1
0
mirror of https://github.com/FFmpeg/FFmpeg.git synced 2024-11-26 19:01:44 +02:00
FFmpeg/libavfilter/vf_derain.c
Guo, Yejun 76fc6879e2 dnn: add function type for model
So the backend knows the usage of model is for frame processing,
detect, classify, etc. Each function type has different behavior
in backend when handling the input/output data of the model.

Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
2021-02-18 09:59:37 +08:00

141 lines
4.8 KiB
C

/*
* Copyright (c) 2019 Xuewei Meng
*
* 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
* Filter implementing image derain filter using deep convolutional networks.
* http://openaccess.thecvf.com/content_ECCV_2018/html/Xia_Li_Recurrent_Squeeze-and-Excitation_Context_ECCV_2018_paper.html
*/
#include "libavformat/avio.h"
#include "libavutil/opt.h"
#include "avfilter.h"
#include "dnn_filter_common.h"
#include "formats.h"
#include "internal.h"
typedef struct DRContext {
const AVClass *class;
DnnContext dnnctx;
int filter_type;
} DRContext;
#define OFFSET(x) offsetof(DRContext, x)
#define FLAGS AV_OPT_FLAG_FILTERING_PARAM | AV_OPT_FLAG_VIDEO_PARAM
static const AVOption derain_options[] = {
{ "filter_type", "filter type(derain/dehaze)", OFFSET(filter_type), AV_OPT_TYPE_INT, { .i64 = 0 }, 0, 1, FLAGS, "type" },
{ "derain", "derain filter flag", 0, AV_OPT_TYPE_CONST, { .i64 = 0 }, 0, 0, FLAGS, "type" },
{ "dehaze", "dehaze filter flag", 0, AV_OPT_TYPE_CONST, { .i64 = 1 }, 0, 0, FLAGS, "type" },
{ "dnn_backend", "DNN backend", OFFSET(dnnctx.backend_type), AV_OPT_TYPE_INT, { .i64 = 0 }, 0, 1, FLAGS, "backend" },
{ "native", "native backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = 0 }, 0, 0, FLAGS, "backend" },
#if (CONFIG_LIBTENSORFLOW == 1)
{ "tensorflow", "tensorflow backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = 1 }, 0, 0, FLAGS, "backend" },
#endif
{ "model", "path to model file", OFFSET(dnnctx.model_filename), AV_OPT_TYPE_STRING, { .str = NULL }, 0, 0, FLAGS },
{ "input", "input name of the model", OFFSET(dnnctx.model_inputname), AV_OPT_TYPE_STRING, { .str = "x" }, 0, 0, FLAGS },
{ "output", "output name of the model", OFFSET(dnnctx.model_outputname), AV_OPT_TYPE_STRING, { .str = "y" }, 0, 0, FLAGS },
{ NULL }
};
AVFILTER_DEFINE_CLASS(derain);
static int query_formats(AVFilterContext *ctx)
{
AVFilterFormats *formats;
const enum AVPixelFormat pixel_fmts[] = {
AV_PIX_FMT_RGB24,
AV_PIX_FMT_NONE
};
formats = ff_make_format_list(pixel_fmts);
return ff_set_common_formats(ctx, formats);
}
static int filter_frame(AVFilterLink *inlink, AVFrame *in)
{
AVFilterContext *ctx = inlink->dst;
AVFilterLink *outlink = ctx->outputs[0];
DRContext *dr_context = ctx->priv;
DNNReturnType dnn_result;
AVFrame *out;
out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
if (!out) {
av_log(ctx, AV_LOG_ERROR, "could not allocate memory for output frame\n");
av_frame_free(&in);
return AVERROR(ENOMEM);
}
av_frame_copy_props(out, in);
dnn_result = ff_dnn_execute_model(&dr_context->dnnctx, in, out);
if (dnn_result != DNN_SUCCESS){
av_log(ctx, AV_LOG_ERROR, "failed to execute model\n");
av_frame_free(&in);
return AVERROR(EIO);
}
av_frame_free(&in);
return ff_filter_frame(outlink, out);
}
static av_cold int init(AVFilterContext *ctx)
{
DRContext *dr_context = ctx->priv;
return ff_dnn_init(&dr_context->dnnctx, DFT_PROCESS_FRAME, ctx);
}
static av_cold void uninit(AVFilterContext *ctx)
{
DRContext *dr_context = ctx->priv;
ff_dnn_uninit(&dr_context->dnnctx);
}
static const AVFilterPad derain_inputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
.filter_frame = filter_frame,
},
{ NULL }
};
static const AVFilterPad derain_outputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
},
{ NULL }
};
AVFilter ff_vf_derain = {
.name = "derain",
.description = NULL_IF_CONFIG_SMALL("Apply derain filter to the input."),
.priv_size = sizeof(DRContext),
.init = init,
.uninit = uninit,
.query_formats = query_formats,
.inputs = derain_inputs,
.outputs = derain_outputs,
.priv_class = &derain_class,
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC,
};