libavfilter/vf_dnn_processing.c - third_party/ffmpeg - Git at Google

 /*
  * Copyright (c) 2019 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
  * implementing a generic image processing filter using deep learning networks.
  */

 #include "libavformat/avio.h"
 #include "libavutil/opt.h"
 #include "libavutil/pixdesc.h"
 #include "libavutil/avassert.h"
 #include "libavutil/imgutils.h"
 #include "avfilter.h"
 #include "dnn_interface.h"
 #include "formats.h"
 #include "internal.h"
 #include "libswscale/swscale.h"

 typedef struct DnnProcessingContext {
     const AVClass *class;

     char *model_filename;
     DNNBackendType backend_type;
     char *model_inputname;
     char *model_outputname;

     DNNModule *dnn_module;
     DNNModel *model;

     // input & output of the model at execution time
     DNNData input;
     DNNData output;

     struct SwsContext *sws_gray8_to_grayf32;
     struct SwsContext *sws_grayf32_to_gray8;
     struct SwsContext *sws_uv_scale;
     int sws_uv_height;
 } DnnProcessingContext;

 #define OFFSET(x) offsetof(DnnProcessingContext, x)
 #define FLAGS AV_OPT_FLAG_FILTERING_PARAM | AV_OPT_FLAG_VIDEO_PARAM
 static const AVOption dnn_processing_options[] = {
     { "dnn_backend", "DNN backend",                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
     { "model",       "path to model file",         OFFSET(model_filename),   AV_OPT_TYPE_STRING,    { .str = NULL }, 0, 0, FLAGS },
     { "input",       "input name of the model",    OFFSET(model_inputname),  AV_OPT_TYPE_STRING,    { .str = NULL }, 0, 0, FLAGS },
     { "output",      "output name of the model",   OFFSET(model_outputname), AV_OPT_TYPE_STRING,    { .str = NULL }, 0, 0, FLAGS },
     { NULL }
 };

 AVFILTER_DEFINE_CLASS(dnn_processing);

 static av_cold int init(AVFilterContext *context)
 {
     DnnProcessingContext *ctx = context->priv;

     if (!ctx->model_filename) {
         av_log(ctx, AV_LOG_ERROR, "model file for network is not specified\n");
         return AVERROR(EINVAL);
     }
     if (!ctx->model_inputname) {
         av_log(ctx, AV_LOG_ERROR, "input name of the model network is not specified\n");
         return AVERROR(EINVAL);
     }
     if (!ctx->model_outputname) {
         av_log(ctx, AV_LOG_ERROR, "output name of the model network is not specified\n");
         return AVERROR(EINVAL);
     }

     ctx->dnn_module = ff_get_dnn_module(ctx->backend_type);
     if (!ctx->dnn_module) {
         av_log(ctx, AV_LOG_ERROR, "could not create DNN module for requested backend\n");
         return AVERROR(ENOMEM);
     }
     if (!ctx->dnn_module->load_model) {
         av_log(ctx, AV_LOG_ERROR, "load_model for network is not specified\n");
         return AVERROR(EINVAL);
     }

     ctx->model = (ctx->dnn_module->load_model)(ctx->model_filename);
     if (!ctx->model) {
         av_log(ctx, AV_LOG_ERROR, "could not load DNN model\n");
         return AVERROR(EINVAL);
     }

     return 0;
 }

 static int query_formats(AVFilterContext *context)
 {
     static const enum AVPixelFormat pix_fmts[] = {
         AV_PIX_FMT_RGB24, AV_PIX_FMT_BGR24,
         AV_PIX_FMT_GRAY8, AV_PIX_FMT_GRAYF32,
         AV_PIX_FMT_YUV420P, AV_PIX_FMT_YUV422P,
         AV_PIX_FMT_YUV444P, AV_PIX_FMT_YUV410P, AV_PIX_FMT_YUV411P,
         AV_PIX_FMT_NONE
     };
     AVFilterFormats *fmts_list = ff_make_format_list(pix_fmts);
     return ff_set_common_formats(context, fmts_list);
 }

 #define LOG_FORMAT_CHANNEL_MISMATCH()                       \
     av_log(ctx, AV_LOG_ERROR,                               \
            "the frame's format %s does not match "          \
            "the model input channel %d\n",                  \
            av_get_pix_fmt_name(fmt),                        \
            model_input->channels);

 static int check_modelinput_inlink(const DNNData *model_input, const AVFilterLink *inlink)
 {
     AVFilterContext *ctx   = inlink->dst;
     enum AVPixelFormat fmt = inlink->format;

     // the design is to add explicit scale filter before this filter
     if (model_input->height != -1 && model_input->height != inlink->h) {
         av_log(ctx, AV_LOG_ERROR, "the model requires frame height %d but got %d\n",
                                    model_input->height, inlink->h);
         return AVERROR(EIO);
     }
     if (model_input->width != -1 && model_input->width != inlink->w) {
         av_log(ctx, AV_LOG_ERROR, "the model requires frame width %d but got %d\n",
                                    model_input->width, inlink->w);
         return AVERROR(EIO);
     }

     switch (fmt) {
     case AV_PIX_FMT_RGB24:
     case AV_PIX_FMT_BGR24:
         if (model_input->channels != 3) {
             LOG_FORMAT_CHANNEL_MISMATCH();
             return AVERROR(EIO);
         }
         if (model_input->dt != DNN_FLOAT && model_input->dt != DNN_UINT8) {
             av_log(ctx, AV_LOG_ERROR, "only support dnn models with input data type as float32 and uint8.\n");
             return AVERROR(EIO);
         }
         return 0;
     case AV_PIX_FMT_GRAY8:
         if (model_input->channels != 1) {
             LOG_FORMAT_CHANNEL_MISMATCH();
             return AVERROR(EIO);
         }
         if (model_input->dt != DNN_UINT8) {
             av_log(ctx, AV_LOG_ERROR, "only support dnn models with input data type uint8.\n");
             return AVERROR(EIO);
         }
         return 0;
     case AV_PIX_FMT_GRAYF32:
     case AV_PIX_FMT_YUV420P:
     case AV_PIX_FMT_YUV422P:
     case AV_PIX_FMT_YUV444P:
     case AV_PIX_FMT_YUV410P:
     case AV_PIX_FMT_YUV411P:
         if (model_input->channels != 1) {
             LOG_FORMAT_CHANNEL_MISMATCH();
             return AVERROR(EIO);
         }
         if (model_input->dt != DNN_FLOAT) {
             av_log(ctx, AV_LOG_ERROR, "only support dnn models with input data type float32.\n");
             return AVERROR(EIO);
         }
         return 0;
     default:
         av_log(ctx, AV_LOG_ERROR, "%s not supported.\n", av_get_pix_fmt_name(fmt));
         return AVERROR(EIO);
     }

     return 0;
 }

 static int config_input(AVFilterLink *inlink)
 {
     AVFilterContext *context     = inlink->dst;
     DnnProcessingContext *ctx = context->priv;
     DNNReturnType result;
     DNNData model_input;
     int check;

     result = ctx->model->get_input(ctx->model->model, &model_input, ctx->model_inputname);
     if (result != DNN_SUCCESS) {
         av_log(ctx, AV_LOG_ERROR, "could not get input from the model\n");
         return AVERROR(EIO);
     }

     check = check_modelinput_inlink(&model_input, inlink);
     if (check != 0) {
         return check;
     }

     ctx->input.width    = inlink->w;
     ctx->input.height   = inlink->h;
     ctx->input.channels = model_input.channels;
     ctx->input.dt = model_input.dt;

     result = (ctx->model->set_input_output)(ctx->model->model,
                                         &ctx->input, ctx->model_inputname,
                                         (const char **)&ctx->model_outputname, 1);
     if (result != DNN_SUCCESS) {
         av_log(ctx, AV_LOG_ERROR, "could not set input and output for the model\n");
         return AVERROR(EIO);
     }

     return 0;
 }

 static int prepare_sws_context(AVFilterLink *outlink)
 {
     AVFilterContext *context = outlink->src;
     DnnProcessingContext *ctx = context->priv;
     AVFilterLink *inlink = context->inputs[0];
     enum AVPixelFormat fmt = inlink->format;
     DNNDataType input_dt  = ctx->input.dt;
     DNNDataType output_dt = ctx->output.dt;

     switch (fmt) {
     case AV_PIX_FMT_RGB24:
     case AV_PIX_FMT_BGR24:
         if (input_dt == DNN_FLOAT) {
             ctx->sws_gray8_to_grayf32 = sws_getContext(inlink->w * 3,
                                                        inlink->h,
                                                        AV_PIX_FMT_GRAY8,
                                                        inlink->w * 3,
                                                        inlink->h,
                                                        AV_PIX_FMT_GRAYF32,
                                                        0, NULL, NULL, NULL);
         }
         if (output_dt == DNN_FLOAT) {
             ctx->sws_grayf32_to_gray8 = sws_getContext(outlink->w * 3,
                                                        outlink->h,
                                                        AV_PIX_FMT_GRAYF32,
                                                        outlink->w * 3,
                                                        outlink->h,
                                                        AV_PIX_FMT_GRAY8,
                                                        0, NULL, NULL, NULL);
         }
         return 0;
     case AV_PIX_FMT_YUV420P:
     case AV_PIX_FMT_YUV422P:
     case AV_PIX_FMT_YUV444P:
     case AV_PIX_FMT_YUV410P:
     case AV_PIX_FMT_YUV411P:
         av_assert0(input_dt == DNN_FLOAT);
         av_assert0(output_dt == DNN_FLOAT);
         ctx->sws_gray8_to_grayf32 = sws_getContext(inlink->w,
                                                    inlink->h,
                                                    AV_PIX_FMT_GRAY8,
                                                    inlink->w,
                                                    inlink->h,
                                                    AV_PIX_FMT_GRAYF32,
                                                    0, NULL, NULL, NULL);
         ctx->sws_grayf32_to_gray8 = sws_getContext(outlink->w,
                                                    outlink->h,
                                                    AV_PIX_FMT_GRAYF32,
                                                    outlink->w,
                                                    outlink->h,
                                                    AV_PIX_FMT_GRAY8,
                                                    0, NULL, NULL, NULL);

         if (inlink->w != outlink->w || inlink->h != outlink->h) {
             const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(fmt);
             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;
         }
         return 0;
     default:
         //do nothing
         break;
     }

     return 0;
 }

 static int config_output(AVFilterLink *outlink)
 {
     AVFilterContext *context = outlink->src;
     DnnProcessingContext *ctx = context->priv;
     DNNReturnType result;

     // have a try run in case that the dnn model resize the frame
     result = (ctx->dnn_module->execute_model)(ctx->model, &ctx->output, 1);
     if (result != DNN_SUCCESS){
         av_log(ctx, AV_LOG_ERROR, "failed to execute model\n");
         return AVERROR(EIO);
     }

     outlink->w = ctx->output.width;
     outlink->h = ctx->output.height;

     prepare_sws_context(outlink);

     return 0;
 }

 static int copy_from_frame_to_dnn(DnnProcessingContext *ctx, const AVFrame *frame)
 {
     int bytewidth = av_image_get_linesize(frame->format, frame->width, 0);
     DNNData *dnn_input = &ctx->input;

     switch (frame->format) {
     case AV_PIX_FMT_RGB24:
     case AV_PIX_FMT_BGR24:
         if (dnn_input->dt == DNN_FLOAT) {
             sws_scale(ctx->sws_gray8_to_grayf32, (const uint8_t **)frame->data, frame->linesize,
                       0, frame->height, (uint8_t * const*)(&dnn_input->data),
                       (const int [4]){frame->width * 3 * sizeof(float), 0, 0, 0});
         } else {
             av_assert0(dnn_input->dt == DNN_UINT8);
             av_image_copy_plane(dnn_input->data, bytewidth,
                                 frame->data[0], frame->linesize[0],
                                 bytewidth, frame->height);
         }
         return 0;
     case AV_PIX_FMT_GRAY8:
     case AV_PIX_FMT_GRAYF32:
         av_image_copy_plane(dnn_input->data, bytewidth,
                             frame->data[0], frame->linesize[0],
                             bytewidth, frame->height);
         return 0;
     case AV_PIX_FMT_YUV420P:
     case AV_PIX_FMT_YUV422P:
     case AV_PIX_FMT_YUV444P:
     case AV_PIX_FMT_YUV410P:
     case AV_PIX_FMT_YUV411P:
         sws_scale(ctx->sws_gray8_to_grayf32, (const uint8_t **)frame->data, frame->linesize,
                   0, frame->height, (uint8_t * const*)(&dnn_input->data),
                   (const int [4]){frame->width * sizeof(float), 0, 0, 0});
         return 0;
     default:
         return AVERROR(EIO);
     }

     return 0;
 }

 static int copy_from_dnn_to_frame(DnnProcessingContext *ctx, AVFrame *frame)
 {
     int bytewidth = av_image_get_linesize(frame->format, frame->width, 0);
     DNNData *dnn_output = &ctx->output;

     switch (frame->format) {
     case AV_PIX_FMT_RGB24:
     case AV_PIX_FMT_BGR24:
         if (dnn_output->dt == DNN_FLOAT) {
             sws_scale(ctx->sws_grayf32_to_gray8, (const uint8_t *[4]){(const uint8_t *)dnn_output->data, 0, 0, 0},
                       (const int[4]){frame->width * 3 * sizeof(float), 0, 0, 0},
                       0, frame->height, (uint8_t * const*)frame->data, frame->linesize);

         } else {
             av_assert0(dnn_output->dt == DNN_UINT8);
             av_image_copy_plane(frame->data[0], frame->linesize[0],
                                 dnn_output->data, bytewidth,
                                 bytewidth, frame->height);
         }
         return 0;
     case AV_PIX_FMT_GRAY8:
         // it is possible that data type of dnn output is float32,
         // need to add support for such case when needed.
         av_assert0(dnn_output->dt == DNN_UINT8);
         av_image_copy_plane(frame->data[0], frame->linesize[0],
                             dnn_output->data, bytewidth,
                             bytewidth, frame->height);
         return 0;
     case AV_PIX_FMT_GRAYF32:
         av_assert0(dnn_output->dt == DNN_FLOAT);
         av_image_copy_plane(frame->data[0], frame->linesize[0],
                             dnn_output->data, bytewidth,
                             bytewidth, frame->height);
         return 0;
     case AV_PIX_FMT_YUV420P:
     case AV_PIX_FMT_YUV422P:
     case AV_PIX_FMT_YUV444P:
     case AV_PIX_FMT_YUV410P:
     case AV_PIX_FMT_YUV411P:
         sws_scale(ctx->sws_grayf32_to_gray8, (const uint8_t *[4]){(const uint8_t *)dnn_output->data, 0, 0, 0},
                   (const int[4]){frame->width * sizeof(float), 0, 0, 0},
                   0, frame->height, (uint8_t * const*)frame->data, frame->linesize);
         return 0;
     default:
         return AVERROR(EIO);
     }

     return 0;
 }

 static av_always_inline int isPlanarYUV(enum AVPixelFormat pix_fmt)
 {
     const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(pix_fmt);
     av_assert0(desc);
     return !(desc->flags & AV_PIX_FMT_FLAG_RGB) && desc->nb_components == 3;
 }

 static int copy_uv_planes(DnnProcessingContext *ctx, AVFrame *out, const AVFrame *in)
 {
     const AVPixFmtDescriptor *desc;
     int uv_height;

     if (!ctx->sws_uv_scale) {
         av_assert0(in->height == out->height && in->width == out->width);
         desc = av_pix_fmt_desc_get(in->format);
         uv_height = AV_CEIL_RSHIFT(in->height, desc->log2_chroma_h);
         for (int i = 1; i < 3; ++i) {
             int bytewidth = av_image_get_linesize(in->format, in->width, i);
             av_image_copy_plane(out->data[i], out->linesize[i],
                                 in->data[i], in->linesize[i],
                                 bytewidth, uv_height);
         }
     } else {
         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);
     }

     return 0;
 }

 static int filter_frame(AVFilterLink *inlink, AVFrame *in)
 {
     AVFilterContext *context  = inlink->dst;
     AVFilterLink *outlink = context->outputs[0];
     DnnProcessingContext *ctx = context->priv;
     DNNReturnType dnn_result;
     AVFrame *out;

     copy_from_frame_to_dnn(ctx, in);

     dnn_result = (ctx->dnn_module->execute_model)(ctx->model, &ctx->output, 1);
     if (dnn_result != DNN_SUCCESS){
         av_log(ctx, AV_LOG_ERROR, "failed to execute model\n");
         av_frame_free(&in);
         return AVERROR(EIO);
     }

     out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
     if (!out) {
         av_frame_free(&in);
         return AVERROR(ENOMEM);
     }

     av_frame_copy_props(out, in);
     copy_from_dnn_to_frame(ctx, out);

     if (isPlanarYUV(in->format))
         copy_uv_planes(ctx, out, in);

     av_frame_free(&in);
     return ff_filter_frame(outlink, out);
 }

 static av_cold void uninit(AVFilterContext *ctx)
 {
     DnnProcessingContext *context = ctx->priv;

     sws_freeContext(context->sws_gray8_to_grayf32);
     sws_freeContext(context->sws_grayf32_to_gray8);
     sws_freeContext(context->sws_uv_scale);

     if (context->dnn_module)
         (context->dnn_module->free_model)(&context->model);

     av_freep(&context->dnn_module);
 }

 static const AVFilterPad dnn_processing_inputs[] = {
     {
         .name         = "default",
         .type         = AVMEDIA_TYPE_VIDEO,
         .config_props = config_input,
         .filter_frame = filter_frame,
     },
     { NULL }
 };

 static const AVFilterPad dnn_processing_outputs[] = {
     {
         .name = "default",
         .type = AVMEDIA_TYPE_VIDEO,
         .config_props  = config_output,
     },
     { NULL }
 };

 AVFilter ff_vf_dnn_processing = {
     .name          = "dnn_processing",
     .description   = NULL_IF_CONFIG_SMALL("Apply DNN processing filter to the input."),
     .priv_size     = sizeof(DnnProcessingContext),
     .init          = init,
     .uninit        = uninit,
     .query_formats = query_formats,
     .inputs        = dnn_processing_inputs,
     .outputs       = dnn_processing_outputs,
     .priv_class    = &dnn_processing_class,
 };
	/*
	* Copyright (c) 2019 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
	* implementing a generic image processing filter using deep learning networks.
	*/

	#include "libavformat/avio.h"
	#include "libavutil/opt.h"
	#include "libavutil/pixdesc.h"
	#include "libavutil/avassert.h"
	#include "libavutil/imgutils.h"
	#include "avfilter.h"
	#include "dnn_interface.h"
	#include "formats.h"
	#include "internal.h"
	#include "libswscale/swscale.h"

	typedef struct DnnProcessingContext {
	const AVClass *class;

	char *model_filename;
	DNNBackendType backend_type;
	char *model_inputname;
	char *model_outputname;

	DNNModule *dnn_module;
	DNNModel *model;

	// input & output of the model at execution time
	DNNData input;
	DNNData output;

	struct SwsContext *sws_gray8_to_grayf32;
	struct SwsContext *sws_grayf32_to_gray8;
	struct SwsContext *sws_uv_scale;
	int sws_uv_height;
	} DnnProcessingContext;

	#define OFFSET(x) offsetof(DnnProcessingContext, x)
	#define FLAGS AV_OPT_FLAG_FILTERING_PARAM \| AV_OPT_FLAG_VIDEO_PARAM
	static const AVOption dnn_processing_options[] = {
	{ "dnn_backend", "DNN backend", 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
	{ "model", "path to model file", OFFSET(model_filename), AV_OPT_TYPE_STRING, { .str = NULL }, 0, 0, FLAGS },
	{ "input", "input name of the model", OFFSET(model_inputname), AV_OPT_TYPE_STRING, { .str = NULL }, 0, 0, FLAGS },
	{ "output", "output name of the model", OFFSET(model_outputname), AV_OPT_TYPE_STRING, { .str = NULL }, 0, 0, FLAGS },
	{ NULL }
	};

	AVFILTER_DEFINE_CLASS(dnn_processing);

	static av_cold int init(AVFilterContext *context)
	{
	DnnProcessingContext *ctx = context->priv;

	if (!ctx->model_filename) {
	av_log(ctx, AV_LOG_ERROR, "model file for network is not specified\n");
	return AVERROR(EINVAL);
	}
	if (!ctx->model_inputname) {
	av_log(ctx, AV_LOG_ERROR, "input name of the model network is not specified\n");
	return AVERROR(EINVAL);
	}
	if (!ctx->model_outputname) {
	av_log(ctx, AV_LOG_ERROR, "output name of the model network is not specified\n");
	return AVERROR(EINVAL);
	}

	ctx->dnn_module = ff_get_dnn_module(ctx->backend_type);
	if (!ctx->dnn_module) {
	av_log(ctx, AV_LOG_ERROR, "could not create DNN module for requested backend\n");
	return AVERROR(ENOMEM);
	}
	if (!ctx->dnn_module->load_model) {
	av_log(ctx, AV_LOG_ERROR, "load_model for network is not specified\n");
	return AVERROR(EINVAL);
	}

	ctx->model = (ctx->dnn_module->load_model)(ctx->model_filename);
	if (!ctx->model) {
	av_log(ctx, AV_LOG_ERROR, "could not load DNN model\n");
	return AVERROR(EINVAL);
	}

	return 0;
	}

	static int query_formats(AVFilterContext *context)
	{
	static const enum AVPixelFormat pix_fmts[] = {
	AV_PIX_FMT_RGB24, AV_PIX_FMT_BGR24,
	AV_PIX_FMT_GRAY8, AV_PIX_FMT_GRAYF32,
	AV_PIX_FMT_YUV420P, AV_PIX_FMT_YUV422P,
	AV_PIX_FMT_YUV444P, AV_PIX_FMT_YUV410P, AV_PIX_FMT_YUV411P,
	AV_PIX_FMT_NONE
	};
	AVFilterFormats *fmts_list = ff_make_format_list(pix_fmts);
	return ff_set_common_formats(context, fmts_list);
	}

	#define LOG_FORMAT_CHANNEL_MISMATCH() \
	av_log(ctx, AV_LOG_ERROR, \
	"the frame's format %s does not match " \
	"the model input channel %d\n", \
	av_get_pix_fmt_name(fmt), \
	model_input->channels);

	static int check_modelinput_inlink(const DNNData model_input, const AVFilterLink inlink)
	{
	AVFilterContext *ctx = inlink->dst;
	enum AVPixelFormat fmt = inlink->format;

	// the design is to add explicit scale filter before this filter
	if (model_input->height != -1 && model_input->height != inlink->h) {
	av_log(ctx, AV_LOG_ERROR, "the model requires frame height %d but got %d\n",
	model_input->height, inlink->h);
	return AVERROR(EIO);
	}
	if (model_input->width != -1 && model_input->width != inlink->w) {
	av_log(ctx, AV_LOG_ERROR, "the model requires frame width %d but got %d\n",
	model_input->width, inlink->w);
	return AVERROR(EIO);
	}

	switch (fmt) {
	case AV_PIX_FMT_RGB24:
	case AV_PIX_FMT_BGR24:
	if (model_input->channels != 3) {
	LOG_FORMAT_CHANNEL_MISMATCH();
	return AVERROR(EIO);
	}
	if (model_input->dt != DNN_FLOAT && model_input->dt != DNN_UINT8) {
	av_log(ctx, AV_LOG_ERROR, "only support dnn models with input data type as float32 and uint8.\n");
	return AVERROR(EIO);
	}
	return 0;
	case AV_PIX_FMT_GRAY8:
	if (model_input->channels != 1) {
	LOG_FORMAT_CHANNEL_MISMATCH();
	return AVERROR(EIO);
	}
	if (model_input->dt != DNN_UINT8) {
	av_log(ctx, AV_LOG_ERROR, "only support dnn models with input data type uint8.\n");
	return AVERROR(EIO);
	}
	return 0;
	case AV_PIX_FMT_GRAYF32:
	case AV_PIX_FMT_YUV420P:
	case AV_PIX_FMT_YUV422P:
	case AV_PIX_FMT_YUV444P:
	case AV_PIX_FMT_YUV410P:
	case AV_PIX_FMT_YUV411P:
	if (model_input->channels != 1) {
	LOG_FORMAT_CHANNEL_MISMATCH();
	return AVERROR(EIO);
	}
	if (model_input->dt != DNN_FLOAT) {
	av_log(ctx, AV_LOG_ERROR, "only support dnn models with input data type float32.\n");
	return AVERROR(EIO);
	}
	return 0;
	default:
	av_log(ctx, AV_LOG_ERROR, "%s not supported.\n", av_get_pix_fmt_name(fmt));
	return AVERROR(EIO);
	}

	return 0;
	}

	static int config_input(AVFilterLink *inlink)
	{
	AVFilterContext *context = inlink->dst;
	DnnProcessingContext *ctx = context->priv;
	DNNReturnType result;
	DNNData model_input;
	int check;

	result = ctx->model->get_input(ctx->model->model, &model_input, ctx->model_inputname);
	if (result != DNN_SUCCESS) {
	av_log(ctx, AV_LOG_ERROR, "could not get input from the model\n");
	return AVERROR(EIO);
	}

	check = check_modelinput_inlink(&model_input, inlink);
	if (check != 0) {
	return check;
	}

	ctx->input.width = inlink->w;
	ctx->input.height = inlink->h;
	ctx->input.channels = model_input.channels;
	ctx->input.dt = model_input.dt;

	result = (ctx->model->set_input_output)(ctx->model->model,
	&ctx->input, ctx->model_inputname,
	(const char **)&ctx->model_outputname, 1);
	if (result != DNN_SUCCESS) {
	av_log(ctx, AV_LOG_ERROR, "could not set input and output for the model\n");
	return AVERROR(EIO);
	}

	return 0;
	}

	static int prepare_sws_context(AVFilterLink *outlink)
	{
	AVFilterContext *context = outlink->src;
	DnnProcessingContext *ctx = context->priv;
	AVFilterLink *inlink = context->inputs[0];
	enum AVPixelFormat fmt = inlink->format;
	DNNDataType input_dt = ctx->input.dt;
	DNNDataType output_dt = ctx->output.dt;

	switch (fmt) {
	case AV_PIX_FMT_RGB24:
	case AV_PIX_FMT_BGR24:
	if (input_dt == DNN_FLOAT) {
	ctx->sws_gray8_to_grayf32 = sws_getContext(inlink->w * 3,
	inlink->h,
	AV_PIX_FMT_GRAY8,
	inlink->w * 3,
	inlink->h,
	AV_PIX_FMT_GRAYF32,
	0, NULL, NULL, NULL);
	}
	if (output_dt == DNN_FLOAT) {
	ctx->sws_grayf32_to_gray8 = sws_getContext(outlink->w * 3,
	outlink->h,
	AV_PIX_FMT_GRAYF32,
	outlink->w * 3,
	outlink->h,
	AV_PIX_FMT_GRAY8,
	0, NULL, NULL, NULL);
	}
	return 0;
	case AV_PIX_FMT_YUV420P:
	case AV_PIX_FMT_YUV422P:
	case AV_PIX_FMT_YUV444P:
	case AV_PIX_FMT_YUV410P:
	case AV_PIX_FMT_YUV411P:
	av_assert0(input_dt == DNN_FLOAT);
	av_assert0(output_dt == DNN_FLOAT);
	ctx->sws_gray8_to_grayf32 = sws_getContext(inlink->w,
	inlink->h,
	AV_PIX_FMT_GRAY8,
	inlink->w,
	inlink->h,
	AV_PIX_FMT_GRAYF32,
	0, NULL, NULL, NULL);
	ctx->sws_grayf32_to_gray8 = sws_getContext(outlink->w,
	outlink->h,
	AV_PIX_FMT_GRAYF32,
	outlink->w,
	outlink->h,
	AV_PIX_FMT_GRAY8,
	0, NULL, NULL, NULL);

	if (inlink->w != outlink->w \|\| inlink->h != outlink->h) {
	const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(fmt);
	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;
	}
	return 0;
	default:
	//do nothing
	break;
	}

	return 0;
	}

	static int config_output(AVFilterLink *outlink)
	{
	AVFilterContext *context = outlink->src;
	DnnProcessingContext *ctx = context->priv;
	DNNReturnType result;

	// have a try run in case that the dnn model resize the frame
	result = (ctx->dnn_module->execute_model)(ctx->model, &ctx->output, 1);
	if (result != DNN_SUCCESS){
	av_log(ctx, AV_LOG_ERROR, "failed to execute model\n");
	return AVERROR(EIO);
	}

	outlink->w = ctx->output.width;
	outlink->h = ctx->output.height;

	prepare_sws_context(outlink);

	return 0;
	}

	static int copy_from_frame_to_dnn(DnnProcessingContext ctx, const AVFrame frame)
	{
	int bytewidth = av_image_get_linesize(frame->format, frame->width, 0);
	DNNData *dnn_input = &ctx->input;

	switch (frame->format) {
	case AV_PIX_FMT_RGB24:
	case AV_PIX_FMT_BGR24:
	if (dnn_input->dt == DNN_FLOAT) {
	sws_scale(ctx->sws_gray8_to_grayf32, (const uint8_t **)frame->data, frame->linesize,
	0, frame->height, (uint8_t * const*)(&dnn_input->data),
	(const int [4]){frame->width * 3 * sizeof(float), 0, 0, 0});
	} else {
	av_assert0(dnn_input->dt == DNN_UINT8);
	av_image_copy_plane(dnn_input->data, bytewidth,
	frame->data[0], frame->linesize[0],
	bytewidth, frame->height);
	}
	return 0;
	case AV_PIX_FMT_GRAY8:
	case AV_PIX_FMT_GRAYF32:
	av_image_copy_plane(dnn_input->data, bytewidth,
	frame->data[0], frame->linesize[0],
	bytewidth, frame->height);
	return 0;
	case AV_PIX_FMT_YUV420P:
	case AV_PIX_FMT_YUV422P:
	case AV_PIX_FMT_YUV444P:
	case AV_PIX_FMT_YUV410P:
	case AV_PIX_FMT_YUV411P:
	sws_scale(ctx->sws_gray8_to_grayf32, (const uint8_t **)frame->data, frame->linesize,
	0, frame->height, (uint8_t * const*)(&dnn_input->data),
	(const int [4]){frame->width * sizeof(float), 0, 0, 0});
	return 0;
	default:
	return AVERROR(EIO);
	}

	return 0;
	}

	static int copy_from_dnn_to_frame(DnnProcessingContext ctx, AVFrame frame)
	{
	int bytewidth = av_image_get_linesize(frame->format, frame->width, 0);
	DNNData *dnn_output = &ctx->output;

	switch (frame->format) {
	case AV_PIX_FMT_RGB24:
	case AV_PIX_FMT_BGR24:
	if (dnn_output->dt == DNN_FLOAT) {
	sws_scale(ctx->sws_grayf32_to_gray8, (const uint8_t [4]){(const uint8_t )dnn_output->data, 0, 0, 0},
	(const int[4]){frame->width * 3 * sizeof(float), 0, 0, 0},
	0, frame->height, (uint8_t * const*)frame->data, frame->linesize);

	} else {
	av_assert0(dnn_output->dt == DNN_UINT8);
	av_image_copy_plane(frame->data[0], frame->linesize[0],
	dnn_output->data, bytewidth,
	bytewidth, frame->height);
	}
	return 0;
	case AV_PIX_FMT_GRAY8:
	// it is possible that data type of dnn output is float32,
	// need to add support for such case when needed.
	av_assert0(dnn_output->dt == DNN_UINT8);
	av_image_copy_plane(frame->data[0], frame->linesize[0],
	dnn_output->data, bytewidth,
	bytewidth, frame->height);
	return 0;
	case AV_PIX_FMT_GRAYF32:
	av_assert0(dnn_output->dt == DNN_FLOAT);
	av_image_copy_plane(frame->data[0], frame->linesize[0],
	dnn_output->data, bytewidth,
	bytewidth, frame->height);
	return 0;
	case AV_PIX_FMT_YUV420P:
	case AV_PIX_FMT_YUV422P:
	case AV_PIX_FMT_YUV444P:
	case AV_PIX_FMT_YUV410P:
	case AV_PIX_FMT_YUV411P:
	sws_scale(ctx->sws_grayf32_to_gray8, (const uint8_t [4]){(const uint8_t )dnn_output->data, 0, 0, 0},
	(const int[4]){frame->width * sizeof(float), 0, 0, 0},
	0, frame->height, (uint8_t * const*)frame->data, frame->linesize);
	return 0;
	default:
	return AVERROR(EIO);
	}

	return 0;
	}

	static av_always_inline int isPlanarYUV(enum AVPixelFormat pix_fmt)
	{
	const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(pix_fmt);
	av_assert0(desc);
	return !(desc->flags & AV_PIX_FMT_FLAG_RGB) && desc->nb_components == 3;
	}

	static int copy_uv_planes(DnnProcessingContext ctx, AVFrame out, const AVFrame *in)
	{
	const AVPixFmtDescriptor *desc;
	int uv_height;

	if (!ctx->sws_uv_scale) {
	av_assert0(in->height == out->height && in->width == out->width);
	desc = av_pix_fmt_desc_get(in->format);
	uv_height = AV_CEIL_RSHIFT(in->height, desc->log2_chroma_h);
	for (int i = 1; i < 3; ++i) {
	int bytewidth = av_image_get_linesize(in->format, in->width, i);
	av_image_copy_plane(out->data[i], out->linesize[i],
	in->data[i], in->linesize[i],
	bytewidth, uv_height);
	}
	} else {
	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);
	}

	return 0;
	}

	static int filter_frame(AVFilterLink inlink, AVFrame in)
	{
	AVFilterContext *context = inlink->dst;
	AVFilterLink *outlink = context->outputs[0];
	DnnProcessingContext *ctx = context->priv;
	DNNReturnType dnn_result;
	AVFrame *out;

	copy_from_frame_to_dnn(ctx, in);

	dnn_result = (ctx->dnn_module->execute_model)(ctx->model, &ctx->output, 1);
	if (dnn_result != DNN_SUCCESS){
	av_log(ctx, AV_LOG_ERROR, "failed to execute model\n");
	av_frame_free(&in);
	return AVERROR(EIO);
	}

	out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
	if (!out) {
	av_frame_free(&in);
	return AVERROR(ENOMEM);
	}

	av_frame_copy_props(out, in);
	copy_from_dnn_to_frame(ctx, out);

	if (isPlanarYUV(in->format))
	copy_uv_planes(ctx, out, in);

	av_frame_free(&in);
	return ff_filter_frame(outlink, out);
	}

	static av_cold void uninit(AVFilterContext *ctx)
	{
	DnnProcessingContext *context = ctx->priv;

	sws_freeContext(context->sws_gray8_to_grayf32);
	sws_freeContext(context->sws_grayf32_to_gray8);
	sws_freeContext(context->sws_uv_scale);

	if (context->dnn_module)
	(context->dnn_module->free_model)(&context->model);

	av_freep(&context->dnn_module);
	}

	static const AVFilterPad dnn_processing_inputs[] = {
	{
	.name = "default",
	.type = AVMEDIA_TYPE_VIDEO,
	.config_props = config_input,
	.filter_frame = filter_frame,
	},
	{ NULL }
	};

	static const AVFilterPad dnn_processing_outputs[] = {
	{
	.name = "default",
	.type = AVMEDIA_TYPE_VIDEO,
	.config_props = config_output,
	},
	{ NULL }
	};

	AVFilter ff_vf_dnn_processing = {
	.name = "dnn_processing",
	.description = NULL_IF_CONFIG_SMALL("Apply DNN processing filter to the input."),
	.priv_size = sizeof(DnnProcessingContext),
	.init = init,
	.uninit = uninit,
	.query_formats = query_formats,
	.inputs = dnn_processing_inputs,
	.outputs = dnn_processing_outputs,
	.priv_class = &dnn_processing_class,
	};