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avfilter/vf_nnedi: small cleanups

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pull/371/head
Paul B Mahol 4 years ago
parent f3f5ba0bf8
commit 553eb07737
1 changed files with 39 additions and 44 deletions
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  1. 83
      libavfilter/vf_nnedi.c

83
libavfilter/vf_nnedi.c
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@ -37,30 +37,27 @@ static const uint8_t NNEDI_XDIM[] = { 8, 16, 32, 48, 8, 16, 32 };
static const uint8_t NNEDI_YDIM[] = { 6, 6, 6, 6, 4, 4, 4 };
static const uint16_t NNEDI_NNS[] = { 16, 32, 64, 128, 256 };
static const unsigned NNEDI_DIMS0 = 49 * 4 + 5 * 4 + 9 * 4;
static const unsigned NNEDI_DIMS0_NEW = 4 * 65 + 4 * 5;
typedef struct PrescreenerOldCoefficients {
DECLARE_ALIGNED(32, float, kernel_l0)[4][14 * 4];
float bias_l0[4];
DECLARE_ALIGNED(32, float, bias_l0)[4];
DECLARE_ALIGNED(32, float, kernel_l1)[4][4];
float bias_l1[4];
DECLARE_ALIGNED(32, float, bias_l1)[4];
DECLARE_ALIGNED(32, float, kernel_l2)[4][8];
float bias_l2[4];
DECLARE_ALIGNED(32, float, bias_l2)[4];
} PrescreenerOldCoefficients;
typedef struct PrescreenerNewCoefficients {
DECLARE_ALIGNED(32, float, kernel_l0)[4][16 * 4];
float bias_l0[4];
DECLARE_ALIGNED(32, float, bias_l0)[4];
DECLARE_ALIGNED(32, float, kernel_l1)[4][4];
float bias_l1[4];
DECLARE_ALIGNED(32, float, bias_l1)[4];
} PrescreenerNewCoefficients;
typedef struct PredictorCoefficients {
int xdim, ydim, nns;
int xdim, ydim, nns, nsize;
float *data;
float *softmax_q1;
float *elliott_q1;
@ -226,7 +223,7 @@ static int query_formats(AVFilterContext *ctx)
}
static float dot_dsp(NNEDIContext *s, const float *kernel, const float *input,
unsigned n, float scale, float bias)
int n, float scale, float bias)
{
float sum;
@ -235,17 +232,6 @@ static float dot_dsp(NNEDIContext *s, const float *kernel, const float *input,
return sum * scale + bias;
}
static float dot_product(const float *kernel, const float *input,
unsigned n, float scale, float bias)
{
float sum = 0.0f;
for (int i = 0; i < n; i++)
sum += kernel[i] * input[i];
return sum * scale + bias;
}
static float elliott(float x)
{
return x / (1.0f + fabsf(x));
@ -263,7 +249,7 @@ static void process_old(AVFilterContext *ctx,
void *data)
{
NNEDIContext *s = ctx->priv;
PrescreenerOldCoefficients *m_data = data;
const PrescreenerOldCoefficients *const m_data = data;
const float *src_p = src;
// Adjust source pointer to point to top-left of filter window.
@ -283,12 +269,12 @@ static void process_old(AVFilterContext *ctx,
// Layer 1.
for (int n = 0; n < 4; n++)
state[n + 4] = dot_product(m_data->kernel_l1[n], state, 4, 1.0f, m_data->bias_l1[n]);
state[n + 4] = dot_dsp(s, m_data->kernel_l1[n], state, 4, 1.0f, m_data->bias_l1[n]);
transform_elliott(state + 4, 3);
// Layer 2.
for (int n = 0; n < 4; n++)
state[n + 8] = dot_product(m_data->kernel_l2[n], state, 8, 1.0f, m_data->bias_l2[n]);
state[n + 8] = dot_dsp(s, m_data->kernel_l2[n], state, 8, 1.0f, m_data->bias_l2[n]);
prescreen[j] = FFMAX(state[10], state[11]) <= FFMAX(state[8], state[9]) ? 255 : 0;
}
@ -300,7 +286,7 @@ static void process_new(AVFilterContext *ctx,
void *data)
{
NNEDIContext *s = ctx->priv;
PrescreenerNewCoefficients *m_data = data;
const PrescreenerNewCoefficients *const m_data = data;
const float *src_p = src;
// Adjust source pointer to point to top-left of filter window.
@ -318,60 +304,68 @@ static void process_new(AVFilterContext *ctx,
transform_elliott(state, 4);
for (int n = 0; n < 4; n++)
state[n + 4] = dot_product(m_data->kernel_l1[n], state, 4, 1.0f, m_data->bias_l1[n]);
state[n + 4] = dot_dsp(s, m_data->kernel_l1[n], state, 4, 1.0f, m_data->bias_l1[n]);
for (int n = 0; n < 4; n++)
prescreen[j + n] = state[n + 4] > 0.f;
}
}
static int filter_offset(unsigned nn, PredictorCoefficients *model)
static int filter_offset(int nn, const PredictorCoefficients *const model)
{
return nn * model->xdim * model->ydim;
return nn * model->nsize;
}
static const float *softmax_q1_filter(unsigned nn, PredictorCoefficients *model)
static const float *softmax_q1_filter(int nn,
const PredictorCoefficients *const model)
{
return model->softmax_q1 + filter_offset(nn, model);
}
static const float *elliott_q1_filter(unsigned nn, PredictorCoefficients *model)
static const float *elliott_q1_filter(int nn,
const PredictorCoefficients *const model)
{
return model->elliott_q1 + filter_offset(nn, model);
}
static const float *softmax_q2_filter(unsigned nn, PredictorCoefficients *model)
static const float *softmax_q2_filter(int nn,
const PredictorCoefficients *const model)
{
return model->softmax_q2 + filter_offset(nn, model);
}
static const float *elliott_q2_filter(unsigned nn, PredictorCoefficients *model)
static const float *elliott_q2_filter(int nn,
const PredictorCoefficients *const model)
{
return model->elliott_q2 + filter_offset(nn, model);
}
static void gather_input(const float *src, ptrdiff_t src_stride,
float *buf, float mstd[4],
PredictorCoefficients *model)
const PredictorCoefficients *const model)
{
float sum = 0;
float sum_sq = 0;
float tmp;
for (int i = 0; i < model->ydim; i++) {
memcpy(buf, src, model->xdim * sizeof(float));
for (int j = 0; j < model->xdim; j++) {
float val = src[i * src_stride + j];
const float val = src[j];
buf[i * model->xdim + j] = val;
sum += val;
sum_sq += val * val;
}
src += src_stride;
buf += model->xdim;
}
mstd[0] = sum / (model->xdim * model->ydim);
mstd[0] = sum / model->nsize;
mstd[3] = 0.f;
tmp = sum_sq / (model->xdim * model->ydim) - mstd[0] * mstd[0];
tmp = sum_sq / model->nsize - mstd[0] * mstd[0];
if (tmp < FLT_EPSILON) {
mstd[1] = 0.0f;
mstd[2] = 0.0f;
@ -393,7 +387,7 @@ static void transform_softmax_exp(float *input, int size)
}
static void wae5(const float *softmax, const float *el,
unsigned n, float mstd[4])
int n, float mstd[4])
{
float vsum = 0.0f, wsum = 0.0f;
@ -414,13 +408,13 @@ static void predictor(AVFilterContext *ctx,
void *data, int use_q2)
{
NNEDIContext *s = ctx->priv;
PredictorCoefficients *model = data;
const PredictorCoefficients *const model = data;
const float *src_p = src;
float *dst_p = dst;
// Adjust source pointer to point to top-left of filter window.
const float *window = src_p - (model->ydim / 2) * src_stride - (model->xdim / 2 - 1);
int filter_size = model->xdim * model->ydim;
int filter_size = model->nsize;
int nns = model->nns;
for (int i = 0; i < N; i++) {
@ -534,7 +528,7 @@ static void write_words(const float *src, uint8_t *dstp,
}
static void interpolation(const void *src, ptrdiff_t src_stride,
void *dst, const uint8_t *prescreen, unsigned n)
void *dst, const uint8_t *prescreen, int n)
{
const float *src_p = src;
float *dst_p = dst;
@ -844,6 +838,7 @@ static int allocate_model(PredictorCoefficients *coeffs, int xdim, int ydim, int
coeffs->data = data;
coeffs->xdim = xdim;
coeffs->ydim = ydim;
coeffs->nsize = xdim * ydim;
coeffs->nns = nns;
coeffs->softmax_q1 = allocate(&data, filter_size);
@ -966,7 +961,7 @@ static void subtract_mean_new(PrescreenerNewCoefficients *coeffs, float half)
static void subtract_mean_predictor(PredictorCoefficients *model)
{
int filter_size = model->xdim * model->ydim;
int filter_size = model->nsize;
int nns = model->nns;
float softmax_means[256]; // Average of individual softmax filters.
@ -1013,8 +1008,8 @@ static void subtract_mean_predictor(PredictorCoefficients *model)
mean_bias = mean(model->softmax_bias_q2, nns);
for (unsigned nn = 0; nn < nns; nn++) {
for (unsigned k = 0; k < filter_size; k++) {
for (int nn = 0; nn < nns; nn++) {
for (int k = 0; k < filter_size; k++) {
model->softmax_q2[nn * filter_size + k] -= softmax_means[nn] + mean_filter[k];
model->elliott_q2[nn * filter_size + k] -= elliott_means[nn];
}

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