Rectangle kernels
Replace conv::size with conv::{w,h}. Shadow kernels are still squares, though. Signed-off-by: Yuxuan Shui <yshuiv7@gmail.com>
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@ -71,7 +71,9 @@ xcb_image_t *make_shadow(xcb_connection_t *c, const conv *kernel,
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*/
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xcb_image_t *ximage;
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const double *shadow_sum = kernel->rsum;
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int d = kernel->size, r = d / 2;
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// We only support square kernels for shadow
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assert(kernel->w == kernel->h);
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int d = kernel->w, r = d / 2;
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int swidth = width + r * 2, sheight = height + r * 2;
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assert(d % 2 == 1);
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54
src/kernel.c
54
src/kernel.c
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@ -12,32 +12,30 @@
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/// top left corner is at (x, y)
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double sum_kernel(const conv *map, int x, int y, int width, int height) {
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double ret = 0;
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/*
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* Compute set of filter values which are "in range"
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*/
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int xstart = x;
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if (xstart < 0)
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// Compute sum of values which are "in range"
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int xstart = x, xend = width + x;
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if (xstart < 0) {
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xstart = 0;
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int xend = width + x;
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if (xend > map->size)
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xend = map->size;
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int ystart = y;
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if (ystart < 0)
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}
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if (xend > map->w) {
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xend = map->w;
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}
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int ystart = y, yend = height + y;
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if (ystart < 0) {
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ystart = 0;
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int yend = height + y;
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if (yend > map->size)
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yend = map->size;
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}
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if (yend > map->h) {
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yend = map->h;
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}
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assert(yend >= ystart && xend >= xstart);
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assert(yend > 0 && xend > 0);
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int d = map->size;
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int d = map->w;
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if (map->rsum) {
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// See sum_kernel_preprocess
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double v1 = xstart ? map->rsum[(yend - 1) * d + xstart - 1] : 0;
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double v2 = ystart ? map->rsum[(ystart - 1) * d + xend - 1] : 0;
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double v3 =
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(xstart && ystart) ? map->rsum[(ystart - 1) * d + xstart - 1] : 0;
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double v3 = (xstart && ystart) ? map->rsum[(ystart - 1) * d + xstart - 1] : 0;
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return map->rsum[(yend - 1) * d + xend - 1] - v1 - v2 + v3;
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}
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@ -77,7 +75,7 @@ conv *gaussian_kernel(double r) {
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double t;
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c = cvalloc(sizeof(conv) + size * size * sizeof(double));
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c->size = size;
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c->w = c->h = size;
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c->rsum = NULL;
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t = 0.0;
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@ -100,22 +98,22 @@ conv *gaussian_kernel(double r) {
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/// preprocess kernels to make shadow generation faster
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/// shadow_sum[x*d+y] is the sum of the kernel from (0, 0) to (x, y), inclusive
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void shadow_preprocess(conv *map) {
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const int d = map->size;
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if (map->rsum)
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void sum_kernel_preprocess(conv *map) {
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if (map->rsum) {
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free(map->rsum);
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}
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auto sum = map->rsum = ccalloc(d * d, double);
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auto sum = map->rsum = ccalloc(map->w * map->h, double);
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sum[0] = map->data[0];
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for (int x = 1; x < d; x++) {
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for (int x = 1; x < map->w; x++) {
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sum[x] = sum[x - 1] + map->data[x];
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}
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for (int y = 1; y < d; y++) {
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const int d = map->w;
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for (int y = 1; y < map->h; y++) {
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sum[y * d] = sum[(y - 1) * d] + map->data[y * d];
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for (int x = 1; x < d; x++) {
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for (int x = 1; x < map->w; x++) {
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double tmp = sum[(y - 1) * d + x] + sum[y * d + x - 1] -
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sum[(y - 1) * d + x - 1];
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sum[y * d + x] = tmp + map->data[y * d + x];
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@ -8,7 +8,7 @@
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/// Code for generating convolution kernels
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typedef struct conv {
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int size;
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int w, h;
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double *rsum;
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double data[];
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} conv;
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@ -23,7 +23,7 @@ conv *gaussian_kernel(double r);
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/// preprocess kernels to make shadow generation faster
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/// shadow_sum[x*d+y] is the sum of the kernel from (0, 0) to (x, y), inclusive
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void shadow_preprocess(conv *map);
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void sum_kernel_preprocess(conv *map);
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static inline void free_conv(conv *k) {
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free(k->rsum);
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@ -1169,7 +1169,7 @@ bool init_render(session_t *ps) {
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}
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ps->gaussian_map = gaussian_kernel(ps->o.shadow_radius);
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shadow_preprocess(ps->gaussian_map);
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sum_kernel_preprocess(ps->gaussian_map);
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ps->black_picture = solid_picture(ps, true, 1, 0, 0, 0);
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ps->white_picture = solid_picture(ps, true, 1, 1, 1, 1);
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