From patchwork Fri Oct 19 18:04:28 2018 Content-Type: text/plain; charset="utf-8" MIME-Version: 1.0 Content-Transfer-Encoding: 8bit X-Patchwork-Submitter: "Guo, Yejun" X-Patchwork-Id: 10716 Return-Path: X-Original-To: patchwork@ffaux-bg.ffmpeg.org Delivered-To: patchwork@ffaux-bg.ffmpeg.org Received: from ffbox0-bg.mplayerhq.hu (ffbox0-bg.ffmpeg.org [79.124.17.100]) by ffaux.localdomain (Postfix) with ESMTP id 319AE447683 for ; Fri, 19 Oct 2018 13:10:56 +0300 (EEST) Received: from [127.0.1.1] (localhost [127.0.0.1]) by ffbox0-bg.mplayerhq.hu (Postfix) with ESMTP id 8340468A71A; Fri, 19 Oct 2018 13:10:37 +0300 (EEST) X-Original-To: ffmpeg-devel@ffmpeg.org Delivered-To: ffmpeg-devel@ffmpeg.org Received: from mga18.intel.com (mga18.intel.com [134.134.136.126]) by ffbox0-bg.mplayerhq.hu (Postfix) with ESMTPS id C60F568A669 for ; Fri, 19 Oct 2018 13:10:30 +0300 (EEST) X-Amp-Result: SKIPPED(no attachment in message) X-Amp-File-Uploaded: False Received: from orsmga004.jf.intel.com ([10.7.209.38]) by orsmga106.jf.intel.com with ESMTP/TLS/DHE-RSA-AES256-GCM-SHA384; 19 Oct 2018 03:10:54 -0700 X-ExtLoop1: 1 X-IronPort-AV: E=Sophos;i="5.54,399,1534834800"; d="scan'208";a="242604877" Received: from yguo18-skl-u1604.sh.intel.com ([10.239.13.25]) by orsmga004.jf.intel.com with ESMTP; 19 Oct 2018 03:10:53 -0700 From: "Guo, Yejun" To: ffmpeg-devel@ffmpeg.org Date: Sat, 20 Oct 2018 02:04:28 +0800 Message-Id: <1539972268-31472-1-git-send-email-yejun.guo@intel.com> X-Mailer: git-send-email 2.7.4 MIME-Version: 1.0 Subject: [FFmpeg-devel] [PATCH V3] Add a filter implementing HDR image reconstruction from a single exposure using deep CNNs X-BeenThere: ffmpeg-devel@ffmpeg.org X-Mailman-Version: 2.1.20 Precedence: list List-Id: FFmpeg development discussions and patches List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , Reply-To: FFmpeg development discussions and patches Cc: "Guo, Yejun" , Guo@ffbox0-bg.ffmpeg.org Errors-To: ffmpeg-devel-bounces@ffmpeg.org Sender: "ffmpeg-devel" see the algorithm's paper and code below. the filter's parameter looks like: sdr2hdr=model_filename=/path_to_tensorflow_graph.pb:out_fmt=gbrp10le The input of the deep CNN model is RGB24 while the output is float for each color channel. This is the filter's default behavior to output format with gbrpf32le. And gbrp10le is also supported as the output, so we can see the rendering result in a player, as a reference. To generate the model file, we need modify the original script a little. - set name='y' for y_final within script at https://github.com/gabrieleilertsen/hdrcnn/blob/master/network.py - add the following code to the script at https://github.com/gabrieleilertsen/hdrcnn/blob/master/hdrcnn_predict.py graph = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ["y"]) tf.train.write_graph(graph, '.', 'graph.pb', as_text=False) The filter only works when tensorflow C api is supported in the system, native backend is not supported since there are some different types of layers in the deep CNN model, besides CONV and DEPTH_TO_SPACE. https://arxiv.org/pdf/1710.07480.pdf: author = "Eilertsen, Gabriel and Kronander, Joel, and Denes, Gyorgy and Mantiuk, Rafał and Unger, Jonas", title = "HDR image reconstruction from a single exposure using deep CNNs", journal = "ACM Transactions on Graphics (TOG)", number = "6", volume = "36", articleno = "178", year = "2017" https://github.com/gabrieleilertsen/hdrcnn btw, as a whole solution, metadata should also be generated from the sdr video, so to be encoded as a HDR video. Not supported yet. This patch just focuses on this paper. v3: use int16_t instead of short v2: use AV_OPT_TYPE_PIXEL_FMT for filter option remove some unnecessary code Use in->linesize[0] and FFMAX/FFMIN remove flag AVFILTER_FLAG_SLICE_THREADS add av_log message when error Signed-off-by: Guo, Yejun Signed-off-by: Guo, Yejun > --- libavfilter/Makefile | 1 + libavfilter/allfilters.c | 1 + libavfilter/vf_sdr2hdr.c | 266 +++++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 268 insertions(+) create mode 100644 libavfilter/vf_sdr2hdr.c diff --git a/libavfilter/Makefile b/libavfilter/Makefile index 62cc2f5..88e7da6 100644 --- a/libavfilter/Makefile +++ b/libavfilter/Makefile @@ -360,6 +360,7 @@ OBJS-$(CONFIG_SOBEL_OPENCL_FILTER) += vf_convolution_opencl.o opencl.o OBJS-$(CONFIG_SPLIT_FILTER) += split.o OBJS-$(CONFIG_SPP_FILTER) += vf_spp.o OBJS-$(CONFIG_SR_FILTER) += vf_sr.o +OBJS-$(CONFIG_SDR2HDR_FILTER) += vf_sdr2hdr.o OBJS-$(CONFIG_SSIM_FILTER) += vf_ssim.o framesync.o OBJS-$(CONFIG_STEREO3D_FILTER) += vf_stereo3d.o OBJS-$(CONFIG_STREAMSELECT_FILTER) += f_streamselect.o framesync.o diff --git a/libavfilter/allfilters.c b/libavfilter/allfilters.c index 5e72803..1645c0f 100644 --- a/libavfilter/allfilters.c +++ b/libavfilter/allfilters.c @@ -319,6 +319,7 @@ extern AVFilter ff_vf_scale_npp; extern AVFilter ff_vf_scale_qsv; extern AVFilter ff_vf_scale_vaapi; extern AVFilter ff_vf_scale2ref; +extern AVFilter ff_vf_sdr2hdr; extern AVFilter ff_vf_select; extern AVFilter ff_vf_selectivecolor; extern AVFilter ff_vf_sendcmd; diff --git a/libavfilter/vf_sdr2hdr.c b/libavfilter/vf_sdr2hdr.c new file mode 100644 index 0000000..6a51a54 --- /dev/null +++ b/libavfilter/vf_sdr2hdr.c @@ -0,0 +1,266 @@ +/* + * Copyright (c) 2018 Guo Yejun + * + * 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 HDR image reconstruction from a single exposure using deep CNNs. + * https://arxiv.org/pdf/1710.07480.pdf + */ + +#include "avfilter.h" +#include "formats.h" +#include "internal.h" +#include "libavutil/opt.h" +#include "libavutil/qsort.h" +#include "libavformat/avio.h" +#include "libswscale/swscale.h" +#include "dnn_interface.h" +#include + +typedef struct SDR2HDRContext { + const AVClass *class; + + char* model_filename; + enum AVPixelFormat out_fmt; + DNNModule* dnn_module; + DNNModel* model; + DNNData input, output; +} SDR2HDRContext; + +#define OFFSET(x) offsetof(SDR2HDRContext, x) +#define FLAGS AV_OPT_FLAG_FILTERING_PARAM | AV_OPT_FLAG_VIDEO_PARAM +static const AVOption sdr2hdr_options[] = { + { "model_filename", "path to model file specifying network architecture and its parameters", OFFSET(model_filename), AV_OPT_TYPE_STRING, {.str=NULL}, 0, 0, FLAGS }, + { "out_fmt", "the data format of the filter's output, it could be gbrpf32le [default] or gbrp10le", OFFSET(out_fmt), AV_OPT_TYPE_PIXEL_FMT, {.i64=AV_PIX_FMT_GBRPF32LE}, AV_PIX_FMT_NONE, AV_PIX_FMT_NB, FLAGS }, + { NULL } +}; + +AVFILTER_DEFINE_CLASS(sdr2hdr); + +static av_cold int init(AVFilterContext* context) +{ + SDR2HDRContext* ctx = context->priv; + + if (ctx->out_fmt != AV_PIX_FMT_GBRPF32LE && ctx->out_fmt != AV_PIX_FMT_GBRP10LE) { + av_log(context, AV_LOG_ERROR, "could not support the output format\n"); + return AVERROR(ENOSYS); + } + +#if (CONFIG_LIBTENSORFLOW == 1) + ctx->dnn_module = ff_get_dnn_module(DNN_TF); + if (!ctx->dnn_module){ + av_log(context, AV_LOG_ERROR, "could not create DNN module for tensorflow backend\n"); + return AVERROR(ENOMEM); + } + if (!ctx->model_filename){ + av_log(context, AV_LOG_ERROR, "model file for network was not specified\n"); + return AVERROR(EIO); + } + if (!ctx->dnn_module->load_model) { + av_log(context, AV_LOG_ERROR, "load_model for network was not specified\n"); + return AVERROR(EIO); + } + ctx->model = (ctx->dnn_module->load_model)(ctx->model_filename); + if (!ctx->model){ + av_log(context, AV_LOG_ERROR, "could not load DNN model\n"); + return AVERROR(EIO); + } + return 0; +#else + return AVERROR(EIO); +#endif +} + +static int query_formats(AVFilterContext* context) +{ + const enum AVPixelFormat in_formats[] = {AV_PIX_FMT_RGB24, + AV_PIX_FMT_NONE}; + enum AVPixelFormat out_formats[2]; + SDR2HDRContext* ctx = context->priv; + AVFilterFormats* formats_list; + int ret = 0; + + formats_list = ff_make_format_list(in_formats); + if ((ret = ff_formats_ref(formats_list, &context->inputs[0]->out_formats)) < 0) + return ret; + + out_formats[0] = ctx->out_fmt; + out_formats[1] = AV_PIX_FMT_NONE; + formats_list = ff_make_format_list(out_formats); + if ((ret = ff_formats_ref(formats_list, &context->outputs[0]->in_formats)) < 0) + return ret; + + return 0; +} + +static int config_props(AVFilterLink* inlink) +{ + AVFilterContext* context = inlink->dst; + SDR2HDRContext* ctx = context->priv; + AVFilterLink* outlink = context->outputs[0]; + DNNReturnType result; + + // the dnn model is tied with resolution due to deconv layer of tensorflow + // now just support 1920*1080 and so the magic numbers within this file + if (inlink->w != 1920 || inlink->h != 1080) { + av_log(context, AV_LOG_ERROR, "only support frame size with 1920*1080\n"); + return AVERROR(ENOSYS); + } + + ctx->input.width = 1920; + ctx->input.height = 1088; //the model requires height is a multiple of 32, + ctx->input.channels = 3; + + result = (ctx->model->set_input_output)(ctx->model->model, &ctx->input, &ctx->output); + if (result != DNN_SUCCESS){ + av_log(context, AV_LOG_ERROR, "could not set input and output for the model\n"); + return AVERROR(EIO); + } + + memset(ctx->input.data, 0, ctx->input.channels * ctx->input.width * ctx->input.height * sizeof(float)); + outlink->h = 1080; + outlink->w = 1920; + return 0; +} + +static float qsort_comparison_function_float(const void *a, const void *b) +{ + return *(const float *)a - *(const float *)b; +} + +static int filter_frame(AVFilterLink* inlink, AVFrame* in) +{ + DNNReturnType dnn_result = DNN_SUCCESS; + AVFilterContext* context = inlink->dst; + SDR2HDRContext* ctx = context->priv; + AVFilterLink* outlink = context->outputs[0]; + AVFrame* out = ff_get_video_buffer(outlink, outlink->w, outlink->h); + int total_pixels = in->height * in->width; + + av_frame_copy_props(out, in); + + for (int i = 0; i < in->linesize[0] * in->height; ++i) { + ctx->input.data[i] = in->data[0][i] / 255.0f; + } + + dnn_result = (ctx->dnn_module->execute_model)(ctx->model); + if (dnn_result != DNN_SUCCESS){ + av_log(context, AV_LOG_ERROR, "failed to execute loaded model\n"); + return AVERROR(EIO); + } + + if (ctx->out_fmt == AV_PIX_FMT_GBRPF32LE) { + float* outg = (float*)out->data[0]; + float* outb = (float*)out->data[1]; + float* outr = (float*)out->data[2]; + for (int i = 0; i < total_pixels; ++i) { + float r = ctx->output.data[i*3]; + float g = ctx->output.data[i*3+1]; + float b = ctx->output.data[i*3+2]; + outr[i] = r; + outg[i] = g; + outb[i] = b; + } + } else { + // here, we just use a rough mapping to the 10bit contents + // meta data generation for HDR video encoding is not supported yet + float* converted_data = (float*)malloc(total_pixels * 3 * sizeof(float)); + int16_t* outg = (int16_t*)out->data[0]; + int16_t* outb = (int16_t*)out->data[1]; + int16_t* outr = (int16_t*)out->data[2]; + + float max = 1.0f; + for (int i = 0; i < total_pixels * 3; ++i) { + float d = ctx->output.data[i]; + d = sqrt(d); + converted_data[i] = d; + max = FFMAX(d, max); + } + + if (max > 1.0f) { + AV_QSORT(converted_data, total_pixels * 3, float, qsort_comparison_function_float); + // 0.5% pixels are clipped + max = converted_data[(int)(total_pixels * 3 * 0.995)]; + max = FFMAX(max, 1.0f); + + for (int i = 0; i < total_pixels * 3; ++i) { + float d = ctx->output.data[i]; + d = sqrt(d); + d = FFMIN(d, max); + converted_data[i] = d; + } + } + + for (int i = 0; i < total_pixels; ++i) { + float r = converted_data[i*3]; + float g = converted_data[i*3+1]; + float b = converted_data[i*3+2]; + outr[i] = r / max * 1023; + outg[i] = g / max * 1023; + outb[i] = b / max * 1023; + } + + free(converted_data); + } + + av_frame_free(&in); + return ff_filter_frame(outlink, out); +} + +static av_cold void uninit(AVFilterContext* context) +{ + SDR2HDRContext* ctx = context->priv; + + if (ctx->dnn_module){ + (ctx->dnn_module->free_model)(&ctx->model); + av_freep(&ctx->dnn_module); + } +} + +static const AVFilterPad sdr2hdr_inputs[] = { + { + .name = "default", + .type = AVMEDIA_TYPE_VIDEO, + .config_props = config_props, + .filter_frame = filter_frame, + }, + { NULL } +}; + +static const AVFilterPad sdr2hdr_outputs[] = { + { + .name = "default", + .type = AVMEDIA_TYPE_VIDEO, + }, + { NULL } +}; + +AVFilter ff_vf_sdr2hdr = { + .name = "sdr2hdr", + .description = NULL_IF_CONFIG_SMALL("HDR image reconstruction from a single exposure using deep CNNs."), + .priv_size = sizeof(SDR2HDRContext), + .init = init, + .uninit = uninit, + .query_formats = query_formats, + .inputs = sdr2hdr_inputs, + .outputs = sdr2hdr_outputs, + .priv_class = &sdr2hdr_class, + .flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC, +};