.output_name = exec_params->output_names[0]; task.out_frame = exec_params->out_frame ? exec_params->out_frame : exec_params->in_frame; - task.ov_model = ov_model; + task.model = ov_model; if (extract_inference_from_task(ov_model->model->func_type, &task, ov_model->inference_queue, exec_params) != DNN_SUCCESS) { av_log(ctx, AV_LOG_ERROR, "unable to extract inference from task.\n"); @@ -861,7 +845,7 @@ DNNReturnType ff_dnn_execute_model_async_ov(const DNNModel *model, DNNExecBasePa task->in_frame = exec_params->in_frame; task->output_name = exec_params->output_names[0]; task->out_frame = exec_params->out_frame ? exec_params->out_frame : exec_params->in_frame; - task->ov_model = ov_model; + task->model = ov_model; if (ff_queue_push_back(ov_model->task_queue, task) < 0) { av_freep(&task); av_log(ctx, AV_LOG_ERROR, "unable to push back task_queue.\n"); |