/* * 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_interface.h" typedef struct SRContext { const AVClass *class; char *model_filename; DNNBackendType backend_type; DNNModule *dnn_module; DNNModel *model; DNNInputData input; DNNData 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_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(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 { if (!sr_context->dnn_module->load_model) { av_log(context, AV_LOG_ERROR, "load_model 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->input.dt = DNN_FLOAT; 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; const char *model_output_name = "y"; 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, "x", &model_output_name, 1); if (result != DNN_SUCCESS){ av_log(context, AV_LOG_ERROR, "could not set input and output for the model\n"); return AVERROR(EIO); } result = (sr_context->dnn_module->execute_model)(sr_context->model, &sr_context->output, 1); if (result != DNN_SUCCESS){ av_log(context, AV_LOG_ERROR, "failed to execute loaded model\n"); return AVERROR(EIO); } 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, "x", &model_output_name, 1); if (result != DNN_SUCCESS){ av_log(context, AV_LOG_ERROR, "could not set input and output for the model\n"); return AVERROR(EIO); } result = (sr_context->dnn_module->execute_model)(sr_context->model, &sr_context->output, 1); if (result != DNN_SUCCESS){ av_log(context, AV_LOG_ERROR, "failed to execute loaded 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: %s\n", av_get_pix_fmt_name(inlink->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), (const int [4]){sr_context->sws_input_linesize, 0, 0, 0}); } 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), (const int [4]){sr_context->sws_input_linesize, 0, 0, 0}); } av_frame_free(&in); dnn_result = (sr_context->dnn_module->execute_model)(sr_context->model, &sr_context->output, 1); 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 *[4]){(const uint8_t *)sr_context->output.data, 0, 0, 0}, (const int[4]){sr_context->sws_output_linesize, 0, 0, 0}, 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, };