> 2021年1月10日 下午9:16，Guo, Yejun <yejun....@intel.com> 写道：
>
> the default number of batch_size is 1
>
> Signed-off-by: Xie, Lin <lin....@intel.com>
> Signed-off-by: Wu Zhiwen <zhiwen...@intel.com>
> Signed-off-by: Guo, Yejun <yejun....@intel.com>
> ---
> libavfilter/dnn/dnn_backend_openvino.c | 187 ++++++++++++++++++++-----
> libavfilter/dnn/dnn_backend_openvino.h | 1 +
> libavfilter/dnn/dnn_interface.c | 1 +
> libavfilter/dnn_interface.h | 2 +
> libavfilter/vf_dnn_processing.c | 36 ++++-
> 5 files changed, 194 insertions(+), 33 deletions(-)
>
> diff --git a/libavfilter/dnn/dnn_backend_openvino.c
> b/libavfilter/dnn/dnn_backend_openvino.c
> index d27e451eea..5271d1caa5 100644
> --- a/libavfilter/dnn/dnn_backend_openvino.c
> +++ b/libavfilter/dnn/dnn_backend_openvino.c
> @@ -37,6 +37,7 @@
> typedef struct OVOptions{
> char *device_type;
> int nireq;
> + int batch_size;
> } OVOptions;
>
> typedef struct OVContext {
> @@ -70,7 +71,8 @@ typedef struct TaskItem {
>
> typedef struct RequestItem {
> ie_infer_request_t *infer_request;
> - TaskItem *task;
> + TaskItem **tasks;
> + int task_count;
> ie_complete_call_back_t callback;
> } RequestItem;
>
> @@ -83,6 +85,7 @@ typedef struct RequestItem {
> static const AVOption dnn_openvino_options[] = {
> { "device", "device to run model", OFFSET(options.device_type),
> AV_OPT_TYPE_STRING, { .str = "CPU" }, 0, 0, FLAGS },
> { "nireq", "number of request", OFFSET(options.nireq),
> AV_OPT_TYPE_INT, { .i64 = 0 }, 0, INT_MAX, FLAGS },
> + { "batch_size", "batch size per request", OFFSET(options.batch_size),
> AV_OPT_TYPE_INT, { .i64 = 1 }, 1, 1000, FLAGS},
> { NULL }
> };
>
> @@ -100,7 +103,19 @@ static DNNDataType precision_to_datatype(precision_e
> precision)
> }
> }
>
> -static DNNReturnType fill_model_input_ov(OVModel *ov_model, TaskItem *task,
> RequestItem *request)
> +static int get_datatype_size(DNNDataType dt)
> +{
> + switch (dt)
> + {
> + case DNN_FLOAT:
> + return sizeof(float);
> + default:
> + av_assert0(!"not supported yet.");
> + return 1;
Why don’t try about this way ? :D
avpriv_request_sample()
AVERROR_PATCHWELCOME;
> + }
> +}
> +
> +static DNNReturnType fill_model_input_ov(OVModel *ov_model, RequestItem
> *request)
> {
> dimensions_t dims;
> precision_e precision;
> @@ -109,6 +124,7 @@ static DNNReturnType fill_model_input_ov(OVModel
> *ov_model, TaskItem *task, Requ
> IEStatusCode status;
> DNNData input;
> ie_blob_t *input_blob = NULL;
> + TaskItem *task = request->tasks[0];
>
> status = ie_infer_request_get_blob(request->infer_request,
> task->input_name, &input_blob);
> if (status != OK) {
> @@ -134,12 +150,19 @@ static DNNReturnType fill_model_input_ov(OVModel
> *ov_model, TaskItem *task, Requ
> input.channels = dims.dims[1];
> input.data = blob_buffer.buffer;
> input.dt = precision_to_datatype(precision);
> - if (task->do_ioproc) {
> - if (ov_model->model->pre_proc != NULL) {
> - ov_model->model->pre_proc(task->in_frame, &input,
> ov_model->model->filter_ctx);
> - } else {
> - proc_from_frame_to_dnn(task->in_frame, &input, ctx);
> +
> + av_assert0(request->task_count <= dims.dims[0]);
> + for (int i = 0; i < request->task_count; ++i) {
> + task = request->tasks[i];
> + if (task->do_ioproc) {
> + if (ov_model->model->pre_proc != NULL) {
> + ov_model->model->pre_proc(task->in_frame, &input,
> ov_model->model->filter_ctx);
> + } else {
> + proc_from_frame_to_dnn(task->in_frame, &input, ctx);
> + }
> }
> + input.data = (uint8_t *)input.data
> + + input.width * input.height * input.channels *
> get_datatype_size(input.dt);
> }
> ie_blob_free(&input_blob);
>
> @@ -152,7 +175,7 @@ static void infer_completion_callback(void *args)
> precision_e precision;
> IEStatusCode status;
> RequestItem *request = args;
> - TaskItem *task = request->task;
> + TaskItem *task = request->tasks[0];
> ie_blob_t *output_blob = NULL;
> ie_blob_buffer_t blob_buffer;
> DNNData output;
> @@ -194,41 +217,56 @@ static void infer_completion_callback(void *args)
> output.width = dims.dims[3];
> output.dt = precision_to_datatype(precision);
> output.data = blob_buffer.buffer;
> - if (task->do_ioproc) {
> - if (task->ov_model->model->post_proc != NULL) {
> - task->ov_model->model->post_proc(task->out_frame, &output,
> task->ov_model->model->filter_ctx);
> +
> + av_assert0(request->task_count <= dims.dims[0]);
> + av_assert0(request->task_count >= 1);
> + for (int i = 0; i < request->task_count; ++i) {
> + task = request->tasks[i];
> + if (task->do_ioproc) {
> + if (task->ov_model->model->post_proc != NULL) {
> + task->ov_model->model->post_proc(task->out_frame, &output,
> task->ov_model->model->filter_ctx);
> + } else {
> + proc_from_dnn_to_frame(task->out_frame, &output, ctx);
> + }
> } else {
> - proc_from_dnn_to_frame(task->out_frame, &output, ctx);
> + task->out_frame->width = output.width;
> + task->out_frame->height = output.height;
> }
> - } else {
> - task->out_frame->width = output.width;
> - task->out_frame->height = output.height;
> + task->done = 1;
> + output.data = (uint8_t *)output.data
> + + output.width * output.height * output.channels *
> get_datatype_size(output.dt);
> }
> ie_blob_free(&output_blob);
>
> + request->task_count = 0;
> +
> if (task->async) {
> - request->task = NULL;
> if (ff_safe_queue_push_back(task->ov_model->request_queue, request) <
> 0) {
> av_log(ctx, AV_LOG_ERROR, "Failed to push back request_queue.\n");
> return;
> }
> }
> -
> - task->done = 1;
> }
>
> -static DNNReturnType execute_model_ov(TaskItem *task, RequestItem *request)
> +static DNNReturnType execute_model_ov(RequestItem *request)
> {
> IEStatusCode status;
> + DNNReturnType ret;
> + TaskItem *task = request->tasks[0];
> OVContext *ctx = &task->ov_model->ctx;
>
> - DNNReturnType ret = fill_model_input_ov(task->ov_model, task, request);
> - if (ret != DNN_SUCCESS) {
> - return ret;
> - }
> -
> if (task->async) {
> - request->task = task;
> + if (request->task_count < ctx->options.batch_size) {
> + if (ff_safe_queue_push_front(task->ov_model->request_queue,
> request) < 0) {
> + av_log(ctx, AV_LOG_ERROR, "Failed to push back
> request_queue.\n");
> + return DNN_ERROR;
> + }
> + return DNN_SUCCESS;
> + }
> + ret = fill_model_input_ov(task->ov_model, request);
> + if (ret != DNN_SUCCESS) {
> + return ret;
> + }
> status = ie_infer_set_completion_callback(request->infer_request,
> &request->callback);
> if (status != OK) {
> av_log(ctx, AV_LOG_ERROR, "Failed to set completion callback for
> inference\n");
> @@ -241,12 +279,15 @@ static DNNReturnType execute_model_ov(TaskItem *task,
> RequestItem *request)
> }
> return DNN_SUCCESS;
> } else {
> + ret = fill_model_input_ov(task->ov_model, request);
> + if (ret != DNN_SUCCESS) {
> + return ret;
> + }
> status = ie_infer_request_infer(request->infer_request);
> if (status != OK) {
> av_log(ctx, AV_LOG_ERROR, "Failed to start synchronous model
> inference\n");
> return DNN_ERROR;
> }
> - request->task = task;
> infer_completion_callback(request);
> return task->done ? DNN_SUCCESS : DNN_ERROR;
> }
> @@ -319,6 +360,7 @@ static DNNReturnType get_output_ov(void *model, const
> char *input_name, int inpu
> RequestItem request;
> AVFrame *in_frame = av_frame_alloc();
> AVFrame *out_frame = NULL;
> + TaskItem *ptask = &task;
>
> if (!in_frame) {
> av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for input
> frame\n");
> @@ -343,8 +385,10 @@ static DNNReturnType get_output_ov(void *model, const
> char *input_name, int inpu
> task.ov_model = ov_model;
>
> request.infer_request = ov_model->infer_request;
> + request.task_count = 1;
> + request.tasks = &ptask;
>
> - ret = execute_model_ov(&task, &request);
> + ret = execute_model_ov(&request);
> *output_width = out_frame->width;
> *output_height = out_frame->height;
>
> @@ -393,6 +437,24 @@ DNNModel *ff_dnn_load_model_ov(const char
> *model_filename, const char *options,
> if (status != OK)
> goto err;
>
> + // batch size
> + if (ctx->options.batch_size <= 0) {
> + ctx->options.batch_size = 1;
> + }
> +
> + if (ctx->options.batch_size > 1) {
> + input_shapes_t input_shapes;
> + status = ie_network_get_input_shapes(ov_model->network,
> &input_shapes);
> + if (status != OK)
> + goto err;
> + for (int i = 0; i < input_shapes.shape_num; i++)
> + input_shapes.shapes[i].shape.dims[0] = ctx->options.batch_size;
> + status = ie_network_reshape(ov_model->network, input_shapes);
> + ie_network_input_shapes_free(&input_shapes);
> + if (status != OK)
> + goto err;
> + }
> +
> status = ie_core_load_network(ov_model->core, ov_model->network,
> ctx->options.device_type, &config, &ov_model->exe_network);
> if (status != OK) {
> av_log(ctx, AV_LOG_ERROR, "Failed to init OpenVINO model\n");
> @@ -426,17 +488,24 @@ DNNModel *ff_dnn_load_model_ov(const char
> *model_filename, const char *options,
> }
>
> for (int i = 0; i < ctx->options.nireq; i++) {
> - ie_infer_request_t *request;
> RequestItem *item = av_mallocz(sizeof(*item));
> if (!item) {
> goto err;
> }
> - status = ie_exec_network_create_infer_request(ov_model->exe_network,
> &request);
> +
> + status = ie_exec_network_create_infer_request(ov_model->exe_network,
> &item->infer_request);
> if (status != OK) {
> av_freep(&item);
> goto err;
> }
> - item->infer_request = request;
> +
> + item->tasks = av_malloc_array(ctx->options.batch_size,
> sizeof(*item->tasks));
> + if (!item->tasks) {
> + av_freep(&item);
> + goto err;
> + }
> + item->task_count = 0;
> +
> item->callback.completeCallBackFunc = infer_completion_callback;
> item->callback.args = item;
> if (ff_safe_queue_push_back(ov_model->request_queue, item) < 0) {
> @@ -469,6 +538,7 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel
> *model, const char *input_n
> OVContext *ctx = &ov_model->ctx;
> TaskItem task;
> RequestItem request;
> + TaskItem *ptask = &task;
>
> if (!in_frame) {
> av_log(ctx, AV_LOG_ERROR, "in frame is NULL when execute model.\n");
> @@ -487,6 +557,11 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel
> *model, const char *input_n
> return DNN_ERROR;
> }
>
> + if (ctx->options.batch_size > 1) {
> + av_log(ctx, AV_LOG_ERROR, "do not support batch mode for sync
> execution.\n");
> + return DNN_ERROR;
> + }
> +
> task.done = 0;
> task.do_ioproc = 1;
> task.async = 0;
> @@ -497,8 +572,10 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel
> *model, const char *input_n
> task.ov_model = ov_model;
>
> request.infer_request = ov_model->infer_request;
> + request.task_count = 1;
> + request.tasks = &ptask;
>
> - return execute_model_ov(&task, &request);
> + return execute_model_ov(&request);
> }
>
> DNNReturnType ff_dnn_execute_model_async_ov(const DNNModel *model, const char
> *input_name, AVFrame *in_frame,
> @@ -545,7 +622,8 @@ DNNReturnType ff_dnn_execute_model_async_ov(const
> DNNModel *model, const char *i
> return DNN_ERROR;
> }
>
> - return execute_model_ov(task, request);
> + request->tasks[request->task_count++] = task;
> + return execute_model_ov(request);
> }
>
> DNNAsyncStatusType ff_dnn_get_async_result_ov(const DNNModel *model, AVFrame
> **in, AVFrame **out)
> @@ -569,6 +647,48 @@ DNNAsyncStatusType ff_dnn_get_async_result_ov(const
> DNNModel *model, AVFrame **i
> return DAST_SUCCESS;
> }
>
> +DNNReturnType ff_dnn_flush_ov(const DNNModel *model)
> +{
> + OVModel *ov_model = (OVModel *)model->model;
> + OVContext *ctx = &ov_model->ctx;
> + RequestItem *request;
> + IEStatusCode status;
> + DNNReturnType ret;
> +
> + request = ff_safe_queue_pop_front(ov_model->request_queue);
> + if (!request) {
> + av_log(ctx, AV_LOG_ERROR, "unable to get infer request.\n");
> + return DNN_ERROR;
> + }
> +
> + if (request->task_count == 0) {
> + // no pending task need to flush
> + if (ff_safe_queue_push_back(ov_model->request_queue, request) < 0) {
> + av_log(ctx, AV_LOG_ERROR, "Failed to push back
> request_queue.\n");
> + return DNN_ERROR;
> + }
> + return DNN_SUCCESS;
> + }
> +
> + ret = fill_model_input_ov(ov_model, request);
> + if (ret != DNN_SUCCESS) {
> + av_log(ctx, AV_LOG_ERROR, "Failed to fill model input.\n");
> + return ret;
> + }
> + status = ie_infer_set_completion_callback(request->infer_request,
> &request->callback);
> + if (status != OK) {
> + av_log(ctx, AV_LOG_ERROR, "Failed to set completion callback for
> inference\n");
> + return DNN_ERROR;
> + }
> + status = ie_infer_request_infer_async(request->infer_request);
> + if (status != OK) {
> + av_log(ctx, AV_LOG_ERROR, "Failed to start async inference\n");
> + return DNN_ERROR;
> + }
> +
> + return DNN_SUCCESS;
> +}
> +
> void ff_dnn_free_model_ov(DNNModel **model)
> {
> if (*model){
> @@ -578,12 +698,15 @@ void ff_dnn_free_model_ov(DNNModel **model)
> if (item && item->infer_request) {
> ie_infer_request_free(&item->infer_request);
> }
> + av_freep(&item->tasks);
> av_freep(&item);
> }
> ff_safe_queue_destroy(ov_model->request_queue);
>
> while (ff_queue_size(ov_model->task_queue) != 0) {
> TaskItem *item = ff_queue_pop_front(ov_model->task_queue);
> + av_frame_free(&item->in_frame);
> + av_frame_free(&item->out_frame);
> av_freep(&item);
> }
> ff_queue_destroy(ov_model->task_queue);
> diff --git a/libavfilter/dnn/dnn_backend_openvino.h
> b/libavfilter/dnn/dnn_backend_openvino.h
> index 1b70150040..23b819440e 100644
> --- a/libavfilter/dnn/dnn_backend_openvino.h
> +++ b/libavfilter/dnn/dnn_backend_openvino.h
> @@ -36,6 +36,7 @@ DNNReturnType ff_dnn_execute_model_ov(const DNNModel
> *model, const char *input_n
> DNNReturnType ff_dnn_execute_model_async_ov(const DNNModel *model, const char
> *input_name, AVFrame *in_frame,
> const char **output_names,
> uint32_t nb_output, AVFrame *out_frame);
> DNNAsyncStatusType ff_dnn_get_async_result_ov(const DNNModel *model, AVFrame
> **in, AVFrame **out);
> +DNNReturnType ff_dnn_flush_ov(const DNNModel *model);
>
> void ff_dnn_free_model_ov(DNNModel **model);
>
> diff --git a/libavfilter/dnn/dnn_interface.c b/libavfilter/dnn/dnn_interface.c
> index e1b41a21e1..02e532fc1b 100644
> --- a/libavfilter/dnn/dnn_interface.c
> +++ b/libavfilter/dnn/dnn_interface.c
> @@ -60,6 +60,7 @@ DNNModule *ff_get_dnn_module(DNNBackendType backend_type)
> dnn_module->execute_model = &ff_dnn_execute_model_ov;
> dnn_module->execute_model_async = &ff_dnn_execute_model_async_ov;
> dnn_module->get_async_result = &ff_dnn_get_async_result_ov;
> + dnn_module->flush = &ff_dnn_flush_ov;
> dnn_module->free_model = &ff_dnn_free_model_ov;
> #else
> av_freep(&dnn_module);
> diff --git a/libavfilter/dnn_interface.h b/libavfilter/dnn_interface.h
> index 9533c88829..ff338ea084 100644
> --- a/libavfilter/dnn_interface.h
> +++ b/libavfilter/dnn_interface.h
> @@ -82,6 +82,8 @@ typedef struct DNNModule{
> const char **output_names, uint32_t
> nb_output, AVFrame *out_frame);
> // Retrieve inference result.
> DNNAsyncStatusType (*get_async_result)(const DNNModel *model, AVFrame
> **in, AVFrame **out);
> + // Flush all the pending tasks.
> + DNNReturnType (*flush)(const DNNModel *model);
> // Frees memory allocated for model.
> void (*free_model)(DNNModel **model);
> } DNNModule;
> diff --git a/libavfilter/vf_dnn_processing.c b/libavfilter/vf_dnn_processing.c
> index fff5696a31..be48631782 100644
> --- a/libavfilter/vf_dnn_processing.c
> +++ b/libavfilter/vf_dnn_processing.c
> @@ -33,6 +33,7 @@
> #include "formats.h"
> #include "internal.h"
> #include "libswscale/swscale.h"
> +#include "libavutil/time.h"
>
> typedef struct DnnProcessingContext {
> const AVClass *class;
> @@ -369,6 +370,37 @@ static int activate_sync(AVFilterContext *filter_ctx)
> return FFERROR_NOT_READY;
> }
>
> +static int flush_frame(AVFilterLink *outlink, int64_t pts, int64_t *out_pts)
> +{
> + DnnProcessingContext *ctx = outlink->src->priv;
> + int ret;
> + DNNAsyncStatusType async_state;
> +
> + ret = (ctx->dnn_module->flush)(ctx->model);
> + if (ret != DNN_SUCCESS) {
> + return -1;
> + }
> +
> + do {
> + AVFrame *in_frame = NULL;
> + AVFrame *out_frame = NULL;
> + async_state = (ctx->dnn_module->get_async_result)(ctx->model,
> &in_frame, &out_frame);
> + 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];
> @@ -423,7 +455,9 @@ 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;
> }
> }
> --
> 2.17.1
>
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> ffmpeg-devel-requ...@ffmpeg.org with subject "unsubscribe".
Thanks
Steven Liu
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