[FFmpeg-devel] [PATCH] libavfilter: Add derain filter init version--GSoC Qualification Task.

Guo, Yejun yejun.guo at intel.com
Tue Apr 9 10:29:16 EEST 2019



> -----Original Message-----
> From: ffmpeg-devel [mailto:ffmpeg-devel-bounces at ffmpeg.org] On Behalf
> Of xwmeng at pku.edu.cn
> Sent: Tuesday, April 09, 2019 3:15 PM
> To: ffmpeg-devel at ffmpeg.org
> Cc: lq at chinaffmpeg.org
> Subject: [FFmpeg-devel] [PATCH] libavfilter: Add derain filter init version--
> GSoC Qualification Task.
> 
> This patch is the qualification task of the derain filter project in GSoC.
> 
> 
> 
> 
> 
> 
> 
> 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

in alphabet order

>  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

I made some changes for the tensorflow C API interface to support more features, see the patch set of https://patchwork.ffmpeg.org/patch/12567/,

your code might be better to rebase it when these are pushed ...

> 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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