#include "libavutil/pixdesc.h"
#include "libavformat/avio.h"
#include "libswscale/swscale.h"
-#include "dnn_interface.h"
+#include "dnn_filter_common.h"
typedef struct SRContext {
const AVClass *class;
-
- char *model_filename;
- DNNBackendType backend_type;
- DNNModule *dnn_module;
- DNNModel *model;
+ DnnContext dnnctx;
int scale_factor;
struct SwsContext *sws_uv_scale;
int sws_uv_height;
#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" },
+ { "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(model_filename), AV_OPT_TYPE_STRING, {.str=NULL}, 0, 0, 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_outputname), AV_OPT_TYPE_STRING, { .str = "y" }, 0, 0, FLAGS },
{ NULL }
};
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);
- }
- if (!sr_context->dnn_module->load_model) {
- av_log(context, AV_LOG_ERROR, "load_model for network was not specified\n");
- return AVERROR(EIO);
- }
- sr_context->model = (sr_context->dnn_module->load_model)(sr_context->model_filename, NULL, NULL);
- if (!sr_context->model){
- av_log(context, AV_LOG_ERROR, "could not load DNN model\n");
- return AVERROR(EIO);
- }
-
- return 0;
+ return ff_dnn_init(&sr_context->dnnctx, DFT_PROCESS_FRAME, context);
}
static int query_formats(AVFilterContext *context)
SRContext *ctx = context->priv;
DNNReturnType result;
AVFilterLink *inlink = context->inputs[0];
- AVFrame *out = NULL;
- const char *model_output_name = "y";
-
- AVFrame *fake_in = ff_get_video_buffer(inlink, inlink->w, inlink->h);
- result = (ctx->model->set_input)(ctx->model->model, fake_in, "x");
- if (result != DNN_SUCCESS) {
- av_log(context, AV_LOG_ERROR, "could not set input for the model\n");
- return AVERROR(EIO);
- }
+ int out_width, out_height;
// have a try run in case that the dnn model resize the frame
- out = ff_get_video_buffer(inlink, inlink->w, inlink->h);
- result = (ctx->dnn_module->execute_model)(ctx->model, (const char **)&model_output_name, 1, out);
- if (result != DNN_SUCCESS){
- av_log(context, AV_LOG_ERROR, "failed to execute loaded model\n");
+ result = ff_dnn_get_output(&ctx->dnnctx, inlink->w, inlink->h, &out_width, &out_height);
+ if (result != DNN_SUCCESS) {
+ av_log(ctx, AV_LOG_ERROR, "could not get output from the model\n");
return AVERROR(EIO);
}
- if (fake_in->width != out->width || fake_in->height != out->height) {
+ if (inlink->w != out_width || inlink->h != out_height) {
//espcn
- outlink->w = out->width;
- outlink->h = out->height;
+ 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);
}
} else {
//srcnn
- outlink->w = out->width * ctx->scale_factor;
- outlink->h = out->height * ctx->scale_factor;
+ 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);
}
- av_frame_free(&fake_in);
- av_frame_free(&out);
return 0;
}
AVFilterLink *outlink = context->outputs[0];
AVFrame *out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
DNNReturnType dnn_result;
- const char *model_output_name = "y";
if (!out){
av_log(context, AV_LOG_ERROR, "could not allocate memory for output frame\n");
sws_scale(ctx->sws_pre_scale,
(const uint8_t **)in->data, in->linesize, 0, in->height,
out->data, out->linesize);
- dnn_result = (ctx->model->set_input)(ctx->model->model, out, "x");
+ dnn_result = ff_dnn_execute_model(&ctx->dnnctx, out, out);
} else {
- dnn_result = (ctx->model->set_input)(ctx->model->model, in, "x");
- }
-
- if (dnn_result != DNN_SUCCESS) {
- av_frame_free(&in);
- av_frame_free(&out);
- av_log(context, AV_LOG_ERROR, "could not set input for the model\n");
- return AVERROR(EIO);
+ dnn_result = ff_dnn_execute_model(&ctx->dnnctx, in, out);
}
- dnn_result = (ctx->dnn_module->execute_model)(ctx->model, (const char **)&model_output_name, 1, out);
if (dnn_result != DNN_SUCCESS){
av_log(ctx, AV_LOG_ERROR, "failed to execute loaded model\n");
av_frame_free(&in);
{
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);
- }
-
+ ff_dnn_uninit(&sr_context->dnnctx);
sws_freeContext(sr_context->sws_uv_scale);
sws_freeContext(sr_context->sws_pre_scale);
}
{ NULL }
};
-AVFilter ff_vf_sr = {
+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),
projects / ffmpeg / blobdiff