[FFmpeg-cvslog] avfilter/vf_dnn_processing: refine code for better naming
Guo, Yejun
git at videolan.org
Fri Dec 13 16:45:11 EET 2019
ffmpeg | branch: master | Guo, Yejun <yejun.guo at intel.com> | Fri Nov 22 15:49:57 2019 +0800| [ed9fc2e3c576703d0bb904a93d4e654c1239f4da] | committer: Pedro Arthur
avfilter/vf_dnn_processing: refine code for better naming
Signed-off-by: Guo, Yejun <yejun.guo at intel.com>
Signed-off-by: Pedro Arthur <bygrandao at gmail.com>
> http://git.videolan.org/gitweb.cgi/ffmpeg.git/?a=commit;h=ed9fc2e3c576703d0bb904a93d4e654c1239f4da
---
libavfilter/vf_dnn_processing.c | 90 ++++++++++++++++++++---------------------
1 file changed, 45 insertions(+), 45 deletions(-)
diff --git a/libavfilter/vf_dnn_processing.c b/libavfilter/vf_dnn_processing.c
index f59cfb0da2..ce976ec3bd 100644
--- a/libavfilter/vf_dnn_processing.c
+++ b/libavfilter/vf_dnn_processing.c
@@ -136,40 +136,40 @@ static int config_input(AVFilterLink *inlink)
AVFilterContext *context = inlink->dst;
DnnProcessingContext *ctx = context->priv;
DNNReturnType result;
- DNNData dnn_data;
+ DNNData model_input;
- result = ctx->model->get_input(ctx->model->model, &dnn_data, ctx->model_inputname);
+ 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);
}
// the design is to add explicit scale filter before this filter
- if (dnn_data.height != -1 && dnn_data.height != inlink->h) {
+ 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",
- dnn_data.height, inlink->h);
+ model_input.height, inlink->h);
return AVERROR(EIO);
}
- if (dnn_data.width != -1 && dnn_data.width != inlink->w) {
+ 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",
- dnn_data.width, inlink->w);
+ model_input.width, inlink->w);
return AVERROR(EIO);
}
- if (dnn_data.channels != 3) {
+ if (model_input.channels != 3) {
av_log(ctx, AV_LOG_ERROR, "the model requires input channels %d\n",
- dnn_data.channels);
+ model_input.channels);
return AVERROR(EIO);
}
- if (dnn_data.dt != DNN_FLOAT && dnn_data.dt != DNN_UINT8) {
+ 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);
}
ctx->input.width = inlink->w;
ctx->input.height = inlink->h;
- ctx->input.channels = dnn_data.channels;
- ctx->input.dt = dnn_data.dt;
+ 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,
@@ -201,28 +201,28 @@ static int config_output(AVFilterLink *outlink)
return 0;
}
-static int copy_from_frame_to_dnn(DNNData *dnn_data, const AVFrame *in)
+static int copy_from_frame_to_dnn(DNNData *dnn_input, const AVFrame *frame)
{
// extend this function to support more formats
- av_assert0(in->format == AV_PIX_FMT_RGB24 || in->format == AV_PIX_FMT_BGR24);
-
- if (dnn_data->dt == DNN_FLOAT) {
- float *dnn_input = dnn_data->data;
- for (int i = 0; i < in->height; i++) {
- for(int j = 0; j < in->width * 3; j++) {
- int k = i * in->linesize[0] + j;
- int t = i * in->width * 3 + j;
- dnn_input[t] = in->data[0][k] / 255.0f;
+ av_assert0(frame->format == AV_PIX_FMT_RGB24 || frame->format == AV_PIX_FMT_BGR24);
+
+ if (dnn_input->dt == DNN_FLOAT) {
+ float *dnn_input_data = dnn_input->data;
+ for (int i = 0; i < frame->height; i++) {
+ for(int j = 0; j < frame->width * 3; j++) {
+ int k = i * frame->linesize[0] + j;
+ int t = i * frame->width * 3 + j;
+ dnn_input_data[t] = frame->data[0][k] / 255.0f;
}
}
} else {
- uint8_t *dnn_input = dnn_data->data;
- av_assert0(dnn_data->dt == DNN_UINT8);
- for (int i = 0; i < in->height; i++) {
- for(int j = 0; j < in->width * 3; j++) {
- int k = i * in->linesize[0] + j;
- int t = i * in->width * 3 + j;
- dnn_input[t] = in->data[0][k];
+ uint8_t *dnn_input_data = dnn_input->data;
+ av_assert0(dnn_input->dt == DNN_UINT8);
+ for (int i = 0; i < frame->height; i++) {
+ for(int j = 0; j < frame->width * 3; j++) {
+ int k = i * frame->linesize[0] + j;
+ int t = i * frame->width * 3 + j;
+ dnn_input_data[t] = frame->data[0][k];
}
}
}
@@ -230,28 +230,28 @@ static int copy_from_frame_to_dnn(DNNData *dnn_data, const AVFrame *in)
return 0;
}
-static int copy_from_dnn_to_frame(AVFrame *out, const DNNData *dnn_data)
+static int copy_from_dnn_to_frame(AVFrame *frame, const DNNData *dnn_output)
{
// extend this function to support more formats
- av_assert0(out->format == AV_PIX_FMT_RGB24 || out->format == AV_PIX_FMT_BGR24);
-
- if (dnn_data->dt == DNN_FLOAT) {
- float *dnn_output = dnn_data->data;
- for (int i = 0; i < out->height; i++) {
- for(int j = 0; j < out->width * 3; j++) {
- int k = i * out->linesize[0] + j;
- int t = i * out->width * 3 + j;
- out->data[0][k] = av_clip_uintp2((int)(dnn_output[t] * 255.0f), 8);
+ av_assert0(frame->format == AV_PIX_FMT_RGB24 || frame->format == AV_PIX_FMT_BGR24);
+
+ if (dnn_output->dt == DNN_FLOAT) {
+ float *dnn_output_data = dnn_output->data;
+ for (int i = 0; i < frame->height; i++) {
+ for(int j = 0; j < frame->width * 3; j++) {
+ int k = i * frame->linesize[0] + j;
+ int t = i * frame->width * 3 + j;
+ frame->data[0][k] = av_clip_uintp2((int)(dnn_output_data[t] * 255.0f), 8);
}
}
} else {
- uint8_t *dnn_output = dnn_data->data;
- av_assert0(dnn_data->dt == DNN_UINT8);
- for (int i = 0; i < out->height; i++) {
- for(int j = 0; j < out->width * 3; j++) {
- int k = i * out->linesize[0] + j;
- int t = i * out->width * 3 + j;
- out->data[0][k] = dnn_output[t];
+ uint8_t *dnn_output_data = dnn_output->data;
+ av_assert0(dnn_output->dt == DNN_UINT8);
+ for (int i = 0; i < frame->height; i++) {
+ for(int j = 0; j < frame->width * 3; j++) {
+ int k = i * frame->linesize[0] + j;
+ int t = i * frame->width * 3 + j;
+ frame->data[0][k] = dnn_output_data[t];
}
}
}
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