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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 "libavutil/pixdesc.h"
#include "libavformat/avio.h"
#include "libswscale/swscale.h"
#include "dnn_filter_common.h"
typedef struct SRContext {
const AVClass *class;
DnnContext dnnctx;
int scale_factor;
struct SwsContext *sws_uv_scale;
int sws_uv_height;
struct SwsContext *sws_pre_scale;
} 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(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
{ "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(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_outputnames_string), AV_OPT_TYPE_STRING, { .str = "y" }, 0, 0, FLAGS },
{ NULL }
};
AVFILTER_DEFINE_CLASS(sr);
static av_cold int init(AVFilterContext *context)
{
SRContext *sr_context = context->priv;
return ff_dnn_init(&sr_context->dnnctx, DFT_PROCESS_FRAME, context);
}
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};
return ff_set_common_formats_from_list(context, pixel_formats);
}
static int config_output(AVFilterLink *outlink)
{
AVFilterContext *context = outlink->src;
SRContext *ctx = context->priv;
DNNReturnType result;
AVFilterLink *inlink = context->inputs[0];
int out_width, out_height;
// have a try run in case that the dnn model resize the frame
result = ff_dnn_get_output(&ctx->dnnctx, inlink->w, inlink->h, &out_width, &out_height);
if (result != DNN_SUCCESS) {
av_log(ctx, AV_LOG_ERROR, "could not get output from the model\n");
return AVERROR(EIO);
}
if (inlink->w != out_width || inlink->h != out_height) {
//espcn
outlink->w = out_width;
outlink->h = out_height;
if (inlink->format != AV_PIX_FMT_GRAY8){
const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(inlink->format);
int sws_src_h = AV_CEIL_RSHIFT(inlink->h, desc->log2_chroma_h);
int sws_src_w = AV_CEIL_RSHIFT(inlink->w, desc->log2_chroma_w);
int sws_dst_h = AV_CEIL_RSHIFT(outlink->h, desc->log2_chroma_h);
int sws_dst_w = AV_CEIL_RSHIFT(outlink->w, desc->log2_chroma_w);
ctx->sws_uv_scale = 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);
ctx->sws_uv_height = sws_src_h;
}
} else {
//srcnn
outlink->w = out_width * ctx->scale_factor;
outlink->h = out_height * ctx->scale_factor;
ctx->sws_pre_scale = sws_getContext(inlink->w, inlink->h, inlink->format,
outlink->w, outlink->h, outlink->format,
SWS_BICUBIC, NULL, NULL, NULL);
}
return 0;
}
static int filter_frame(AVFilterLink *inlink, AVFrame *in)
{
DNNAsyncStatusType async_state = 0;
AVFilterContext *context = inlink->dst;
SRContext *ctx = 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);
if (ctx->sws_pre_scale) {
sws_scale(ctx->sws_pre_scale,
(const uint8_t **)in->data, in->linesize, 0, in->height,
out->data, out->linesize);
dnn_result = ff_dnn_execute_model(&ctx->dnnctx, out, out);
} else {
dnn_result = ff_dnn_execute_model(&ctx->dnnctx, in, out);
}
if (dnn_result != DNN_SUCCESS){
av_log(ctx, AV_LOG_ERROR, "failed to execute loaded model\n");
av_frame_free(&in);
av_frame_free(&out);
return AVERROR(EIO);
}
do {
async_state = ff_dnn_get_result(&ctx->dnnctx, &in, &out);
} while (async_state == DAST_NOT_READY);
if (async_state != DAST_SUCCESS)
return AVERROR(EINVAL);
if (ctx->sws_uv_scale) {
sws_scale(ctx->sws_uv_scale, (const uint8_t **)(in->data + 1), in->linesize + 1,
0, ctx->sws_uv_height, out->data + 1, out->linesize + 1);
sws_scale(ctx->sws_uv_scale, (const uint8_t **)(in->data + 2), in->linesize + 2,
0, ctx->sws_uv_height, out->data + 2, out->linesize + 2);
}
av_frame_free(&in);
return ff_filter_frame(outlink, out);
}
static av_cold void uninit(AVFilterContext *context)
{
SRContext *sr_context = context->priv;
ff_dnn_uninit(&sr_context->dnnctx);
sws_freeContext(sr_context->sws_uv_scale);
sws_freeContext(sr_context->sws_pre_scale);
}
static const AVFilterPad sr_inputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
.filter_frame = filter_frame,
},
};
static const AVFilterPad sr_outputs[] = {
{
.name = "default",
.config_props = config_output,
.type = AVMEDIA_TYPE_VIDEO,
},
};
const 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,
FILTER_INPUTS(sr_inputs),
FILTER_OUTPUTS(sr_outputs),
FILTER_QUERY_FUNC(query_formats),
.priv_class = &sr_class,
};
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