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https://github.com/FFmpeg/FFmpeg.git
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d0a999a0ab
This patch removes all occurences of DNNReturnType from the DNN module. This commit replaces DNN_SUCCESS by 0 (essentially the same), so the functions with DNNReturnType now return 0 in case of success, the negative values otherwise. Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com> Signed-off-by: Shubhanshu Saxena <shubhanshu.e01@gmail.com>
203 lines
7.2 KiB
C
203 lines
7.2 KiB
C
/*
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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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#include "libavutil/pixdesc.h"
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#include "libavformat/avio.h"
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#include "libswscale/swscale.h"
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#include "dnn_filter_common.h"
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typedef struct SRContext {
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const AVClass *class;
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DnnContext dnnctx;
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int scale_factor;
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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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} 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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{ "dnn_backend", "DNN backend used for model execution", OFFSET(dnnctx.backend_type), AV_OPT_TYPE_INT, { .i64 = 0 }, 0, 1, FLAGS, "backend" },
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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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{ "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(dnnctx.model_filename), AV_OPT_TYPE_STRING, {.str=NULL}, 0, 0, FLAGS },
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{ "input", "input name of the model", OFFSET(dnnctx.model_inputname), AV_OPT_TYPE_STRING, { .str = "x" }, 0, 0, FLAGS },
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{ "output", "output name of the model", OFFSET(dnnctx.model_outputnames_string), AV_OPT_TYPE_STRING, { .str = "y" }, 0, 0, FLAGS },
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{ NULL }
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};
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AVFILTER_DEFINE_CLASS(sr);
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static av_cold int init(AVFilterContext *context)
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{
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SRContext *sr_context = context->priv;
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return ff_dnn_init(&sr_context->dnnctx, DFT_PROCESS_FRAME, context);
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}
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static const enum AVPixelFormat pixel_formats[] = {
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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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};
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static int config_output(AVFilterLink *outlink)
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{
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AVFilterContext *context = outlink->src;
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SRContext *ctx = context->priv;
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int result;
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AVFilterLink *inlink = context->inputs[0];
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int out_width, out_height;
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// have a try run in case that the dnn model resize the frame
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result = ff_dnn_get_output(&ctx->dnnctx, inlink->w, inlink->h, &out_width, &out_height);
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if (result != 0) {
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av_log(ctx, AV_LOG_ERROR, "could not get output from the model\n");
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return result;
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}
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if (inlink->w != out_width || inlink->h != out_height) {
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//espcn
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outlink->w = out_width;
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outlink->h = out_height;
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if (inlink->format != AV_PIX_FMT_GRAY8){
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const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(inlink->format);
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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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}
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} else {
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//srcnn
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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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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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}
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return 0;
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}
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static int filter_frame(AVFilterLink *inlink, AVFrame *in)
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{
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DNNAsyncStatusType async_state = 0;
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AVFilterContext *context = inlink->dst;
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SRContext *ctx = context->priv;
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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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int dnn_result;
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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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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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dnn_result = ff_dnn_execute_model(&ctx->dnnctx, out, out);
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} else {
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dnn_result = ff_dnn_execute_model(&ctx->dnnctx, in, out);
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}
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if (dnn_result != 0){
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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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return dnn_result;
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}
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do {
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async_state = ff_dnn_get_result(&ctx->dnnctx, &in, &out);
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} while (async_state == DAST_NOT_READY);
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if (async_state != DAST_SUCCESS)
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return AVERROR(EINVAL);
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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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av_frame_free(&in);
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return ff_filter_frame(outlink, out);
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}
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static av_cold void uninit(AVFilterContext *context)
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{
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SRContext *sr_context = context->priv;
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ff_dnn_uninit(&sr_context->dnnctx);
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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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}
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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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};
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static const AVFilterPad sr_outputs[] = {
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{
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.name = "default",
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.config_props = config_output,
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.type = AVMEDIA_TYPE_VIDEO,
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},
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};
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const 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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FILTER_INPUTS(sr_inputs),
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FILTER_OUTPUTS(sr_outputs),
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FILTER_PIXFMTS_ARRAY(pixel_formats),
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.priv_class = &sr_class,
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};
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