/* * 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 */ #include "dnn_filter_common.h"#include "libavutil/avstring.h"#include "libavutil/mem.h"#include "libavutil/opt.h" #define MAX_SUPPORTED_OUTPUTS_NB 4 static char **separate_output_names(const char *expr, const char *val_sep, int *separated_nb){    char *val, **parsed_vals = NULL;    int val_num = 0;    if (!expr || !val_sep || !separated_nb) {        return NULL;    }     parsed_vals = av_calloc(MAX_SUPPORTED_OUTPUTS_NB, sizeof(*parsed_vals));    if (!parsed_vals) {        return NULL;    }     do {        val = av_get_token(&expr, val_sep);        if(val) {            parsed_vals[val_num] = val;            val_num++;        }        if (*expr) {            expr++;        }    } while(*expr);     parsed_vals[val_num] = NULL;    *separated_nb = val_num;     return parsed_vals;} typedef struct DnnFilterBase {    const AVClass *class;    DnnContext dnnctx;} DnnFilterBase; int ff_dnn_filter_init_child_class(AVFilterContext *filter) {    DnnFilterBase *base = filter->priv;    ff_dnn_init_child_class(&base->dnnctx);    return 0;} void *ff_dnn_filter_child_next(void *obj, void *prev){    DnnFilterBase *base = obj;    return ff_dnn_child_next(&base->dnnctx, prev);} int ff_dnn_init(DnnContext *ctx, DNNFunctionType func_type, AVFilterContext *filter_ctx){    DNNBackendType backend = ctx->backend_type;     if (!ctx->model_filename) {        av_log(filter_ctx, AV_LOG_ERROR, "model file for network is not specified\n");        return AVERROR(EINVAL);    }     if (backend == DNN_TH) {        if (ctx->model_inputname)            av_log(filter_ctx, AV_LOG_WARNING, "LibTorch backend do not require inputname, "\                                               "inputname will be ignored.\n");        if (ctx->model_outputnames)            av_log(filter_ctx, AV_LOG_WARNING, "LibTorch backend do not require outputname(s), "\                                               "all outputname(s) will be ignored.\n");        ctx->nb_outputs = 1;    } else if (backend == DNN_TF) {        if (!ctx->model_inputname) {            av_log(filter_ctx, AV_LOG_ERROR, "input name of the model network is not specified\n");            return AVERROR(EINVAL);        }        ctx->model_outputnames = separate_output_names(ctx->model_outputnames_string, "&", &ctx->nb_outputs);        if (!ctx->model_outputnames) {            av_log(filter_ctx, AV_LOG_ERROR, "could not parse model output names\n");            return AVERROR(EINVAL);        }    }     ctx->dnn_module = ff_get_dnn_module(ctx->backend_type, filter_ctx);    if (!ctx->dnn_module) {        av_log(filter_ctx, AV_LOG_ERROR, "could not create DNN module for requested backend\n");        return AVERROR(ENOMEM);    }    if (!ctx->dnn_module->load_model) {        av_log(filter_ctx, AV_LOG_ERROR, "load_model for network is not specified\n");        return AVERROR(EINVAL);    }     if (ctx->backend_options) {        void *child = NULL;         av_log(filter_ctx, AV_LOG_WARNING,               "backend_configs is deprecated, please set backend options directly\n");        while (child = ff_dnn_child_next(ctx, child)) {            if (*(const AVClass **)child == &ctx->dnn_module->clazz) {                int ret = av_opt_set_from_string(child, ctx->backend_options,                                                 NULL, "=", "&");                if (ret < 0) {                    av_log(filter_ctx, AV_LOG_ERROR, "failed to parse options \"%s\"\n",                           ctx->backend_options);                    return ret;                }            }        }    }     ctx->model = (ctx->dnn_module->load_model)(ctx, func_type, filter_ctx);    if (!ctx->model) {        av_log(filter_ctx, AV_LOG_ERROR, "could not load DNN model\n");        return AVERROR(EINVAL);    }     return 0;} int ff_dnn_set_frame_proc(DnnContext *ctx, FramePrePostProc pre_proc, FramePrePostProc post_proc){    ctx->model->frame_pre_proc = pre_proc;    ctx->model->frame_post_proc = post_proc;    return 0;} int ff_dnn_set_detect_post_proc(DnnContext *ctx, DetectPostProc post_proc){    ctx->model->detect_post_proc = post_proc;    return 0;} int ff_dnn_set_classify_post_proc(DnnContext *ctx, ClassifyPostProc post_proc){    ctx->model->classify_post_proc = post_proc;    return 0;} int ff_dnn_get_input(DnnContext *ctx, DNNData *input){    return ctx->model->get_input(ctx->model, input, ctx->model_inputname);} int ff_dnn_get_output(DnnContext *ctx, int input_width, int input_height, int *output_width, int *output_height){    char * output_name = ctx->model_outputnames && ctx->backend_type != DNN_TH ?                         ctx->model_outputnames[0] : NULL;    return ctx->model->get_output(ctx->model, ctx->model_inputname, input_width, input_height,                                  (const char *)output_name, output_width, output_height);} int ff_dnn_execute_model(DnnContext *ctx, AVFrame *in_frame, AVFrame *out_frame){    DNNExecBaseParams exec_params = {        .input_name     = ctx->model_inputname,        .output_names   = (const char **)ctx->model_outputnames,        .nb_output      = ctx->nb_outputs,        .in_frame       = in_frame,        .out_frame      = out_frame,    };    return (ctx->dnn_module->execute_model)(ctx->model, &exec_params);} int ff_dnn_execute_model_classification(DnnContext *ctx, AVFrame *in_frame, AVFrame *out_frame, const char *target){    DNNExecClassificationParams class_params = {        {            .input_name     = ctx->model_inputname,            .output_names   = (const char **)ctx->model_outputnames,            .nb_output      = ctx->nb_outputs,            .in_frame       = in_frame,            .out_frame      = out_frame,        },        .target = target,    };    return (ctx->dnn_module->execute_model)(ctx->model, &class_params.base);} DNNAsyncStatusType ff_dnn_get_result(DnnContext *ctx, AVFrame **in_frame, AVFrame **out_frame){    return (ctx->dnn_module->get_result)(ctx->model, in_frame, out_frame);} int ff_dnn_flush(DnnContext *ctx){    return (ctx->dnn_module->flush)(ctx->model);} void ff_dnn_uninit(DnnContext *ctx){    if (ctx->dnn_module) {        (ctx->dnn_module->free_model)(&ctx->model);    }    if (ctx->model_outputnames) {        for (int i = 0; i < ctx->nb_outputs; i++)            av_free(ctx->model_outputnames[i]);         av_freep(&ctx->model_outputnames);    }}