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/*
* Copyright (c) 2018 Sergey Lavrushkin
*
* 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 super-resolution using deep convolutional networks.
* https://arxiv.org/abs/1501.00092
* https://arxiv.org/abs/1609.05158
*/
#include "avfilter.h"
#include "formats.h"
#include "internal.h"
#include "libavutil/opt.h"
#include "libavformat/avio.h"
#include "libswscale/swscale.h"
#include "dnn_interface.h"
typedef struct SRContext {
const AVClass *class;
char *model_filename;
DNNBackendType backend_type;
DNNModule *dnn_module;
DNNModel *model;
DNNData input, output;
int scale_factor;
struct SwsContext *sws_contexts[3];
int sws_slice_h, sws_input_linesize, sws_output_linesize;
} SRContext;
#define OFFSET(x) offsetof(SRContext, x)
#define FLAGS AV_OPT_FLAG_FILTERING_PARAM | AV_OPT_FLAG_VIDEO_PARAM
static const AVOption sr_options[] = {
{ "dnn_backend", "DNN backend used for model execution", 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
{ "scale_factor", "scale factor for SRCNN model", OFFSET(scale_factor), AV_OPT_TYPE_INT, { .i64 = 2 }, 2, 4, FLAGS },
{ "model", "path to model file specifying network architecture and its parameters", OFFSET(model_filename), AV_OPT_TYPE_STRING, {.str=NULL}, 0, 0, FLAGS },
{ NULL }
};
AVFILTER_DEFINE_CLASS(sr);
static av_cold int init(AVFilterContext *context)
{
SRContext *sr_context = context->priv;
sr_context->dnn_module = ff_get_dnn_module(sr_context->backend_type);
if (!sr_context->dnn_module){
av_log(context, AV_LOG_ERROR, "could not create DNN module for requested backend\n");
return AVERROR(ENOMEM);
}
if (!sr_context->model_filename){
av_log(context, AV_LOG_ERROR, "model file for network was not specified\n");
return AVERROR(EIO);
}
else{
sr_context->model = (sr_context->dnn_module->load_model)(sr_context->model_filename);
}
if (!sr_context->model){
av_log(context, AV_LOG_ERROR, "could not load DNN model\n");
return AVERROR(EIO);
}
sr_context->sws_contexts[0] = NULL;
sr_context->sws_contexts[1] = NULL;
sr_context->sws_contexts[2] = NULL;
return 0;
}
static int query_formats(AVFilterContext *context)
{
const enum AVPixelFormat pixel_formats[] = {AV_PIX_FMT_YUV420P, AV_PIX_FMT_YUV422P, AV_PIX_FMT_YUV444P,
AV_PIX_FMT_YUV410P, AV_PIX_FMT_YUV411P, AV_PIX_FMT_GRAY8,
AV_PIX_FMT_NONE};
AVFilterFormats *formats_list;
formats_list = ff_make_format_list(pixel_formats);
if (!formats_list){
av_log(context, AV_LOG_ERROR, "could not create formats list\n");
return AVERROR(ENOMEM);
}
return ff_set_common_formats(context, formats_list);
}
static int config_props(AVFilterLink *inlink)
{
AVFilterContext *context = inlink->dst;
SRContext *sr_context = context->priv;
AVFilterLink *outlink = context->outputs[0];
DNNReturnType result;
int sws_src_h, sws_src_w, sws_dst_h, sws_dst_w;
sr_context->input.width = inlink->w * sr_context->scale_factor;
sr_context->input.height = inlink->h * sr_context->scale_factor;
sr_context->input.channels = 1;
result = (sr_context->model->set_input_output)(sr_context->model->model, &sr_context->input, &sr_context->output);
if (result != DNN_SUCCESS){
av_log(context, AV_LOG_ERROR, "could not set input and output for the model\n");
return AVERROR(EIO);
}
else{
if (sr_context->input.height != sr_context->output.height || sr_context->input.width != sr_context->output.width){
sr_context->input.width = inlink->w;
sr_context->input.height = inlink->h;
result = (sr_context->model->set_input_output)(sr_context->model->model, &sr_context->input, &sr_context->output);
if (result != DNN_SUCCESS){
av_log(context, AV_LOG_ERROR, "could not set input and output for the model\n");
return AVERROR(EIO);
}
sr_context->scale_factor = 0;
}
outlink->h = sr_context->output.height;
outlink->w = sr_context->output.width;
sr_context->sws_contexts[1] = sws_getContext(sr_context->input.width, sr_context->input.height, AV_PIX_FMT_GRAY8,
sr_context->input.width, sr_context->input.height, AV_PIX_FMT_GRAYF32,
0, NULL, NULL, NULL);
sr_context->sws_input_linesize = sr_context->input.width << 2;
sr_context->sws_contexts[2] = sws_getContext(sr_context->output.width, sr_context->output.height, AV_PIX_FMT_GRAYF32,
sr_context->output.width, sr_context->output.height, AV_PIX_FMT_GRAY8,
0, NULL, NULL, NULL);
sr_context->sws_output_linesize = sr_context->output.width << 2;
if (!sr_context->sws_contexts[1] || !sr_context->sws_contexts[2]){
av_log(context, AV_LOG_ERROR, "could not create SwsContext for conversions\n");
return AVERROR(ENOMEM);
}
if (sr_context->scale_factor){
sr_context->sws_contexts[0] = sws_getContext(inlink->w, inlink->h, inlink->format,
outlink->w, outlink->h, outlink->format,
SWS_BICUBIC, NULL, NULL, NULL);
if (!sr_context->sws_contexts[0]){
av_log(context, AV_LOG_ERROR, "could not create SwsContext for scaling\n");
return AVERROR(ENOMEM);
}
sr_context->sws_slice_h = inlink->h;
}
else{
if (inlink->format != AV_PIX_FMT_GRAY8){
sws_src_h = sr_context->input.height;
sws_src_w = sr_context->input.width;
sws_dst_h = sr_context->output.height;
sws_dst_w = sr_context->output.width;
switch (inlink->format){
case AV_PIX_FMT_YUV420P:
sws_src_h = AV_CEIL_RSHIFT(sws_src_h, 1);
sws_src_w = AV_CEIL_RSHIFT(sws_src_w, 1);
sws_dst_h = AV_CEIL_RSHIFT(sws_dst_h, 1);
sws_dst_w = AV_CEIL_RSHIFT(sws_dst_w, 1);
break;
case AV_PIX_FMT_YUV422P:
sws_src_w = AV_CEIL_RSHIFT(sws_src_w, 1);
sws_dst_w = AV_CEIL_RSHIFT(sws_dst_w, 1);
break;
case AV_PIX_FMT_YUV444P:
break;
case AV_PIX_FMT_YUV410P:
sws_src_h = AV_CEIL_RSHIFT(sws_src_h, 2);
sws_src_w = AV_CEIL_RSHIFT(sws_src_w, 2);
sws_dst_h = AV_CEIL_RSHIFT(sws_dst_h, 2);
sws_dst_w = AV_CEIL_RSHIFT(sws_dst_w, 2);
break;
case AV_PIX_FMT_YUV411P:
sws_src_w = AV_CEIL_RSHIFT(sws_src_w, 2);
sws_dst_w = AV_CEIL_RSHIFT(sws_dst_w, 2);
break;
default:
av_log(context, AV_LOG_ERROR, "could not create SwsContext for scaling for given input pixel format");
return AVERROR(EIO);
}
sr_context->sws_contexts[0] = sws_getContext(sws_src_w, sws_src_h, AV_PIX_FMT_GRAY8,
sws_dst_w, sws_dst_h, AV_PIX_FMT_GRAY8,
SWS_BICUBIC, NULL, NULL, NULL);
if (!sr_context->sws_contexts[0]){
av_log(context, AV_LOG_ERROR, "could not create SwsContext for scaling\n");
return AVERROR(ENOMEM);
}
sr_context->sws_slice_h = sws_src_h;
}
}
return 0;
}
}
static int filter_frame(AVFilterLink *inlink, AVFrame *in)
{
AVFilterContext *context = inlink->dst;
SRContext *sr_context = context->priv;
AVFilterLink *outlink = context->outputs[0];
AVFrame *out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
DNNReturnType dnn_result;
if (!out){
av_log(context, 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 = sr_context->output.height;
out->width = sr_context->output.width;
if (sr_context->scale_factor){
sws_scale(sr_context->sws_contexts[0], (const uint8_t **)in->data, in->linesize,
0, sr_context->sws_slice_h, out->data, out->linesize);
sws_scale(sr_context->sws_contexts[1], (const uint8_t **)out->data, out->linesize,
0, out->height, (uint8_t * const*)(&sr_context->input.data), &sr_context->sws_input_linesize);
}
else{
if (sr_context->sws_contexts[0]){
sws_scale(sr_context->sws_contexts[0], (const uint8_t **)(in->data + 1), in->linesize + 1,
0, sr_context->sws_slice_h, out->data + 1, out->linesize + 1);
sws_scale(sr_context->sws_contexts[0], (const uint8_t **)(in->data + 2), in->linesize + 2,
0, sr_context->sws_slice_h, out->data + 2, out->linesize + 2);
}
sws_scale(sr_context->sws_contexts[1], (const uint8_t **)in->data, in->linesize,
0, in->height, (uint8_t * const*)(&sr_context->input.data), &sr_context->sws_input_linesize);
}
av_frame_free(&in);
dnn_result = (sr_context->dnn_module->execute_model)(sr_context->model);
if (dnn_result != DNN_SUCCESS){
av_log(context, AV_LOG_ERROR, "failed to execute loaded model\n");
return AVERROR(EIO);
}
sws_scale(sr_context->sws_contexts[2], (const uint8_t **)(&sr_context->output.data), &sr_context->sws_output_linesize,
0, out->height, (uint8_t * const*)out->data, out->linesize);
return ff_filter_frame(outlink, out);
}
static av_cold void uninit(AVFilterContext *context)
{
int i;
SRContext *sr_context = context->priv;
if (sr_context->dnn_module){
(sr_context->dnn_module->free_model)(&sr_context->model);
av_freep(&sr_context->dnn_module);
}
for (i = 0; i < 3; ++i){
if (sr_context->sws_contexts[i]){
sws_freeContext(sr_context->sws_contexts[i]);
}
}
}
static const AVFilterPad sr_inputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
.config_props = config_props,
.filter_frame = filter_frame,
},
{ NULL }
};
static const AVFilterPad sr_outputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
},
{ NULL }
};
AVFilter ff_vf_sr = {
.name = "sr",
.description = NULL_IF_CONFIG_SMALL("Apply DNN-based image super resolution to the input."),
.priv_size = sizeof(SRContext),
.init = init,
.uninit = uninit,
.query_formats = query_formats,
.inputs = sr_inputs,
.outputs = sr_outputs,
.priv_class = &sr_class,
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
};
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