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-rw-r--r--libavfilter/vf_srcnn.c250
1 files changed, 0 insertions, 250 deletions
diff --git a/libavfilter/vf_srcnn.c b/libavfilter/vf_srcnn.c
deleted file mode 100644
index bba54f6780..0000000000
--- a/libavfilter/vf_srcnn.c
+++ /dev/null
@@ -1,250 +0,0 @@
-/*
- * 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
- */
-
-#include "avfilter.h"
-#include "formats.h"
-#include "internal.h"
-#include "libavutil/opt.h"
-#include "libavformat/avio.h"
-#include "dnn_interface.h"
-
-typedef struct SRCNNContext {
- const AVClass *class;
-
- char* model_filename;
- float* input_output_buf;
- DNNBackendType backend_type;
- DNNModule* dnn_module;
- DNNModel* model;
- DNNData input_output;
-} SRCNNContext;
-
-#define OFFSET(x) offsetof(SRCNNContext, x)
-#define FLAGS AV_OPT_FLAG_FILTERING_PARAM | AV_OPT_FLAG_VIDEO_PARAM
-static const AVOption srcnn_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
- { "model_filename", "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(srcnn);
-
-static av_cold int init(AVFilterContext* context)
-{
- SRCNNContext* srcnn_context = context->priv;
-
- srcnn_context->dnn_module = ff_get_dnn_module(srcnn_context->backend_type);
- if (!srcnn_context->dnn_module){
- av_log(context, AV_LOG_ERROR, "could not create DNN module for requested backend\n");
- return AVERROR(ENOMEM);
- }
- if (!srcnn_context->model_filename){
- av_log(context, AV_LOG_VERBOSE, "model file for network was not specified, using default network for x2 upsampling\n");
- srcnn_context->model = (srcnn_context->dnn_module->load_default_model)(DNN_SRCNN);
- }
- else{
- srcnn_context->model = (srcnn_context->dnn_module->load_model)(srcnn_context->model_filename);
- }
- if (!srcnn_context->model){
- av_log(context, AV_LOG_ERROR, "could not load DNN model\n");
- return AVERROR(EIO);
- }
-
- 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;
- SRCNNContext* srcnn_context = context->priv;
- DNNReturnType result;
-
- srcnn_context->input_output_buf = av_malloc(inlink->h * inlink->w * sizeof(float));
- if (!srcnn_context->input_output_buf){
- av_log(context, AV_LOG_ERROR, "could not allocate memory for input/output buffer\n");
- return AVERROR(ENOMEM);
- }
-
- srcnn_context->input_output.data = srcnn_context->input_output_buf;
- srcnn_context->input_output.width = inlink->w;
- srcnn_context->input_output.height = inlink->h;
- srcnn_context->input_output.channels = 1;
-
- result = (srcnn_context->model->set_input_output)(srcnn_context->model->model, &srcnn_context->input_output, &srcnn_context->input_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{
- return 0;
- }
-}
-
-typedef struct ThreadData{
- uint8_t* out;
- int out_linesize, height, width;
-} ThreadData;
-
-static int uint8_to_float(AVFilterContext* context, void* arg, int jobnr, int nb_jobs)
-{
- SRCNNContext* srcnn_context = context->priv;
- const ThreadData* td = arg;
- const int slice_start = (td->height * jobnr ) / nb_jobs;
- const int slice_end = (td->height * (jobnr + 1)) / nb_jobs;
- const uint8_t* src = td->out + slice_start * td->out_linesize;
- float* dst = srcnn_context->input_output_buf + slice_start * td->width;
- int y, x;
-
- for (y = slice_start; y < slice_end; ++y){
- for (x = 0; x < td->width; ++x){
- dst[x] = (float)src[x] / 255.0f;
- }
- src += td->out_linesize;
- dst += td->width;
- }
-
- return 0;
-}
-
-static int float_to_uint8(AVFilterContext* context, void* arg, int jobnr, int nb_jobs)
-{
- SRCNNContext* srcnn_context = context->priv;
- const ThreadData* td = arg;
- const int slice_start = (td->height * jobnr ) / nb_jobs;
- const int slice_end = (td->height * (jobnr + 1)) / nb_jobs;
- const float* src = srcnn_context->input_output_buf + slice_start * td->width;
- uint8_t* dst = td->out + slice_start * td->out_linesize;
- int y, x;
-
- for (y = slice_start; y < slice_end; ++y){
- for (x = 0; x < td->width; ++x){
- dst[x] = (uint8_t)(255.0f * FFMIN(src[x], 1.0f));
- }
- src += td->width;
- dst += td->out_linesize;
- }
-
- return 0;
-}
-
-static int filter_frame(AVFilterLink* inlink, AVFrame* in)
-{
- AVFilterContext* context = inlink->dst;
- SRCNNContext* srcnn_context = context->priv;
- AVFilterLink* outlink = context->outputs[0];
- AVFrame* out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
- ThreadData td;
- int nb_threads;
- 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);
- av_frame_copy(out, in);
- av_frame_free(&in);
- td.out = out->data[0];
- td.out_linesize = out->linesize[0];
- td.height = out->height;
- td.width = out->width;
-
- nb_threads = ff_filter_get_nb_threads(context);
- context->internal->execute(context, uint8_to_float, &td, NULL, FFMIN(td.height, nb_threads));
-
- dnn_result = (srcnn_context->dnn_module->execute_model)(srcnn_context->model);
- if (dnn_result != DNN_SUCCESS){
- av_log(context, AV_LOG_ERROR, "failed to execute loaded model\n");
- return AVERROR(EIO);
- }
-
- context->internal->execute(context, float_to_uint8, &td, NULL, FFMIN(td.height, nb_threads));
-
- return ff_filter_frame(outlink, out);
-}
-
-static av_cold void uninit(AVFilterContext* context)
-{
- SRCNNContext* srcnn_context = context->priv;
-
- if (srcnn_context->dnn_module){
- (srcnn_context->dnn_module->free_model)(&srcnn_context->model);
- av_freep(&srcnn_context->dnn_module);
- }
- av_freep(&srcnn_context->input_output_buf);
-}
-
-static const AVFilterPad srcnn_inputs[] = {
- {
- .name = "default",
- .type = AVMEDIA_TYPE_VIDEO,
- .config_props = config_props,
- .filter_frame = filter_frame,
- },
- { NULL }
-};
-
-static const AVFilterPad srcnn_outputs[] = {
- {
- .name = "default",
- .type = AVMEDIA_TYPE_VIDEO,
- },
- { NULL }
-};
-
-AVFilter ff_vf_srcnn = {
- .name = "srcnn",
- .description = NULL_IF_CONFIG_SMALL("Apply super resolution convolutional neural network to the input. Use bicubic upsamping with corresponding scaling factor before."),
- .priv_size = sizeof(SRCNNContext),
- .init = init,
- .uninit = uninit,
- .query_formats = query_formats,
- .inputs = srcnn_inputs,
- .outputs = srcnn_outputs,
- .priv_class = &srcnn_class,
- .flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
-};
-
generated by cgit v1.2.3 (git 2.39.1) at 2024-07-23 17:21:36 +0000