FFmpeg/libavfilter/dnn_filter_common.h

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/*
* This file is part of FFmpeg.
*
* FFmpeg is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* FFmpeg is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with FFmpeg; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*/
/**
* @file
* common functions for the dnn based filters
*/
#ifndef AVFILTER_DNN_FILTER_COMMON_H
#define AVFILTER_DNN_FILTER_COMMON_H
#include "dnn_interface.h"
#define DNN_FILTER_CHILD_CLASS_ITERATE(name, backend_mask) \
static const AVClass *name##_child_class_iterate(void **iter) \
{ \
return ff_dnn_child_class_iterate_with_mask(iter, (backend_mask)); \
}
avfilter/dnn: Refactor DNN parameter configuration system This patch trying to resolve mulitiple issues related to parameter configuration: Firstly, each DNN filters duplicate DNN_COMMON_OPTIONS, which should be the common options of backend. Secondly, backend options are hidden behind the scene. It's a AV_OPT_TYPE_STRING backend_configs for user, and parsed by each backend. We don't know each backend support what kind of options from the help message. Third, DNN backends duplicate DNN_BACKEND_COMMON_OPTIONS. Last but not the least, pass backend options via AV_OPT_TYPE_STRING makes it hard to pass AV_OPT_TYPE_BINARY to backend, if not impossible. This patch puts backend common options and each backend options inside DnnContext to reduce code duplication, make options user friendly, and easy to extend for future usecase. For example, ./ffmpeg -h filter=dnn_processing dnn_processing AVOptions: dnn_backend <int> ..FV....... DNN backend (from INT_MIN to INT_MAX) (default tensorflow) tensorflow 1 ..FV....... tensorflow backend flag openvino 2 ..FV....... openvino backend flag torch 3 ..FV....... torch backend flag dnn_base AVOptions: model <string> ..F........ path to model file input <string> ..F........ input name of the model output <string> ..F........ output name of the model backend_configs <string> ..F.......P backend configs (deprecated) options <string> ..F.......P backend configs (deprecated) nireq <int> ..F........ number of request (from 0 to INT_MAX) (default 0) async <boolean> ..F........ use DNN async inference (default true) device <string> ..F........ device to run model dnn_tensorflow AVOptions: sess_config <string> ..F........ config for SessionOptions dnn_openvino AVOptions: batch_size <int> ..F........ batch size per request (from 1 to 1000) (default 1) input_resizable <boolean> ..F........ can input be resizable or not (default false) layout <int> ..F........ input layout of model (from 0 to 2) (default none) none 0 ..F........ none nchw 1 ..F........ nchw nhwc 2 ..F........ nhwc scale <float> ..F........ Add scale preprocess operation. Divide each element of input by specified value. (from INT_MIN to INT_MAX) (default 0) mean <float> ..F........ Add mean preprocess operation. Subtract specified value from each element of input. (from INT_MIN to INT_MAX) (default 0) dnn_th AVOptions: optimize <int> ..F........ turn on graph executor optimization (from 0 to 1) (default 0) Signed-off-by: Zhao Zhili <zhilizhao@tencent.com> Reviewed-by: Wenbin Chen <wenbin.chen@intel.com> Reviewed-by: Guo Yejun <yejun.guo@intel.com>
2024-05-07 16:08:08 +00:00
#define AVFILTER_DNN_DEFINE_CLASS_EXT(name, desc, options) \
static const AVClass name##_class = { \
.class_name = desc, \
.item_name = av_default_item_name, \
.option = options, \
.version = LIBAVUTIL_VERSION_INT, \
.category = AV_CLASS_CATEGORY_FILTER, \
.child_next = ff_dnn_filter_child_next, \
.child_class_iterate = name##_child_class_iterate, \
avfilter/dnn: Refactor DNN parameter configuration system This patch trying to resolve mulitiple issues related to parameter configuration: Firstly, each DNN filters duplicate DNN_COMMON_OPTIONS, which should be the common options of backend. Secondly, backend options are hidden behind the scene. It's a AV_OPT_TYPE_STRING backend_configs for user, and parsed by each backend. We don't know each backend support what kind of options from the help message. Third, DNN backends duplicate DNN_BACKEND_COMMON_OPTIONS. Last but not the least, pass backend options via AV_OPT_TYPE_STRING makes it hard to pass AV_OPT_TYPE_BINARY to backend, if not impossible. This patch puts backend common options and each backend options inside DnnContext to reduce code duplication, make options user friendly, and easy to extend for future usecase. For example, ./ffmpeg -h filter=dnn_processing dnn_processing AVOptions: dnn_backend <int> ..FV....... DNN backend (from INT_MIN to INT_MAX) (default tensorflow) tensorflow 1 ..FV....... tensorflow backend flag openvino 2 ..FV....... openvino backend flag torch 3 ..FV....... torch backend flag dnn_base AVOptions: model <string> ..F........ path to model file input <string> ..F........ input name of the model output <string> ..F........ output name of the model backend_configs <string> ..F.......P backend configs (deprecated) options <string> ..F.......P backend configs (deprecated) nireq <int> ..F........ number of request (from 0 to INT_MAX) (default 0) async <boolean> ..F........ use DNN async inference (default true) device <string> ..F........ device to run model dnn_tensorflow AVOptions: sess_config <string> ..F........ config for SessionOptions dnn_openvino AVOptions: batch_size <int> ..F........ batch size per request (from 1 to 1000) (default 1) input_resizable <boolean> ..F........ can input be resizable or not (default false) layout <int> ..F........ input layout of model (from 0 to 2) (default none) none 0 ..F........ none nchw 1 ..F........ nchw nhwc 2 ..F........ nhwc scale <float> ..F........ Add scale preprocess operation. Divide each element of input by specified value. (from INT_MIN to INT_MAX) (default 0) mean <float> ..F........ Add mean preprocess operation. Subtract specified value from each element of input. (from INT_MIN to INT_MAX) (default 0) dnn_th AVOptions: optimize <int> ..F........ turn on graph executor optimization (from 0 to 1) (default 0) Signed-off-by: Zhao Zhili <zhilizhao@tencent.com> Reviewed-by: Wenbin Chen <wenbin.chen@intel.com> Reviewed-by: Guo Yejun <yejun.guo@intel.com>
2024-05-07 16:08:08 +00:00
}
#define AVFILTER_DNN_DEFINE_CLASS(fname, backend_mask) \
DNN_FILTER_CHILD_CLASS_ITERATE(fname, backend_mask) \
avfilter/dnn: Refactor DNN parameter configuration system This patch trying to resolve mulitiple issues related to parameter configuration: Firstly, each DNN filters duplicate DNN_COMMON_OPTIONS, which should be the common options of backend. Secondly, backend options are hidden behind the scene. It's a AV_OPT_TYPE_STRING backend_configs for user, and parsed by each backend. We don't know each backend support what kind of options from the help message. Third, DNN backends duplicate DNN_BACKEND_COMMON_OPTIONS. Last but not the least, pass backend options via AV_OPT_TYPE_STRING makes it hard to pass AV_OPT_TYPE_BINARY to backend, if not impossible. This patch puts backend common options and each backend options inside DnnContext to reduce code duplication, make options user friendly, and easy to extend for future usecase. For example, ./ffmpeg -h filter=dnn_processing dnn_processing AVOptions: dnn_backend <int> ..FV....... DNN backend (from INT_MIN to INT_MAX) (default tensorflow) tensorflow 1 ..FV....... tensorflow backend flag openvino 2 ..FV....... openvino backend flag torch 3 ..FV....... torch backend flag dnn_base AVOptions: model <string> ..F........ path to model file input <string> ..F........ input name of the model output <string> ..F........ output name of the model backend_configs <string> ..F.......P backend configs (deprecated) options <string> ..F.......P backend configs (deprecated) nireq <int> ..F........ number of request (from 0 to INT_MAX) (default 0) async <boolean> ..F........ use DNN async inference (default true) device <string> ..F........ device to run model dnn_tensorflow AVOptions: sess_config <string> ..F........ config for SessionOptions dnn_openvino AVOptions: batch_size <int> ..F........ batch size per request (from 1 to 1000) (default 1) input_resizable <boolean> ..F........ can input be resizable or not (default false) layout <int> ..F........ input layout of model (from 0 to 2) (default none) none 0 ..F........ none nchw 1 ..F........ nchw nhwc 2 ..F........ nhwc scale <float> ..F........ Add scale preprocess operation. Divide each element of input by specified value. (from INT_MIN to INT_MAX) (default 0) mean <float> ..F........ Add mean preprocess operation. Subtract specified value from each element of input. (from INT_MIN to INT_MAX) (default 0) dnn_th AVOptions: optimize <int> ..F........ turn on graph executor optimization (from 0 to 1) (default 0) Signed-off-by: Zhao Zhili <zhilizhao@tencent.com> Reviewed-by: Wenbin Chen <wenbin.chen@intel.com> Reviewed-by: Guo Yejun <yejun.guo@intel.com>
2024-05-07 16:08:08 +00:00
AVFILTER_DNN_DEFINE_CLASS_EXT(fname, #fname, fname##_options)
void *ff_dnn_filter_child_next(void *obj, void *prev);
int ff_dnn_filter_init_child_class(AVFilterContext *filter);
int ff_dnn_init(DnnContext *ctx, DNNFunctionType func_type, AVFilterContext *filter_ctx);
int ff_dnn_set_frame_proc(DnnContext *ctx, FramePrePostProc pre_proc, FramePrePostProc post_proc);
int ff_dnn_set_detect_post_proc(DnnContext *ctx, DetectPostProc post_proc);
int ff_dnn_set_classify_post_proc(DnnContext *ctx, ClassifyPostProc post_proc);
int ff_dnn_get_input(DnnContext *ctx, DNNData *input);
int ff_dnn_get_output(DnnContext *ctx, int input_width, int input_height, int *output_width, int *output_height);
int ff_dnn_execute_model(DnnContext *ctx, AVFrame *in_frame, AVFrame *out_frame);
int ff_dnn_execute_model_classification(DnnContext *ctx, AVFrame *in_frame, AVFrame *out_frame, const char *target);
DNNAsyncStatusType ff_dnn_get_result(DnnContext *ctx, AVFrame **in_frame, AVFrame **out_frame);
int ff_dnn_flush(DnnContext *ctx);
void ff_dnn_uninit(DnnContext *ctx);
#endif