be ideal.
*/
-const uint patch_size = 12;
-const uint num_iterations = 16;
+in vec3 flow_tc;
+in vec2 patch_center;
+flat in int ref_layer, search_layer;
+out vec3 out_flow;
+
+uniform sampler2DArray flow_tex, image_tex;
+uniform usampler2DArray grad_tex; // Also contains the corresponding reference image.
+uniform vec2 inv_image_size, inv_prev_level_size;
+uniform uint patch_size;
+uniform uint num_iterations;
+
+vec3 unpack_gradients(uint v)
+{
+ uint vi = v & 0xffu;
+ uint xi = (v >> 8) & 0xfffu;
+ uint yi = v >> 20;
+ vec3 r = vec3(xi * (1.0f / 4095.0f) - 0.5f, yi * (1.0f / 4095.0f) - 0.5f, vi * (1.0f / 255.0f));
+ return r;
+}
+
+// Note: The third variable is the actual pixel value.
+vec3 get_gradients(vec3 tc)
+{
+ vec3 grad = unpack_gradients(texture(grad_tex, tc).x);
-in vec2 flow_tc;
-in vec2 patch_bottom_left_texel; // Center of bottom-left texel of patch.
-out vec2 out_flow;
+ // Zero gradients outside the image. (We'd do this with a sampler,
+ // but we want the repeat behavior for the actual texels, in the
+ // z channel.)
+ if (any(lessThan(tc.xy, vec2(0.0f))) || any(greaterThan(tc.xy, vec2(1.0f)))) {
+ grad.xy = vec2(0.0f);
+ }
-uniform sampler2D flow_tex, grad0_tex, image0_tex, image1_tex;
-uniform vec2 image_size, inv_image_size;
+ return grad;
+}
void main()
{
- // Lock patch_bottom_left_texel to an integer, so that we never get
- // any bilinear artifacts for the gradient.
- vec2 base = round(patch_bottom_left_texel * image_size)
+ vec2 image_size = textureSize(grad_tex, 0).xy;
+
+ // Lock the patch center to an integer, so that we never get
+ // any bilinear artifacts for the gradient. (NOTE: This assumes an
+ // even patch size.) Then calculate the bottom-left texel of the patch.
+ vec2 base = (round(patch_center * image_size) - (0.5f * patch_size - 0.5f))
* inv_image_size;
// First, precompute the pseudo-Hessian for the template patch.
for (uint y = 0; y < patch_size; ++y) {
for (uint x = 0; x < patch_size; ++x) {
vec2 tc = base + uvec2(x, y) * inv_image_size;
- vec2 grad = texture(grad0_tex, tc).xy;
+ vec3 grad = get_gradients(vec3(tc, ref_layer));
H[0][0] += grad.x * grad.x;
H[1][1] += grad.y * grad.y;
H[0][1] += grad.x * grad.y;
- template_sum += texture(image0_tex, tc).x;
- grad_sum += grad;
+ template_sum += grad.z; // The actual template pixel value.
+ grad_sum += grad.xy;
}
}
H[1][0] = H[0][1];
mat2 H_inv = inverse(H);
- // Fetch the initial guess for the flow. (We need the normalization step
- // because densification works by accumulating; see the comments on the
- // Densify class.)
- vec3 prev_flow = texture(flow_tex, flow_tc).xyz;
- vec2 initial_u;
- if (prev_flow.z < 1e-3) {
- initial_u = vec2(0.0, 0.0);
- } else {
- initial_u = prev_flow.xy / prev_flow.z;
- }
-
- // Note: The flow is in OpenGL coordinates [0..1], but the calculations
- // generally come out in pixels since the gradient is in pixels,
- // so we need to convert at the end.
+ // Fetch the initial guess for the flow, and convert from the previous size to this one.
+ vec2 initial_u = texture(flow_tex, flow_tc).xy * (image_size * inv_prev_level_size);
vec2 u = initial_u;
+ float mean_diff, first_mean_diff;
for (uint i = 0; i < num_iterations; ++i) {
vec2 du = vec2(0.0, 0.0);
float warped_sum = 0.0f;
+ vec2 u_norm = u * inv_image_size; // In [0..1] coordinates instead of pixels.
for (uint y = 0; y < patch_size; ++y) {
for (uint x = 0; x < patch_size; ++x) {
vec2 tc = base + uvec2(x, y) * inv_image_size;
- vec2 grad = texture(grad0_tex, tc).xy;
- float t = texture(image0_tex, tc).x;
- float warped = texture(image1_tex, tc + u).x;
- du += grad * (warped - t);
+ vec3 grad = get_gradients(vec3(tc, ref_layer));
+ float t = grad.z;
+ float warped = texture(image_tex, vec3(tc + u_norm, search_layer)).x;
+ du += grad.xy * (warped - t);
warped_sum += warped;
}
}
// sum(S^T * (x - y)) = [what we calculated] - (µ1 - µ2) sum(S^T)
//
// so we can just subtract away the mean difference here.
- du -= grad_sum * (warped_sum - template_sum) * (1.0 / (patch_size * patch_size));
+ mean_diff = (warped_sum - template_sum) * (1.0 / float(patch_size * patch_size));
+ du -= grad_sum * mean_diff;
- u += (H_inv * du) * inv_image_size;
+ if (i == 0) {
+ first_mean_diff = mean_diff;
+ }
+
+ // Do the actual update.
+ u -= H_inv * du;
}
- // Reject if we moved too far.
- if (length((u - initial_u) * image_size) > patch_size) {
+ // Reject if we moved too far. Note that the paper says “too far” is the
+ // patch size, but the DIS code uses half of a patch size. The latter seems
+ // to give much better overall results.
+ //
+ // Also reject if the patch goes out-of-bounds (the paper does not mention this,
+ // but the code does, and it seems to be critical to avoid really bad behavior
+ // at the edges).
+ vec2 patch_center = (base * image_size - 0.5f) + patch_size * 0.5f + u;
+ if (length(u - initial_u) > (patch_size * 0.5f) ||
+ patch_center.x < -(patch_size * 0.5f) ||
+ image_size.x - patch_center.x < -(patch_size * 0.5f) ||
+ patch_center.y < -(patch_size * 0.5f) ||
+ image_size.y - patch_center.y < -(patch_size * 0.5f)) {
u = initial_u;
+ mean_diff = first_mean_diff;
}
- out_flow = u;
+ // NOTE: The mean patch diff will be for the second-to-last patch,
+ // not the true position of du. But hopefully, it will be very close.
+ u *= inv_image_size;
+ out_flow = vec3(u.x, u.y, mean_diff);
}
projects / nageru / blobdiff