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avfilter/vf_nnedi: fix some compilation errors and warnings

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This commit is contained in:
Paul B Mahol 2021-01-19 12:15:07 +01:00
parent c48110a4a4
commit f3f5ba0bf8
1 changed files with 27 additions and 27 deletions
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54
libavfilter/vf_nnedi.c
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@ -325,7 +325,7 @@ static void process_new(AVFilterContext *ctx,
}
}
static size_t filter_offset(unsigned nn, PredictorCoefficients *model)
static int filter_offset(unsigned nn, PredictorCoefficients *model)
{
return nn * model->xdim * model->ydim;
}
@ -420,8 +420,8 @@ static void predictor(AVFilterContext *ctx,
// 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);
unsigned filter_size = model->xdim * model->ydim;
unsigned nns = model->nns;
int filter_size = model->xdim * model->ydim;
int nns = model->nns;
for (int i = 0; i < N; i++) {
LOCAL_ALIGNED_32(float, input, [48 * 6]);
@ -816,13 +816,13 @@ static int request_frame(AVFilterLink *link)
return 0;
}
static void read(float *dst, size_t n, const float **data)
static void copy_weights(float *dst, int n, const float **data)
{
memcpy(dst, *data, n * sizeof(float));
*data += n;
}
static float *allocate(float **ptr, size_t size)
static float *allocate(float **ptr, int size)
{
float *ret = *ptr;
@ -833,8 +833,8 @@ static float *allocate(float **ptr, size_t size)
static int allocate_model(PredictorCoefficients *coeffs, int xdim, int ydim, int nns)
{
size_t filter_size = nns * xdim * ydim;
size_t bias_size = nns;
int filter_size = nns * xdim * ydim;
int bias_size = nns;
float *data;
data = av_malloc_array(filter_size + bias_size, 4 * sizeof(float));
@ -864,25 +864,25 @@ static int read_weights(AVFilterContext *ctx, const float *bdata)
NNEDIContext *s = ctx->priv;
int ret;
read(&s->prescreener_old.kernel_l0[0][0], 4 * 48, &bdata);
read(s->prescreener_old.bias_l0, 4, &bdata);
copy_weights(&s->prescreener_old.kernel_l0[0][0], 4 * 48, &bdata);
copy_weights(s->prescreener_old.bias_l0, 4, &bdata);
read(&s->prescreener_old.kernel_l1[0][0], 4 * 4, &bdata);
read(s->prescreener_old.bias_l1, 4, &bdata);
copy_weights(&s->prescreener_old.kernel_l1[0][0], 4 * 4, &bdata);
copy_weights(s->prescreener_old.bias_l1, 4, &bdata);
read(&s->prescreener_old.kernel_l2[0][0], 4 * 8, &bdata);
read(s->prescreener_old.bias_l2, 4, &bdata);
copy_weights(&s->prescreener_old.kernel_l2[0][0], 4 * 8, &bdata);
copy_weights(s->prescreener_old.bias_l2, 4, &bdata);
for (int i = 0; i < 3; i++) {
PrescreenerNewCoefficients *data = &s->prescreener_new[i];
float kernel_l0_shuffled[4 * 64];
float kernel_l1_shuffled[4 * 4];
read(kernel_l0_shuffled, 4 * 64, &bdata);
read(data->bias_l0, 4, &bdata);
copy_weights(kernel_l0_shuffled, 4 * 64, &bdata);
copy_weights(data->bias_l0, 4, &bdata);
read(kernel_l1_shuffled, 4 * 4, &bdata);
read(data->bias_l1, 4, &bdata);
copy_weights(kernel_l1_shuffled, 4 * 4, &bdata);
copy_weights(data->bias_l1, 4, &bdata);
for (int n = 0; n < 4; n++) {
for (int k = 0; k < 64; k++)
@ -902,27 +902,27 @@ static int read_weights(AVFilterContext *ctx, const float *bdata)
PredictorCoefficients *model = &s->coeffs[m][i][j];
int xdim = NNEDI_XDIM[j];
int ydim = NNEDI_YDIM[j];
size_t filter_size = xdim * ydim;
int filter_size = xdim * ydim;
ret = allocate_model(model, xdim, ydim, nns);
if (ret < 0)
return ret;
// Quality 1 model. NNS[i] * (XDIM[j] * YDIM[j]) * 2 coefficients.
read(model->softmax_q1, nns * filter_size, &bdata);
read(model->elliott_q1, nns * filter_size, &bdata);
copy_weights(model->softmax_q1, nns * filter_size, &bdata);
copy_weights(model->elliott_q1, nns * filter_size, &bdata);
// Quality 1 model bias. NNS[i] * 2 coefficients.
read(model->softmax_bias_q1, nns, &bdata);
read(model->elliott_bias_q1, nns, &bdata);
copy_weights(model->softmax_bias_q1, nns, &bdata);
copy_weights(model->elliott_bias_q1, nns, &bdata);
// Quality 2 model. NNS[i] * (XDIM[j] * YDIM[j]) * 2 coefficients.
read(model->softmax_q2, nns * filter_size, &bdata);
read(model->elliott_q2, nns * filter_size, &bdata);
copy_weights(model->softmax_q2, nns * filter_size, &bdata);
copy_weights(model->elliott_q2, nns * filter_size, &bdata);
// Quality 2 model bias. NNS[i] * 2 coefficients.
read(model->softmax_bias_q2, nns, &bdata);
read(model->elliott_bias_q2, nns, &bdata);
copy_weights(model->softmax_bias_q2, nns, &bdata);
copy_weights(model->elliott_bias_q2, nns, &bdata);
}
}
}
@ -966,7 +966,7 @@ static void subtract_mean_new(PrescreenerNewCoefficients *coeffs, float half)
static void subtract_mean_predictor(PredictorCoefficients *model)
{
size_t filter_size = model->xdim * model->ydim;
int filter_size = model->xdim * model->ydim;
int nns = model->nns;
float softmax_means[256]; // Average of individual softmax filters.