[FFmpeg-devel] [PATCH] libavfilter: Add derain filter init version--GSoC Qualification Task.
xwmeng at pku.edu.cn
xwmeng at pku.edu.cn
Thu Apr 11 08:46:36 EEST 2019
> -----原始邮件-----
> 发件人: "Liu Steven" <lq at chinaffmpeg.org>
> 发送时间: 2019-04-09 16:00:25 (星期二)
> 收件人: "FFmpeg development discussions and patches" <ffmpeg-devel at ffmpeg.org>
> 抄送: "Liu Steven" <lq at chinaffmpeg.org>
> 主题: Re: [FFmpeg-devel] [PATCH] libavfilter: Add derain filter init version--GSoC Qualification Task.
>
>
>
> > 在 2019年4月9日，下午3:14，xwmeng at pku.edu.cn 写道：
> >
> > This patch is the qualification task of the derain filter project in GSoC.
> >
> It maybe better if you submit a model file and test example here.
The model file has been uploaded (https://github.com/XueweiMeng/derain_filter). And you can download the test/train dataset from http://www.icst.pku.edu.cn/struct/Projects/joint_rain_removal.html
xuewei
> > From 61463dfe14c0e0de4e233f68c8404d73d5bd9f8f Mon Sep 17 00:00:00 2001
> >
> > From: Xuewei Meng <xwmeng at pku.edu.cn>
> > Date: Tue, 9 Apr 2019 15:09:33 +0800
> > Subject: [PATCH] Add derain filter init version-GSoC Qualification Task
> >
> >
> > Signed-off-by: Xuewei Meng <xwmeng at pku.edu.cn>
> > ---
> > doc/filters.texi | 41 ++++++++
> > libavfilter/Makefile | 1 +
> > libavfilter/allfilters.c | 1 +
> > libavfilter/vf_derain.c | 204 +++++++++++++++++++++++++++++++++++++++
> > 4 files changed, 247 insertions(+)
> > create mode 100644 libavfilter/vf_derain.c
> >
> >
> > diff --git a/doc/filters.texi b/doc/filters.texi
> > index 867607d870..0117c418b4 100644
> > --- a/doc/filters.texi
> > +++ b/doc/filters.texi
> > @@ -8036,6 +8036,47 @@ delogo=x=0:y=0:w=100:h=77:band=10
> >
> > @end itemize
> >
> > + at section derain
> > +
> > +Remove the rain in the input image/video by applying the derain methods based on
> > +convolutional neural networks. Supported models:
> > +
> > + at itemize
> > + at item
> > +Efficient Sub-Pixel Convolutional Neural Network model (ESPCN).
> > +See @url{https://arxiv.org/abs/1609.05158}.
> > + at end itemize
> > +
> > +Training scripts as well as scripts for model generation are provided in
> > +the repository at @url{https://github.com/XueweiMeng/derain_filter.git}.
> > +
> > +The filter accepts the following options:
> > +
> > + at table @option
> > + at item dnn_backend
> > +Specify which DNN backend to use for model loading and execution. This option accepts
> > +the following values:
> > +
> > + at table @samp
> > + at item native
> > +Native implementation of DNN loading and execution.
> > +
> > + at item tensorflow
> > +TensorFlow backend. To enable this backend you
> > +need to install the TensorFlow for C library (see
> > + at url{https://www.tensorflow.org/install/install_c}) and configure FFmpeg with
> > + at code{--enable-libtensorflow}
> > + at end table
> > +
> > +Default value is @samp{native}.
> > +
> > + at item model
> > +Set path to model file specifying network architecture and its parameters.
> > +Note that different backends use different file formats. TensorFlow backend
> > +can load files for both formats, while native backend can load files for only
> > +its format.
> > + at end table
> > +
> > @section deshake
> >
> > Attempt to fix small changes in horizontal and/or vertical shift. This
> > diff --git a/libavfilter/Makefile b/libavfilter/Makefile
> > index fef6ec5c55..7809bac565 100644
> > --- a/libavfilter/Makefile
> > +++ b/libavfilter/Makefile
> > @@ -194,6 +194,7 @@ OBJS-$(CONFIG_DATASCOPE_FILTER) += vf_datascope.o
> > OBJS-$(CONFIG_DCTDNOIZ_FILTER) += vf_dctdnoiz.o
> > OBJS-$(CONFIG_DEBAND_FILTER) += vf_deband.o
> > OBJS-$(CONFIG_DEBLOCK_FILTER) += vf_deblock.o
> > +OBJS-$(CONFIG_DERAIN_FILTER) += vf_derain.o
> > OBJS-$(CONFIG_DECIMATE_FILTER) += vf_decimate.o
> > OBJS-$(CONFIG_DECONVOLVE_FILTER) += vf_convolve.o framesync.o
> > OBJS-$(CONFIG_DEDOT_FILTER) += vf_dedot.o
> > diff --git a/libavfilter/allfilters.c b/libavfilter/allfilters.c
> > index c51ae0f3c7..ee2a5b63e6 100644
> > --- a/libavfilter/allfilters.c
> > +++ b/libavfilter/allfilters.c
> > @@ -182,6 +182,7 @@ extern AVFilter ff_vf_datascope;
> > extern AVFilter ff_vf_dctdnoiz;
> > extern AVFilter ff_vf_deband;
> > extern AVFilter ff_vf_deblock;
> > +extern AVFilter ff_vf_derain;
> > extern AVFilter ff_vf_decimate;
> > extern AVFilter ff_vf_deconvolve;
> > extern AVFilter ff_vf_dedot;
> > diff --git a/libavfilter/vf_derain.c b/libavfilter/vf_derain.c
> > new file mode 100644
> > index 0000000000..f72ae1cd3a
> > --- /dev/null
> > +++ b/libavfilter/vf_derain.c
> > @@ -0,0 +1,204 @@
> > +/*
> > + * 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.
> > + * https://arxiv.org/abs/1609.05158
> > + * http://openaccess.thecvf.com/content_ECCV_2018/html/Xia_Li_Recurrent_Squeeze-and-Excitation_Context_ECCV_2018_paper.html
> > + */
> > +
> > +#include "libavutil/opt.h"
> > +#include "libavformat/avio.h"
> > +#include "libswscale/swscale.h"
> > +#include "avfilter.h"
> > +#include "formats.h"
> > +#include "internal.h"
> > +#include "dnn_interface.h"
> > +
> > +typedef struct DRContext {
> > + const AVClass *class;
> > +
> > + char *model_filename;
> > + DNNBackendType backend_type;
> > + DNNModule *dnn_module;
> > + DNNModel *model;
> > + DNNData input;
> > + DNNData output;
> > +} DRContext;
> > +
> > +#define OFFSET(x) offsetof(DRContext, x)
> > +#define FLAGS AV_OPT_FLAG_FILTERING_PARAM | AV_OPT_FLAG_VIDEO_PARAM
> > +static const AVOption derain_options[] = {
> > + { "dnn_backend", "DNN backend", OFFSET(backend_type), AV_OPT_TYPE_FLAGS, { .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(model_filename), AV_OPT_TYPE_STRING, { .str = NULL }, 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);
> > + if (!formats) {
> > + av_log(ctx, AV_LOG_ERROR, "could not create formats list\n");
> > + return AVERROR(ENOMEM);
> > + }
> > +
> > + return ff_set_common_formats(ctx, formats);
> > +}
> > +
> > +static int config_inputs(AVFilterLink *inlink)
> > +{
> > + AVFilterContext *ctx = inlink->dst;
> > + DRContext *dr_context = ctx->priv;
> > + AVFilterLink *outlink = ctx->outputs[0];
> > + DNNReturnType result;
> > +
> > + dr_context->input.width = inlink->w;
> > + dr_context->input.height = inlink->h;
> > + dr_context->input.channels = 3;
> > +
> > + result = (dr_context->model->set_input_output)(dr_context->model->model, &dr_context->input, &dr_context->output);
> > + if (result != DNN_SUCCESS) {
> > + av_log(ctx, AV_LOG_ERROR, "could not set input and output for the model\n");
> > + return AVERROR(EIO);
> > + }
> > +
> > + outlink->h = dr_context->output.height;
> > + outlink->w = dr_context->output.width;
> > +
> > + return 0;
> > +}
> > +
> > +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 = 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);
> > + out->height = dr_context->output.height;
> > + out->width = dr_context->output.width;
> > +
> > + for (int i = 0; i < out->height * out->width * 3; i++) {
> > + dr_context->input.data[i] = in->data[0][i] / 255.0;
> > + }
> > +
> > + av_frame_free(&in);
> > + dnn_result = (dr_context->dnn_module->execute_model)(dr_context->model);
> > + if (dnn_result != DNN_SUCCESS){
> > + av_log(ctx, AV_LOG_ERROR, "failed to execute model\n");
> > + return AVERROR(EIO);
> > + }
> > +
> > + for (int i = 0; i < out->height * out->width * 3; i++) {
> > + out->data[0][i] = (int)(dr_context->output.data[i] * 255);
> > + }
> > +
> > + return ff_filter_frame(outlink, out);
> > +}
> > +
> > +static av_cold int init(AVFilterContext *ctx)
> > +{
> > + DRContext *dr_context = ctx->priv;
> > +
> > + dr_context->dnn_module = ff_get_dnn_module(dr_context->backend_type);
> > + if (!dr_context->dnn_module) {
> > + av_log(ctx, AV_LOG_ERROR, "could not create DNN module for requested backend\n");
> > + return AVERROR(ENOMEM);
> > + }
> > + if (!dr_context->model_filename) {
> > + av_log(ctx, AV_LOG_ERROR, "model file for network is not specified\n");
> > + return AVERROR(EINVAL);
> > + }
> > + if (!dr_context->dnn_module->load_model) {
> > + av_log(ctx, AV_LOG_ERROR, "load_model for network is not specified\n");
> > + return AVERROR(EINVAL);
> > + }
> > +
> > + dr_context->model = (dr_context->dnn_module->load_model)(dr_context->model_filename);
> > + if (!dr_context->model) {
> > + av_log(ctx, AV_LOG_ERROR, "could not load DNN model\n");
> > + return AVERROR(EINVAL);
> > + }
> > +
> > + return 0;
> > +}
> > +
> > +static av_cold void uninit(AVFilterContext *ctx)
> > +{
> > + DRContext *dr_context = ctx->priv;
> > +
> > + if (dr_context->dnn_module) {
> > + (dr_context->dnn_module->free_model)(&dr_context->model);
> > + av_freep(&dr_context->dnn_module);
> > + }
> > +}
> > +
> > +static const AVFilterPad derain_inputs[] = {
> > + {
> > + .name = "default",
> > + .type = AVMEDIA_TYPE_VIDEO,
> > + .config_props = config_inputs,
> > + .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 | AVFILTER_FLAG_SLICE_THREADS,
> > +};
> > +
> > --
> > 2.17.1
> >
> > _______________________________________________
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