1
0
mirror of https://github.com/FFmpeg/FFmpeg.git synced 2024-12-07 11:13:41 +02:00
FFmpeg/libavfilter/vf_sr.c
Ting Fu 130d19bf20 lavf/sr: fix the segmentation fault caused by incorrect input frame free.
This issue would cause segmetaion fault when running srcnn model with
sr filter by TensorFlow backend. This filter would free the frame incorectly.

Signed-off-by: Ting Fu <ting.fu@intel.com>
2022-07-22 08:15:04 +08:00

204 lines
7.2 KiB
C

/*
* 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 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
};
static int config_output(AVFilterLink *outlink)
{
AVFilterContext *context = outlink->src;
SRContext *ctx = context->priv;
int 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 != 0) {
av_log(ctx, AV_LOG_ERROR, "could not get output from the model\n");
return result;
}
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);
int 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 != 0){
av_log(ctx, AV_LOG_ERROR, "failed to execute loaded model\n");
av_frame_free(&in);
av_frame_free(&out);
return dnn_result;
}
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);
}
if (in != out) {
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_PIXFMTS_ARRAY(pixel_formats),
.priv_class = &sr_class,
};