2018-06-13 23:37:12 +02:00
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/*
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* Copyright (c) 2018 Sergey Lavrushkin
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*
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* This file is part of FFmpeg.
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*
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* FFmpeg is free software; you can redistribute it and/or
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* modify it under the terms of the GNU Lesser General Public
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* License as published by the Free Software Foundation; either
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* version 2.1 of the License, or (at your option) any later version.
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*
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* FFmpeg is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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* Lesser General Public License for more details.
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*
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* You should have received a copy of the GNU Lesser General Public
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* License along with FFmpeg; if not, write to the Free Software
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* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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*/
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/**
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* @file
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* Filter implementing image super-resolution using deep convolutional networks.
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* https://arxiv.org/abs/1501.00092
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* https://arxiv.org/abs/1609.05158
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*/
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#include "avfilter.h"
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#include "formats.h"
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#include "internal.h"
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#include "libavutil/opt.h"
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2019-06-01 05:20:33 +02:00
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#include "libavutil/pixdesc.h"
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2018-06-13 23:37:12 +02:00
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#include "libavformat/avio.h"
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#include "libswscale/swscale.h"
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#include "dnn_interface.h"
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typedef struct SRContext {
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const AVClass *class;
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2018-07-27 18:34:02 +02:00
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char *model_filename;
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2018-06-13 23:37:12 +02:00
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DNNBackendType backend_type;
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2018-07-27 18:34:02 +02:00
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DNNModule *dnn_module;
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DNNModel *model;
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2018-06-13 23:37:12 +02:00
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int scale_factor;
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2020-08-28 06:51:44 +02:00
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struct SwsContext *sws_uv_scale;
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int sws_uv_height;
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struct SwsContext *sws_pre_scale;
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2018-06-13 23:37:12 +02:00
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} SRContext;
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#define OFFSET(x) offsetof(SRContext, x)
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#define FLAGS AV_OPT_FLAG_FILTERING_PARAM | AV_OPT_FLAG_VIDEO_PARAM
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static const AVOption sr_options[] = {
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2019-05-25 13:59:42 +02:00
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{ "dnn_backend", "DNN backend used for model execution", OFFSET(backend_type), AV_OPT_TYPE_INT, { .i64 = 0 }, 0, 1, FLAGS, "backend" },
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2018-06-13 23:37:12 +02:00
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{ "native", "native backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = 0 }, 0, 0, FLAGS, "backend" },
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#if (CONFIG_LIBTENSORFLOW == 1)
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{ "tensorflow", "tensorflow backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = 1 }, 0, 0, FLAGS, "backend" },
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#endif
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2018-09-06 13:33:06 +02:00
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{ "scale_factor", "scale factor for SRCNN model", OFFSET(scale_factor), AV_OPT_TYPE_INT, { .i64 = 2 }, 2, 4, FLAGS },
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{ "model", "path to model file specifying network architecture and its parameters", OFFSET(model_filename), AV_OPT_TYPE_STRING, {.str=NULL}, 0, 0, FLAGS },
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2018-06-13 23:37:12 +02:00
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{ NULL }
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};
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AVFILTER_DEFINE_CLASS(sr);
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2018-07-27 18:34:02 +02:00
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static av_cold int init(AVFilterContext *context)
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2018-06-13 23:37:12 +02:00
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{
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2018-07-27 18:34:02 +02:00
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SRContext *sr_context = context->priv;
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2018-06-13 23:37:12 +02:00
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sr_context->dnn_module = ff_get_dnn_module(sr_context->backend_type);
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if (!sr_context->dnn_module){
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av_log(context, AV_LOG_ERROR, "could not create DNN module for requested backend\n");
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return AVERROR(ENOMEM);
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}
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2019-06-01 05:28:56 +02:00
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2018-06-13 23:37:12 +02:00
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if (!sr_context->model_filename){
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2018-09-06 13:33:06 +02:00
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av_log(context, AV_LOG_ERROR, "model file for network was not specified\n");
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return AVERROR(EIO);
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2018-06-13 23:37:12 +02:00
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}
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2019-06-01 05:28:56 +02:00
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if (!sr_context->dnn_module->load_model) {
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av_log(context, AV_LOG_ERROR, "load_model for network was not specified\n");
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return AVERROR(EIO);
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}
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2020-08-24 10:09:59 +02:00
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sr_context->model = (sr_context->dnn_module->load_model)(sr_context->model_filename, NULL, NULL);
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2018-06-13 23:37:12 +02:00
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if (!sr_context->model){
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av_log(context, AV_LOG_ERROR, "could not load DNN model\n");
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return AVERROR(EIO);
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}
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return 0;
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}
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2018-07-27 18:34:02 +02:00
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static int query_formats(AVFilterContext *context)
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2018-06-13 23:37:12 +02:00
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{
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const enum AVPixelFormat pixel_formats[] = {AV_PIX_FMT_YUV420P, AV_PIX_FMT_YUV422P, AV_PIX_FMT_YUV444P,
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AV_PIX_FMT_YUV410P, AV_PIX_FMT_YUV411P, AV_PIX_FMT_GRAY8,
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AV_PIX_FMT_NONE};
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2018-07-27 18:34:02 +02:00
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AVFilterFormats *formats_list;
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2018-06-13 23:37:12 +02:00
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formats_list = ff_make_format_list(pixel_formats);
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if (!formats_list){
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av_log(context, AV_LOG_ERROR, "could not create formats list\n");
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return AVERROR(ENOMEM);
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}
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2018-07-31 17:58:28 +02:00
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2018-06-13 23:37:12 +02:00
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return ff_set_common_formats(context, formats_list);
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}
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2020-08-28 06:51:44 +02:00
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static int config_output(AVFilterLink *outlink)
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2018-06-13 23:37:12 +02:00
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{
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2020-08-28 06:51:44 +02:00
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AVFilterContext *context = outlink->src;
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SRContext *ctx = context->priv;
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2018-06-13 23:37:12 +02:00
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DNNReturnType result;
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2020-08-28 06:51:44 +02:00
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AVFilterLink *inlink = context->inputs[0];
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2020-09-11 16:15:04 +02:00
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int out_width, out_height;
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2018-06-13 23:37:12 +02:00
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2020-08-28 06:51:44 +02:00
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// have a try run in case that the dnn model resize the frame
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2020-09-11 16:15:04 +02:00
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result = ctx->model->get_output(ctx->model->model, "x", inlink->w, inlink->h,
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"y", &out_width, &out_height);
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if (result != DNN_SUCCESS) {
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av_log(ctx, AV_LOG_ERROR, "could not get output from the model\n");
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2019-04-25 04:14:17 +02:00
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return AVERROR(EIO);
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}
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2020-09-11 16:15:04 +02:00
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if (inlink->w != out_width || inlink->h != out_height) {
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2020-08-28 06:51:44 +02:00
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//espcn
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2020-09-11 16:15:04 +02:00
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outlink->w = out_width;
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outlink->h = out_height;
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2019-04-25 04:14:01 +02:00
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if (inlink->format != AV_PIX_FMT_GRAY8){
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2020-02-21 13:29:12 +02:00
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const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(inlink->format);
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2020-08-28 06:51:44 +02:00
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int sws_src_h = AV_CEIL_RSHIFT(inlink->h, desc->log2_chroma_h);
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int sws_src_w = AV_CEIL_RSHIFT(inlink->w, desc->log2_chroma_w);
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int sws_dst_h = AV_CEIL_RSHIFT(outlink->h, desc->log2_chroma_h);
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int sws_dst_w = AV_CEIL_RSHIFT(outlink->w, desc->log2_chroma_w);
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ctx->sws_uv_scale = sws_getContext(sws_src_w, sws_src_h, AV_PIX_FMT_GRAY8,
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sws_dst_w, sws_dst_h, AV_PIX_FMT_GRAY8,
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SWS_BICUBIC, NULL, NULL, NULL);
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ctx->sws_uv_height = sws_src_h;
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2018-06-13 23:37:12 +02:00
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}
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2020-08-28 06:51:44 +02:00
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} else {
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//srcnn
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2020-09-11 16:15:04 +02:00
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outlink->w = out_width * ctx->scale_factor;
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outlink->h = out_height * ctx->scale_factor;
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2020-08-28 06:51:44 +02:00
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ctx->sws_pre_scale = sws_getContext(inlink->w, inlink->h, inlink->format,
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outlink->w, outlink->h, outlink->format,
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SWS_BICUBIC, NULL, NULL, NULL);
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2018-06-13 23:37:12 +02:00
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}
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2019-04-25 04:14:01 +02:00
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return 0;
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2018-06-13 23:37:12 +02:00
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}
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2018-07-27 18:34:02 +02:00
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static int filter_frame(AVFilterLink *inlink, AVFrame *in)
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2018-06-13 23:37:12 +02:00
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{
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2018-07-27 18:34:02 +02:00
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AVFilterContext *context = inlink->dst;
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2020-08-28 06:51:44 +02:00
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SRContext *ctx = context->priv;
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2018-07-27 18:34:02 +02:00
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AVFilterLink *outlink = context->outputs[0];
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AVFrame *out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
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2018-06-13 23:37:12 +02:00
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DNNReturnType dnn_result;
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2020-08-13 10:19:48 +02:00
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const char *model_output_name = "y";
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2018-06-13 23:37:12 +02:00
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if (!out){
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av_log(context, AV_LOG_ERROR, "could not allocate memory for output frame\n");
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av_frame_free(&in);
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return AVERROR(ENOMEM);
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}
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av_frame_copy_props(out, in);
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2018-07-31 17:58:28 +02:00
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2020-08-28 06:51:44 +02:00
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if (ctx->sws_pre_scale) {
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sws_scale(ctx->sws_pre_scale,
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(const uint8_t **)in->data, in->linesize, 0, in->height,
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out->data, out->linesize);
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2020-09-10 16:29:57 +02:00
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dnn_result = (ctx->dnn_module->execute_model)(ctx->model, "x", out,
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(const char **)&model_output_name, 1, out);
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2019-04-25 04:14:01 +02:00
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} else {
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2020-09-10 16:29:57 +02:00
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dnn_result = (ctx->dnn_module->execute_model)(ctx->model, "x", in,
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(const char **)&model_output_name, 1, out);
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2018-07-31 17:58:28 +02:00
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}
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2018-06-13 23:37:12 +02:00
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if (dnn_result != DNN_SUCCESS){
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2020-08-28 06:51:44 +02:00
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av_log(ctx, AV_LOG_ERROR, "failed to execute loaded model\n");
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av_frame_free(&in);
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av_frame_free(&out);
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2018-06-13 23:37:12 +02:00
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return AVERROR(EIO);
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}
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2020-08-28 06:51:44 +02:00
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if (ctx->sws_uv_scale) {
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sws_scale(ctx->sws_uv_scale, (const uint8_t **)(in->data + 1), in->linesize + 1,
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0, ctx->sws_uv_height, out->data + 1, out->linesize + 1);
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sws_scale(ctx->sws_uv_scale, (const uint8_t **)(in->data + 2), in->linesize + 2,
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0, ctx->sws_uv_height, out->data + 2, out->linesize + 2);
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}
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2018-06-13 23:37:12 +02:00
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2020-08-28 06:51:44 +02:00
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av_frame_free(&in);
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2018-06-13 23:37:12 +02:00
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return ff_filter_frame(outlink, out);
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}
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2018-07-27 18:34:02 +02:00
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static av_cold void uninit(AVFilterContext *context)
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2018-06-13 23:37:12 +02:00
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{
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2018-07-27 18:34:02 +02:00
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SRContext *sr_context = context->priv;
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2018-06-13 23:37:12 +02:00
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if (sr_context->dnn_module){
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(sr_context->dnn_module->free_model)(&sr_context->model);
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av_freep(&sr_context->dnn_module);
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}
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2020-08-28 06:51:44 +02:00
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sws_freeContext(sr_context->sws_uv_scale);
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sws_freeContext(sr_context->sws_pre_scale);
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2018-06-13 23:37:12 +02:00
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}
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static const AVFilterPad sr_inputs[] = {
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{
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.name = "default",
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.type = AVMEDIA_TYPE_VIDEO,
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.filter_frame = filter_frame,
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},
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{ NULL }
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};
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static const AVFilterPad sr_outputs[] = {
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{
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.name = "default",
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2020-08-28 06:51:44 +02:00
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.config_props = config_output,
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2018-06-13 23:37:12 +02:00
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.type = AVMEDIA_TYPE_VIDEO,
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},
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{ NULL }
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};
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AVFilter ff_vf_sr = {
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.name = "sr",
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.description = NULL_IF_CONFIG_SMALL("Apply DNN-based image super resolution to the input."),
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.priv_size = sizeof(SRContext),
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.init = init,
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.uninit = uninit,
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.query_formats = query_formats,
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.inputs = sr_inputs,
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.outputs = sr_outputs,
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.priv_class = &sr_class,
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};
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