mirror of https://git.ffmpeg.org/ffmpeg.git
790 lines
25 KiB
C
790 lines
25 KiB
C
/*
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* Copyright (c) 2020
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*
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* This file is part of FFmpeg.
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*
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* FFmpeg is free software; you can redistribute it and/or
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* modify it under the terms of the GNU Lesser General Public
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* License as published by the Free Software Foundation; either
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* version 2.1 of the License, or (at your option) any later version.
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*
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* FFmpeg is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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* Lesser General Public License for more details.
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*
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* You should have received a copy of the GNU Lesser General Public
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* License along with FFmpeg; if not, write to the Free Software
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* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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*/
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/**
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* @file
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* DNN OpenVINO backend implementation.
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*/
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#include "dnn_backend_openvino.h"
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#include "dnn_io_proc.h"
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#include "libavformat/avio.h"
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#include "libavutil/avassert.h"
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#include "libavutil/opt.h"
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#include "libavutil/avstring.h"
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#include "../internal.h"
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#include "queue.h"
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#include "safe_queue.h"
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#include <c_api/ie_c_api.h>
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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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int input_resizable;
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} OVOptions;
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typedef struct OVContext {
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const AVClass *class;
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OVOptions options;
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} OVContext;
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typedef struct OVModel{
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OVContext ctx;
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DNNModel *model;
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ie_core_t *core;
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ie_network_t *network;
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ie_executable_network_t *exe_network;
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ie_infer_request_t *infer_request;
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/* for async execution */
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SafeQueue *request_queue; // holds RequestItem
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Queue *task_queue; // holds TaskItem
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} OVModel;
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typedef struct TaskItem {
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OVModel *ov_model;
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const char *input_name;
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AVFrame *in_frame;
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const char *output_name;
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AVFrame *out_frame;
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int do_ioproc;
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int async;
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int done;
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} TaskItem;
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typedef struct RequestItem {
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ie_infer_request_t *infer_request;
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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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#define APPEND_STRING(generated_string, iterate_string) \
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generated_string = generated_string ? av_asprintf("%s %s", generated_string, iterate_string) : \
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av_asprintf("%s", iterate_string);
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#define OFFSET(x) offsetof(OVContext, x)
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#define FLAGS AV_OPT_FLAG_FILTERING_PARAM
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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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{ "input_resizable", "can input be resizable or not", OFFSET(options.input_resizable), AV_OPT_TYPE_BOOL, { .i64 = 0 }, 0, 1, FLAGS },
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{ NULL }
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};
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AVFILTER_DEFINE_CLASS(dnn_openvino);
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static DNNDataType precision_to_datatype(precision_e precision)
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{
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switch (precision)
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{
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case FP32:
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return DNN_FLOAT;
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default:
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av_assert0(!"not supported yet.");
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return DNN_FLOAT;
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}
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}
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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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ie_blob_buffer_t blob_buffer;
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OVContext *ctx = &ov_model->ctx;
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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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av_log(ctx, AV_LOG_ERROR, "Failed to get input blob with name %s\n", task->input_name);
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return DNN_ERROR;
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}
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status |= ie_blob_get_dims(input_blob, &dims);
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status |= ie_blob_get_precision(input_blob, &precision);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to get input blob dims/precision\n");
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return DNN_ERROR;
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}
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status = ie_blob_get_buffer(input_blob, &blob_buffer);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to get input blob buffer\n");
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return DNN_ERROR;
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}
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input.height = dims.dims[2];
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input.width = dims.dims[3];
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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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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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ff_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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return DNN_SUCCESS;
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}
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static void infer_completion_callback(void *args)
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{
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dimensions_t dims;
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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->tasks[0];
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SafeQueue *requestq = task->ov_model->request_queue;
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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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OVContext *ctx = &task->ov_model->ctx;
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status = ie_infer_request_get_blob(request->infer_request, task->output_name, &output_blob);
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if (status != OK) {
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//incorrect output name
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char *model_output_name = NULL;
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char *all_output_names = NULL;
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size_t model_output_count = 0;
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av_log(ctx, AV_LOG_ERROR, "Failed to get model output data\n");
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status = ie_network_get_outputs_number(task->ov_model->network, &model_output_count);
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for (size_t i = 0; i < model_output_count; i++) {
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status = ie_network_get_output_name(task->ov_model->network, i, &model_output_name);
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APPEND_STRING(all_output_names, model_output_name)
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}
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av_log(ctx, AV_LOG_ERROR,
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"output \"%s\" may not correct, all output(s) are: \"%s\"\n",
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task->output_name, all_output_names);
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return;
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}
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status = ie_blob_get_buffer(output_blob, &blob_buffer);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to access output memory\n");
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return;
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}
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status |= ie_blob_get_dims(output_blob, &dims);
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status |= ie_blob_get_precision(output_blob, &precision);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to get dims or precision of output\n");
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return;
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}
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output.channels = dims.dims[1];
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output.height = dims.dims[2];
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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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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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ff_proc_from_dnn_to_frame(task->out_frame, &output, ctx);
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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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}
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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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if (ff_safe_queue_push_back(requestq, 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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}
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static DNNReturnType init_model_ov(OVModel *ov_model, const char *input_name, const char *output_name)
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{
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OVContext *ctx = &ov_model->ctx;
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IEStatusCode status;
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ie_available_devices_t a_dev;
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ie_config_t config = {NULL, NULL, NULL};
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char *all_dev_names = NULL;
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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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// The order of dims in the openvino is fixed and it is always NCHW for 4-D data.
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// while we pass NHWC data from FFmpeg to openvino
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status = ie_network_set_input_layout(ov_model->network, input_name, NHWC);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to set layout as NHWC for input %s\n", input_name);
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goto err;
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}
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status = ie_network_set_output_layout(ov_model->network, output_name, NHWC);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to set layout as NHWC for output %s\n", output_name);
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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 load OpenVINO model network\n");
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status = ie_core_get_available_devices(ov_model->core, &a_dev);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to get available devices\n");
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goto err;
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}
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for (int i = 0; i < a_dev.num_devices; i++) {
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APPEND_STRING(all_dev_names, a_dev.devices[i])
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}
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av_log(ctx, AV_LOG_ERROR,"device %s may not be supported, all available devices are: \"%s\"\n",
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ctx->options.device_type, all_dev_names);
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goto err;
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}
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// create infer_request for sync execution
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status = ie_exec_network_create_infer_request(ov_model->exe_network, &ov_model->infer_request);
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if (status != OK)
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goto err;
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// create infer_requests for async execution
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if (ctx->options.nireq <= 0) {
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// the default value is a rough estimation
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ctx->options.nireq = av_cpu_count() / 2 + 1;
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}
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ov_model->request_queue = ff_safe_queue_create();
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if (!ov_model->request_queue) {
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goto err;
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}
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for (int i = 0; i < ctx->options.nireq; i++) {
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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, &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->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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av_freep(&item);
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goto err;
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}
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}
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ov_model->task_queue = ff_queue_create();
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if (!ov_model->task_queue) {
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goto err;
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}
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return DNN_SUCCESS;
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err:
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ff_dnn_free_model_ov(&ov_model->model);
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return DNN_ERROR;
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}
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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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if (task->async) {
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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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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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} 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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infer_completion_callback(request);
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return task->done ? DNN_SUCCESS : DNN_ERROR;
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}
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}
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static DNNReturnType get_input_ov(void *model, DNNData *input, const char *input_name)
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{
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OVModel *ov_model = model;
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OVContext *ctx = &ov_model->ctx;
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char *model_input_name = NULL;
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char *all_input_names = NULL;
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IEStatusCode status;
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size_t model_input_count = 0;
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dimensions_t dims;
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precision_e precision;
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int input_resizable = ctx->options.input_resizable;
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status = ie_network_get_inputs_number(ov_model->network, &model_input_count);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to get input count\n");
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return DNN_ERROR;
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}
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for (size_t i = 0; i < model_input_count; i++) {
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status = ie_network_get_input_name(ov_model->network, i, &model_input_name);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to get No.%d input's name\n", (int)i);
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return DNN_ERROR;
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}
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if (strcmp(model_input_name, input_name) == 0) {
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ie_network_name_free(&model_input_name);
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status |= ie_network_get_input_dims(ov_model->network, input_name, &dims);
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status |= ie_network_get_input_precision(ov_model->network, input_name, &precision);
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if (status != OK) {
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av_log(ctx, AV_LOG_ERROR, "Failed to get No.%d input's dims or precision\n", (int)i);
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return DNN_ERROR;
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}
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input->channels = dims.dims[1];
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input->height = input_resizable ? -1 : dims.dims[2];
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input->width = input_resizable ? -1 : dims.dims[3];
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input->dt = precision_to_datatype(precision);
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return DNN_SUCCESS;
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} else {
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//incorrect input name
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APPEND_STRING(all_input_names, model_input_name)
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}
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ie_network_name_free(&model_input_name);
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}
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av_log(ctx, AV_LOG_ERROR, "Could not find \"%s\" in model, all input(s) are: \"%s\"\n", input_name, all_input_names);
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return DNN_ERROR;
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}
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static DNNReturnType get_output_ov(void *model, const char *input_name, int input_width, int input_height,
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const char *output_name, int *output_width, int *output_height)
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{
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DNNReturnType ret;
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OVModel *ov_model = model;
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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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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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IEStatusCode status;
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input_shapes_t input_shapes;
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if (!in_frame) {
|
|
av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for input frame\n");
|
|
return DNN_ERROR;
|
|
}
|
|
out_frame = av_frame_alloc();
|
|
if (!out_frame) {
|
|
av_log(ctx, AV_LOG_ERROR, "Failed to allocate memory for output frame\n");
|
|
av_frame_free(&in_frame);
|
|
return DNN_ERROR;
|
|
}
|
|
in_frame->width = input_width;
|
|
in_frame->height = input_height;
|
|
|
|
if (ctx->options.input_resizable) {
|
|
status = ie_network_get_input_shapes(ov_model->network, &input_shapes);
|
|
input_shapes.shapes->shape.dims[2] = input_height;
|
|
input_shapes.shapes->shape.dims[3] = input_width;
|
|
status |= ie_network_reshape(ov_model->network, input_shapes);
|
|
ie_network_input_shapes_free(&input_shapes);
|
|
if (status != OK) {
|
|
av_log(ctx, AV_LOG_ERROR, "Failed to reshape input size for %s\n", input_name);
|
|
return DNN_ERROR;
|
|
}
|
|
}
|
|
|
|
if (!ov_model->exe_network) {
|
|
if (init_model_ov(ov_model, input_name, output_name) != DNN_SUCCESS) {
|
|
av_log(ctx, AV_LOG_ERROR, "Failed init OpenVINO exectuable network or inference request\n");
|
|
return DNN_ERROR;
|
|
}
|
|
}
|
|
|
|
task.done = 0;
|
|
task.do_ioproc = 0;
|
|
task.async = 0;
|
|
task.input_name = input_name;
|
|
task.in_frame = in_frame;
|
|
task.output_name = output_name;
|
|
task.out_frame = out_frame;
|
|
task.ov_model = ov_model;
|
|
|
|
request.infer_request = ov_model->infer_request;
|
|
request.task_count = 1;
|
|
request.tasks = &ptask;
|
|
|
|
ret = execute_model_ov(&request);
|
|
*output_width = out_frame->width;
|
|
*output_height = out_frame->height;
|
|
|
|
av_frame_free(&out_frame);
|
|
av_frame_free(&in_frame);
|
|
return ret;
|
|
}
|
|
|
|
DNNModel *ff_dnn_load_model_ov(const char *model_filename, DNNFunctionType func_type, const char *options, AVFilterContext *filter_ctx)
|
|
{
|
|
DNNModel *model = NULL;
|
|
OVModel *ov_model = NULL;
|
|
OVContext *ctx = NULL;
|
|
IEStatusCode status;
|
|
|
|
model = av_mallocz(sizeof(DNNModel));
|
|
if (!model){
|
|
return NULL;
|
|
}
|
|
|
|
ov_model = av_mallocz(sizeof(OVModel));
|
|
if (!ov_model) {
|
|
av_freep(&model);
|
|
return NULL;
|
|
}
|
|
model->model = ov_model;
|
|
ov_model->model = model;
|
|
ov_model->ctx.class = &dnn_openvino_class;
|
|
ctx = &ov_model->ctx;
|
|
|
|
//parse options
|
|
av_opt_set_defaults(ctx);
|
|
if (av_opt_set_from_string(ctx, options, NULL, "=", "&") < 0) {
|
|
av_log(ctx, AV_LOG_ERROR, "Failed to parse options \"%s\"\n", options);
|
|
goto err;
|
|
}
|
|
|
|
status = ie_core_create("", &ov_model->core);
|
|
if (status != OK)
|
|
goto err;
|
|
|
|
status = ie_core_read_network(ov_model->core, model_filename, NULL, &ov_model->network);
|
|
if (status != OK) {
|
|
ie_version_t ver;
|
|
ver = ie_c_api_version();
|
|
av_log(ctx, AV_LOG_ERROR, "Failed to read the network from model file %s,\n"
|
|
"Please check if the model version matches the runtime OpenVINO %s\n",
|
|
model_filename, ver.api_version);
|
|
ie_version_free(&ver);
|
|
goto err;
|
|
}
|
|
|
|
model->get_input = &get_input_ov;
|
|
model->get_output = &get_output_ov;
|
|
model->options = options;
|
|
model->filter_ctx = filter_ctx;
|
|
model->func_type = func_type;
|
|
|
|
return model;
|
|
|
|
err:
|
|
ff_dnn_free_model_ov(&model);
|
|
return NULL;
|
|
}
|
|
|
|
DNNReturnType ff_dnn_execute_model_ov(const DNNModel *model, const char *input_name, AVFrame *in_frame,
|
|
const char **output_names, uint32_t nb_output, AVFrame *out_frame)
|
|
{
|
|
OVModel *ov_model = model->model;
|
|
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");
|
|
return DNN_ERROR;
|
|
}
|
|
|
|
if (!out_frame) {
|
|
av_log(ctx, AV_LOG_ERROR, "out frame is NULL when execute model.\n");
|
|
return DNN_ERROR;
|
|
}
|
|
|
|
if (nb_output != 1) {
|
|
// currently, the filter does not need multiple outputs,
|
|
// so we just pending the support until we really need it.
|
|
avpriv_report_missing_feature(ctx, "multiple outputs");
|
|
return DNN_ERROR;
|
|
}
|
|
|
|
if (ctx->options.batch_size > 1) {
|
|
avpriv_report_missing_feature(ctx, "batch mode for sync execution");
|
|
return DNN_ERROR;
|
|
}
|
|
|
|
if (!ov_model->exe_network) {
|
|
if (init_model_ov(ov_model, input_name, output_names[0]) != DNN_SUCCESS) {
|
|
av_log(ctx, AV_LOG_ERROR, "Failed init OpenVINO exectuable network or inference request\n");
|
|
return DNN_ERROR;
|
|
}
|
|
}
|
|
|
|
task.done = 0;
|
|
task.do_ioproc = 1;
|
|
task.async = 0;
|
|
task.input_name = input_name;
|
|
task.in_frame = in_frame;
|
|
task.output_name = output_names[0];
|
|
task.out_frame = out_frame;
|
|
task.ov_model = ov_model;
|
|
|
|
request.infer_request = ov_model->infer_request;
|
|
request.task_count = 1;
|
|
request.tasks = &ptask;
|
|
|
|
return execute_model_ov(&request);
|
|
}
|
|
|
|
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)
|
|
{
|
|
OVModel *ov_model = model->model;
|
|
OVContext *ctx = &ov_model->ctx;
|
|
RequestItem *request;
|
|
TaskItem *task;
|
|
|
|
if (!in_frame) {
|
|
av_log(ctx, AV_LOG_ERROR, "in frame is NULL when async execute model.\n");
|
|
return DNN_ERROR;
|
|
}
|
|
|
|
if (!out_frame) {
|
|
av_log(ctx, AV_LOG_ERROR, "out frame is NULL when async execute model.\n");
|
|
return DNN_ERROR;
|
|
}
|
|
|
|
task = av_malloc(sizeof(*task));
|
|
if (!task) {
|
|
av_log(ctx, AV_LOG_ERROR, "unable to alloc memory for task item.\n");
|
|
return DNN_ERROR;
|
|
}
|
|
|
|
if (!ov_model->exe_network) {
|
|
if (init_model_ov(ov_model, input_name, output_names[0]) != DNN_SUCCESS) {
|
|
av_log(ctx, AV_LOG_ERROR, "Failed init OpenVINO exectuable network or inference request\n");
|
|
return DNN_ERROR;
|
|
}
|
|
}
|
|
|
|
task->done = 0;
|
|
task->do_ioproc = 1;
|
|
task->async = 1;
|
|
task->input_name = input_name;
|
|
task->in_frame = in_frame;
|
|
task->output_name = output_names[0];
|
|
task->out_frame = out_frame;
|
|
task->ov_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");
|
|
return DNN_ERROR;
|
|
}
|
|
|
|
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;
|
|
}
|
|
|
|
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)
|
|
{
|
|
OVModel *ov_model = model->model;
|
|
TaskItem *task = ff_queue_peek_front(ov_model->task_queue);
|
|
|
|
if (!task) {
|
|
return DAST_EMPTY_QUEUE;
|
|
}
|
|
|
|
if (!task->done) {
|
|
return DAST_NOT_READY;
|
|
}
|
|
|
|
*in = task->in_frame;
|
|
*out = task->out_frame;
|
|
ff_queue_pop_front(ov_model->task_queue);
|
|
av_freep(&task);
|
|
|
|
return DAST_SUCCESS;
|
|
}
|
|
|
|
DNNReturnType ff_dnn_flush_ov(const DNNModel *model)
|
|
{
|
|
OVModel *ov_model = 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){
|
|
OVModel *ov_model = (*model)->model;
|
|
while (ff_safe_queue_size(ov_model->request_queue) != 0) {
|
|
RequestItem *item = ff_safe_queue_pop_front(ov_model->request_queue);
|
|
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);
|
|
|
|
if (ov_model->infer_request)
|
|
ie_infer_request_free(&ov_model->infer_request);
|
|
if (ov_model->exe_network)
|
|
ie_exec_network_free(&ov_model->exe_network);
|
|
if (ov_model->network)
|
|
ie_network_free(&ov_model->network);
|
|
if (ov_model->core)
|
|
ie_core_free(&ov_model->core);
|
|
av_freep(&ov_model);
|
|
av_freep(model);
|
|
}
|
|
}
|