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https://github.com/FFmpeg/FFmpeg.git
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64ea15f050
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>
95 lines
4.1 KiB
C
95 lines
4.1 KiB
C
/*
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* Copyright (c) 2018 Sergey Lavrushkin
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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 inference engine interface.
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*/
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#ifndef AVFILTER_DNN_INTERFACE_H
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#define AVFILTER_DNN_INTERFACE_H
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#include <stdint.h>
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#include "libavutil/frame.h"
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#include "avfilter.h"
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typedef enum {DNN_SUCCESS, DNN_ERROR} DNNReturnType;
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typedef enum {DNN_NATIVE, DNN_TF, DNN_OV} DNNBackendType;
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typedef enum {DNN_FLOAT = 1, DNN_UINT8 = 4} DNNDataType;
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typedef enum {
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DAST_FAIL, // something wrong
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DAST_EMPTY_QUEUE, // no more inference result to get
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DAST_NOT_READY, // all queued inferences are not finished
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DAST_SUCCESS // got a result frame successfully
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} DNNAsyncStatusType;
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typedef struct DNNData{
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void *data;
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DNNDataType dt;
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int width, height, channels;
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} DNNData;
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typedef struct DNNModel{
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// Stores model that can be different for different backends.
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void *model;
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// Stores options when the model is executed by the backend
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const char *options;
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// Stores FilterContext used for the interaction between AVFrame and DNNData
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AVFilterContext *filter_ctx;
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// Gets model input information
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// Just reuse struct DNNData here, actually the DNNData.data field is not needed.
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DNNReturnType (*get_input)(void *model, DNNData *input, const char *input_name);
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// Gets model output width/height with given input w/h
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DNNReturnType (*get_output)(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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// set the pre process to transfer data from AVFrame to DNNData
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// the default implementation within DNN is used if it is not provided by the filter
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int (*pre_proc)(AVFrame *frame_in, DNNData *model_input, AVFilterContext *filter_ctx);
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// set the post process to transfer data from DNNData to AVFrame
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// the default implementation within DNN is used if it is not provided by the filter
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int (*post_proc)(AVFrame *frame_out, DNNData *model_output, AVFilterContext *filter_ctx);
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} DNNModel;
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// Stores pointers to functions for loading, executing, freeing DNN models for one of the backends.
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typedef struct DNNModule{
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// Loads model and parameters from given file. Returns NULL if it is not possible.
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DNNModel *(*load_model)(const char *model_filename, const char *options, AVFilterContext *filter_ctx);
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// Executes model with specified input and output. Returns DNN_ERROR otherwise.
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DNNReturnType (*execute_model)(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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// Executes model with specified input and output asynchronously. Returns DNN_ERROR otherwise.
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DNNReturnType (*execute_model_async)(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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// 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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// Initializes DNNModule depending on chosen backend.
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DNNModule *ff_get_dnn_module(DNNBackendType backend_type);
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#endif
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