//
// Solve for e = 1e-6 yields a step size of 0.0027, which to cover the range
// 0..3 needs 1109 steps. We round up to the next power of two, just to be sure.
+//
+// You need to call lanczos_table_init_done before the first call to
+// lanczos_weight_cached.
#define LANCZOS_TABLE_SIZE 2048
bool lanczos_table_init_done = false;
float lanczos_table[LANCZOS_TABLE_SIZE + 2];
float lanczos_weight_cached(float x)
{
- if (!lanczos_table_init_done) {
- // Could in theory race between two threads if we are unlucky,
- // but that is harmless, since they'll write the same data.
- init_lanczos_table();
- }
x = fabs(x);
if (x > LANCZOS_RADIUS) {
return 0.0f;
void normalize_sum(Tap<T>* vals, unsigned num)
{
for (int normalize_pass = 0; normalize_pass < 2; ++normalize_pass) {
- double sum = 0.0;
+ float sum = 0.0;
for (unsigned i = 0; i < num; ++i) {
- sum += to_fp64(vals[i].weight);
+ sum += to_fp32(vals[i].weight);
}
- double inv_sum = 1.0 / sum;
+ float inv_sum = 1.0 / sum;
for (unsigned i = 0; i < num; ++i) {
- vals[i].weight = from_fp64<T>(to_fp64(vals[i].weight) * inv_sum);
+ vals[i].weight = from_fp32<T>(to_fp32(vals[i].weight) * inv_sum);
}
}
}
// Find the effective range of the bilinear-optimized kernel.
// Due to rounding of the positions, this is not necessarily the same
// as the intended range (ie., the range of the original weights).
- int lower_pos = int(floor(to_fp64(bilinear_weights[0].pos) * size - 0.5));
- int upper_pos = int(ceil(to_fp64(bilinear_weights[num_bilinear_weights - 1].pos) * size - 0.5)) + 2;
+ int lower_pos = int(floor(to_fp32(bilinear_weights[0].pos) * size - 0.5));
+ int upper_pos = int(ceil(to_fp32(bilinear_weights[num_bilinear_weights - 1].pos) * size - 0.5)) + 2;
lower_pos = min<int>(lower_pos, lrintf(weights[0].pos * size - 0.5));
upper_pos = max<int>(upper_pos, lrintf(weights[num_weights - 1].pos * size - 0.5) + 1);
// Now find the effective weights that result from this sampling.
for (unsigned i = 0; i < num_bilinear_weights; ++i) {
- const float pixel_pos = to_fp64(bilinear_weights[i].pos) * size - 0.5f;
+ const float pixel_pos = to_fp32(bilinear_weights[i].pos) * size - 0.5f;
const int x0 = int(floor(pixel_pos)) - lower_pos;
const int x1 = x0 + 1;
const float f = lrintf((pixel_pos - (x0 + lower_pos)) / movit_texel_subpixel_precision) * movit_texel_subpixel_precision;
assert(x0 < upper_pos - lower_pos);
assert(x1 < upper_pos - lower_pos);
- effective_weights[x0] += to_fp64(bilinear_weights[i].weight) * (1.0 - f);
- effective_weights[x1] += to_fp64(bilinear_weights[i].weight) * f;
+ effective_weights[x0] += to_fp32(bilinear_weights[i].weight) * (1.0 - f);
+ effective_weights[x1] += to_fp32(bilinear_weights[i].weight) * f;
}
// Subtract the desired weights to get the error.
register_uniform_float("whole_pixel_offset", &uniform_whole_pixel_offset);
glGenTextures(1, &texnum);
+
+ if (!lanczos_table_init_done) {
+ // Could in theory race between two threads if we are unlucky,
+ // but that is harmless, since they'll write the same data.
+ init_lanczos_table();
+ }
}
SingleResamplePassEffect::~SingleResamplePassEffect()
// We specifically do not want mipmaps on the input texture;
// they break minification.
Node *self = chain->find_node_for_effect(this);
- glActiveTexture(chain->get_input_sampler(self, 0));
- check_error();
- glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_LINEAR);
- check_error();
+ if (chain->has_input_sampler(self, 0)) {
+ glActiveTexture(chain->get_input_sampler(self, 0));
+ check_error();
+ glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_LINEAR);
+ check_error();
+ }
}
} // namespace movit