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Code Issues Releases Activity

avfilter/vf_nnedi: small improvements

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Paul B Mahol
2021-01-20 13:05:52 +01:00
parent 2021dbe1d6
commit 1dc71cf64e
1 changed files with 13 additions and 8 deletions
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21
libavfilter/vf_nnedi.c
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@@ -21,6 +21,7 @@
#include <float.h> #include <float.h>
#include "libavutil/avassert.h"
#include "libavutil/common.h" #include "libavutil/common.h"
#include "libavutil/float_dsp.h" #include "libavutil/float_dsp.h"
#include "libavutil/imgutils.h" #include "libavutil/imgutils.h"
@@ -217,11 +218,13 @@ static int query_formats(AVFilterContext *ctx)
static float dot_dsp(const NNEDIContext *const s, const float *kernel, const float *input, static float dot_dsp(const NNEDIContext *const s, const float *kernel, const float *input,
int n, float scale, float bias) int n, float scale, float bias)
{ {
float sum; float sum, y;
sum = s->fdsp->scalarproduct_float(kernel, input, n); sum = s->fdsp->scalarproduct_float(kernel, input, n);
return sum * scale + bias; y = sum * scale + bias + 1e-20f;
return y;
} }
static float elliott(float x) static float elliott(float x)
@@ -334,6 +337,7 @@ static void gather_input(const float *src, ptrdiff_t src_stride,
float *buf, float mstd[4], float *buf, float mstd[4],
const PredictorCoefficients *const model) const PredictorCoefficients *const model)
{ {
const float scale = 1.f / model->nsize;
float sum = 0.f; float sum = 0.f;
float sum_sq = 0.f; float sum_sq = 0.f;
float tmp; float tmp;
@@ -352,10 +356,10 @@ static void gather_input(const float *src, ptrdiff_t src_stride,
buf += model->xdim; buf += model->xdim;
} }
mstd[0] = sum / model->nsize; mstd[0] = sum * scale;
mstd[3] = 0.f; mstd[3] = 0.f;
tmp = sum_sq / model->nsize - mstd[0] * mstd[0]; tmp = sum_sq * scale - mstd[0] * mstd[0];
if (tmp < FLT_EPSILON) { if (tmp < FLT_EPSILON) {
mstd[1] = 0.0f; mstd[1] = 0.0f;
mstd[2] = 0.0f; mstd[2] = 0.0f;
@@ -945,8 +949,9 @@ static void subtract_mean_new(PrescreenerCoefficients *coeffs, float half)
static void subtract_mean_predictor(PredictorCoefficients *model) static void subtract_mean_predictor(PredictorCoefficients *model)
{ {
int filter_size = model->nsize; const int filter_size = model->nsize;
int nns = model->nns; const int nns = model->nns;
const float scale = 1.f / nns;
double softmax_means[256]; // Average of individual softmax filters. double softmax_means[256]; // Average of individual softmax filters.
double elliott_means[256]; // Average of individual elliott filters. double elliott_means[256]; // Average of individual elliott filters.
@@ -963,7 +968,7 @@ static void subtract_mean_predictor(PredictorCoefficients *model)
} }
for (int k = 0; k < filter_size; k++) for (int k = 0; k < filter_size; k++)
mean_filter[k] /= nns; mean_filter[k] *= scale;
mean_bias = mean(model->softmax_bias_q1, nns); mean_bias = mean(model->softmax_bias_q1, nns);
@@ -988,7 +993,7 @@ static void subtract_mean_predictor(PredictorCoefficients *model)
} }
for (int k = 0; k < filter_size; k++) for (int k = 0; k < filter_size; k++)
mean_filter[k] /= nns; mean_filter[k] *= scale;
mean_bias = mean(model->softmax_bias_q2, nns); mean_bias = mean(model->softmax_bias_q2, nns);