void ccv_slice(ccv_matrix_t* a, ccv_matrix_t** b, int btype, int y, int x, int rows, int cols)
{
int type = *(int*)a;
if (type & CCV_MATRIX_DENSE)
{
ccv_dense_matrix_t* da = ccv_get_dense_matrix(a);
ccv_declare_derived_signature(sig, da->sig != 0, ccv_sign_with_format(128, "ccv_slice(%d,%d,%d,%d)", y, x, rows, cols), da->sig, CCV_EOF_SIGN);
btype = (btype == 0) ? CCV_GET_DATA_TYPE(da->type) | CCV_GET_CHANNEL(da->type) : CCV_GET_DATA_TYPE(btype) | CCV_GET_CHANNEL(da->type);
ccv_dense_matrix_t* db = *b = ccv_dense_matrix_renew(*b, rows, cols, CCV_ALL_DATA_TYPE | CCV_GET_CHANNEL(da->type), btype, sig);
ccv_object_return_if_cached(, db);
int i, j, ch = CCV_GET_CHANNEL(da->type);
int dx = 0, dy = 0;
if (!(y >= 0 && y + rows <= da->rows && x >= 0 && x + cols <= da->cols))
{
ccv_zero(db);
if (y < 0) { rows += y; dy = -y; y = 0; }
if (y + rows > da->rows) rows = da->rows - y;
if (x < 0) { cols += x; dx = -x; x = 0; }
if (x + cols > da->cols) cols = da->cols - x;
}
unsigned char* a_ptr = da->data.u8 + x * ch * CCV_GET_DATA_TYPE_SIZE(da->type) + y * da->step;
unsigned char* b_ptr = db->data.u8 + dx * ch * CCV_GET_DATA_TYPE_SIZE(db->type) + dy * db->step;
#define for_block(_for_set, _for_get) \
for (i = 0; i < rows; i++) \
{ \
for (j = 0; j < cols * ch; j++) \
{ \
_for_set(b_ptr, j, _for_get(a_ptr, j, 0), 0); \
} \
a_ptr += da->step; \
b_ptr += db->step; \
}
ccv_matrix_setter(db->type, ccv_matrix_getter, da->type, for_block);
#undef for_block
} else if (type & CCV_MATRIX_SPARSE) {
int rosenbrock(const ccv_dense_matrix_t* x, double* f, ccv_dense_matrix_t* df, void* data)
{
int* steps = (int*)data;
(*steps)++;
int i;
double rf = 0;
double* x_vec = x->data.f64;
for (i = 0; i < 1; i++)
rf += 100 * (x_vec[i + 1] - x_vec[i] * x_vec[i]) * (x_vec[i + 1] - x_vec[i] * x_vec[i]) + (1 - x_vec[i]) * (1 - x_vec[i]);
*f = rf;
double* df_vec = df->data.f64;
ccv_zero(df);
df_vec[0] = df_vec[1] = 0;
for (i = 0; i < 1; i++)
df_vec[i] = -400 * x_vec[i] * (x_vec[i+1] - x_vec[i] * x_vec[i]) - 2 * (1 - x_vec[i]);
for (i = 1; i < 2; i++)
df_vec[i] += 200 * (x_vec[i] - x_vec[i - 1] * x_vec[i - 1]);
return 0;
}
void ccv_close_outline(ccv_dense_matrix_t* a, ccv_dense_matrix_t** b, int type)
{
assert((CCV_GET_CHANNEL(a->type) == CCV_C1) && ((a->type & CCV_8U) || (a->type & CCV_32S) || (a->type & CCV_64S)));
ccv_declare_derived_signature(sig, a->sig != 0, ccv_sign_with_literal("ccv_close_outline"), a->sig, CCV_EOF_SIGN);
type = ((type == 0) || (type & CCV_32F) || (type & CCV_64F)) ? CCV_GET_DATA_TYPE(a->type) | CCV_C1 : CCV_GET_DATA_TYPE(type) | CCV_C1;
ccv_dense_matrix_t* db = *b = ccv_dense_matrix_renew(*b, a->rows, a->cols, CCV_C1 | CCV_ALL_DATA_TYPE, type, sig);
ccv_object_return_if_cached(, db);
int i, j;
unsigned char* a_ptr = a->data.u8;
unsigned char* b_ptr = db->data.u8;
ccv_zero(db);
#define for_block(_for_get, _for_set_b, _for_get_b) \
for (i = 0; i < a->rows - 1; i++) \
{ \
for (j = 0; j < a->cols - 1; j++) \
{ \
if (!_for_get_b(b_ptr, j, 0)) \
_for_set_b(b_ptr, j, _for_get(a_ptr, j, 0), 0); \
if (_for_get(a_ptr, j, 0) && _for_get(a_ptr + a->step, j + 1, 0)) \
{ \
_for_set_b(b_ptr + a->step, j, 1, 0); \
_for_set_b(b_ptr, j + 1, 1, 0); \
} \
if (_for_get(a_ptr + a->step, j, 0) && _for_get(a_ptr, j + 1, 0)) \
{ \
_for_set_b(b_ptr, j, 1, 0); \
_for_set_b(b_ptr + a->step, j + 1, 1, 0); \
} \
} \
if (!_for_get_b(b_ptr, a->cols - 1, 0)) \
_for_set_b(b_ptr, a->cols - 1, _for_get(a_ptr, a->cols - 1, 0), 0); \
a_ptr += a->step; \
b_ptr += db->step; \
} \
for (j = 0; j < a->cols; j++) \
{ \
if (!_for_get_b(b_ptr, j, 0)) \
_for_set_b(b_ptr, j, _for_get(a_ptr, j, 0), 0); \
}
ccv_matrix_getter_integer_only(a->type, ccv_matrix_setter_getter_integer_only, db->type, for_block);
#undef for_block
}
void ccv_decimal_slice(ccv_dense_matrix_t* a, ccv_dense_matrix_t** b, int type, float y, float x, int rows, int cols)
{
ccv_declare_derived_signature(sig, a->sig != 0, ccv_sign_with_format(64, "ccv_decimal_slice(%a,%a,%d,%d)", y, x, rows, cols), a->sig, CCV_EOF_SIGN);
type = (type == 0) ? CCV_GET_DATA_TYPE(a->type) | CCV_GET_CHANNEL(a->type) : CCV_GET_DATA_TYPE(type) | CCV_GET_CHANNEL(a->type);
ccv_dense_matrix_t* db = *b = ccv_dense_matrix_renew(*b, rows, cols, CCV_ALL_DATA_TYPE | CCV_GET_CHANNEL(a->type), type, sig);
ccv_object_return_if_cached(, db);
int i, j, ch = CCV_GET_CHANNEL(a->type);
int ix = (int)x, iy = (int)y;
float xd = x - ix, yd = y - iy;
float w00 = (1 - xd) * (1 - yd);
float w01 = xd * (1 - yd);
float w10 = (1 - xd) * yd;
float w11 = xd * yd;
int dx = 0, dy = 0;
int rows_1 = 0, cols_1 = 0;
// it is going to be hard to deal with border efficiently, since this is used for tld, will ignore border for now
if (!(iy >= 0 && iy + rows < a->rows && ix >= 0 && ix + cols < a->cols))
{
ccv_zero(db);
if (iy < 0) { rows += iy; dy = -iy; iy = 0; }
if (iy + rows >= a->rows)
{
rows = a->rows - iy - 1;
if (iy + rows > a->rows)
rows_1 = 1; // we need to do our best to padding the last row
}
if (ix < 0) { cols += ix; dx = -ix; ix = 0; }
if (x + cols >= a->cols)
{
cols = a->cols - ix - 1;
if (x + cols > a->cols)
cols_1 = 1; // we need to do our best to padding the last col
}
}
unsigned char* a_ptr = (unsigned char*)ccv_get_dense_matrix_cell(a, iy, ix, 0);
unsigned char* b_ptr = (unsigned char*)ccv_get_dense_matrix_cell(db, dy, dx, 0);
#define for_block(_for_set, _for_get) \
for (i = 0; i < rows; i++) \
{ \
for (j = 0; j < cols * ch; j++) \
{ \
_for_set(b_ptr, j, (_for_get(a_ptr, j, 0) * G00 + _for_get(a_ptr, j + ch, 0) * G01 + _for_get(a_ptr + a->step, j, 0) * G10 + _for_get(a_ptr + a->step, j + ch, 0) * G11) / GALL, 0); \
} \
if (cols_1) \
_for_set(b_ptr, j, (_for_get(a_ptr, j, 0) * (G00 + G01) + _for_get(a_ptr + a->step, j, 0) * G10 + _for_get(a_ptr + a->step, j + ch, 0) * G11) / GALL, 0); \
a_ptr += a->step; \
b_ptr += db->step; \
} \
if (rows_1) \
{ \
for (j = 0; j < cols * ch; j++) \
{ \
_for_set(b_ptr, j, (_for_get(a_ptr, j, 0) * (G00 + G10) + _for_get(a_ptr, j + ch, 0) * (G01 + G11)) / GALL, 0); \
} \
if (cols_1) \
_for_set(b_ptr, j, _for_get(a_ptr, j, 0), 0); \
}
/* unswitch in the manual way so that we can use integer interpolation */
if ((a->type & CCV_8U) || (a->type & CCV_32S) || (a->type & CCV_64S))
{
const int W_BITS14 = 14;
int iw00 = (int)(w00 * (1 << W_BITS14) + 0.5);
int iw01 = (int)(w01 * (1 << W_BITS14) + 0.5);
int iw10 = (int)(w10 * (1 << W_BITS14) + 0.5);
int iw11 = (1 << W_BITS14) - iw00 - iw01 - iw10;
#define G00 (iw00)
#define G01 (iw01)
#define G10 (iw10)
#define G11 (iw11)
#define GCOM (1 << (W_BITS14 - 1))
#define GALL (1 << (W_BITS14))
ccv_matrix_setter(db->type, ccv_matrix_getter_integer_only, a->type, for_block);
#undef G00
#undef G01
#undef G10
#undef G11
#undef GCOM
#undef GALL
} else {
#define G00 (w00)
#define G01 (w01)
#define G10 (w10)
#define G11 (w11)
#define GCOM (0)
#define GALL (1)
ccv_matrix_setter(db->type, ccv_matrix_getter_float_only, a->type, for_block);
#undef G00
#undef G01
#undef G10
#undef G11
#undef GCOM
#undef GALL
}
#undef for_block
}
void ccv_hog(ccv_dense_matrix_t* a, ccv_dense_matrix_t** b, int b_type, int sbin, int size)
{
assert(a->rows >= size && a->cols >= size && (4 + sbin * 3) <= CCV_MAX_CHANNEL);
int rows = a->rows / size;
int cols = a->cols / size;
b_type = (CCV_GET_DATA_TYPE(b_type) == CCV_64F) ? CCV_64F | (4 + sbin * 3) : CCV_32F | (4 + sbin * 3);
ccv_declare_derived_signature(sig, a->sig != 0, ccv_sign_with_format(64, "ccv_hog(%d,%d)", sbin, size), a->sig, CCV_EOF_SIGN);
ccv_dense_matrix_t* db = *b = ccv_dense_matrix_renew(*b, rows, cols, CCV_64F | CCV_32F | (4 + sbin * 3), b_type, sig);
ccv_object_return_if_cached(, db);
ccv_dense_matrix_t* ag = 0;
ccv_dense_matrix_t* mg = 0;
ccv_gradient(a, &ag, 0, &mg, 0, 1, 1);
float* agp = ag->data.f32;
float* mgp = mg->data.f32;
int i, j, k, ch = CCV_GET_CHANNEL(a->type);
ccv_dense_matrix_t* cn = ccv_dense_matrix_new(rows, cols, CCV_GET_DATA_TYPE(db->type) | (sbin * 2), 0, 0);
ccv_dense_matrix_t* ca = ccv_dense_matrix_new(rows, cols, CCV_GET_DATA_TYPE(db->type) | CCV_C1, 0, 0);
ccv_zero(cn);
// normalize sbin direction-sensitive and sbin * 2 insensitive over 4 normalization factor
// accumulating them over sbin * 2 + sbin + 4 channels
// TNA - truncation - normalization - accumulation
#define TNA(_for_type, idx, a, b, c, d) \
{ \
_for_type norm = 1.0 / sqrt(cap[a] + cap[b] + cap[c] + cap[d] + 1e-4); \
for (k = 0; k < sbin * 2; k++) \
{ \
_for_type v = 0.5 * ccv_min(cnp[k] * norm, 0.2); \
dbp[4 + sbin + k] += v; \
dbp[idx] += v; \
} \
dbp[idx] *= 0.2357; \
for (k = 0; k < sbin; k++) \
{ \
_for_type v = 0.5 * ccv_min((cnp[k] + cnp[k + sbin]) * norm, 0.2); \
dbp[4 + k] += v; \
} \
}
#define for_block(_, _for_type) \
_for_type* cnp = (_for_type*)ccv_get_dense_matrix_cell(cn, 0, 0, 0); \
for (i = 0; i < rows * size; i++) \
{ \
for (j = 0; j < cols * size; j++) \
{ \
_for_type agv = agp[j * ch]; \
_for_type mgv = mgp[j * ch]; \
for (k = 1; k < ch; k++) \
if (mgp[j * ch + k] > mgv) \
{ \
mgv = mgp[j * ch + k]; \
agv = agp[j * ch + k]; \
} \
_for_type agr0 = (ccv_clamp(agv, 0, 359.99) / 360.0) * (sbin * 2); \
int ag0 = (int)agr0; \
int ag1 = (ag0 + 1 < sbin * 2) ? ag0 + 1 : 0; \
agr0 = agr0 - ag0; \
_for_type agr1 = 1.0 - agr0; \
mgv = mgv / 255.0; \
_for_type yp = ((_for_type)i + 0.5) / (_for_type)size - 0.5; \
_for_type xp = ((_for_type)j + 0.5) / (_for_type)size - 0.5; \
int iyp = (int)floor(yp); \
assert(iyp < rows); \
int ixp = (int)floor(xp); \
assert(ixp < cols); \
_for_type vy0 = yp - iyp; \
_for_type vx0 = xp - ixp; \
_for_type vy1 = 1.0 - vy0; \
_for_type vx1 = 1.0 - vx0; \
if (ixp >= 0 && iyp >= 0) \
{ \
cnp[iyp * cn->cols * sbin * 2 + ixp * sbin * 2 + ag0] += agr1 * vx1 * vy1 * mgv; \
cnp[iyp * cn->cols * sbin * 2 + ixp * sbin * 2 + ag1] += agr0 * vx1 * vy1 * mgv; \
} \
if (ixp + 1 < cn->cols && iyp >= 0) \
{ \
cnp[iyp * cn->cols * sbin * 2 + (ixp + 1) * sbin * 2 + ag0] += agr1 * vx0 * vy1 * mgv; \
cnp[iyp * cn->cols * sbin * 2 + (ixp + 1) * sbin * 2 + ag1] += agr0 * vx0 * vy1 * mgv; \
} \
if (ixp >= 0 && iyp + 1 < cn->rows) \
{ \
cnp[(iyp + 1) * cn->cols * sbin * 2 + ixp * sbin * 2 + ag0] += agr1 * vx1 * vy0 * mgv; \
cnp[(iyp + 1) * cn->cols * sbin * 2 + ixp * sbin * 2 + ag1] += agr0 * vx1 * vy0 * mgv; \
} \
if (ixp + 1 < cn->cols && iyp + 1 < cn->rows) \
{ \
cnp[(iyp + 1) * cn->cols * sbin * 2 + (ixp + 1) * sbin * 2 + ag0] += agr1 * vx0 * vy0 * mgv; \
cnp[(iyp + 1) * cn->cols * sbin * 2 + (ixp + 1) * sbin * 2 + ag1] += agr0 * vx0 * vy0 * mgv; \
} \
} \
agp += a->cols * ch; \
mgp += a->cols * ch; \
} \
ccv_matrix_free(ag); \
ccv_matrix_free(mg); \
cnp = (_for_type*)ccv_get_dense_matrix_cell(cn, 0, 0, 0); \
_for_type* cap = (_for_type*)ccv_get_dense_matrix_cell(ca, 0, 0, 0); \
for (i = 0; i < rows; i++) \
{ \
for (j = 0; j < cols; j++) \
{ \
*cap = 0; \
for (k = 0; k < sbin; k++) \
*cap += (cnp[k] + cnp[k + sbin]) * (cnp[k] + cnp[k + sbin]); \
cnp += 2 * sbin; \
cap++; \
} \
} \
cnp = (_for_type*)ccv_get_dense_matrix_cell(cn, 0, 0, 0); \
cap = (_for_type*)ccv_get_dense_matrix_cell(ca, 0, 0, 0); \
ccv_zero(db); \
_for_type* dbp = (_for_type*)ccv_get_dense_matrix_cell(db, 0, 0, 0); \
TNA(_for_type, 0, 1, cols + 1, cols, 0); \
TNA(_for_type, 1, 1, 1, 0, 0); \
TNA(_for_type, 2, 0, cols, cols, 0); \
TNA(_for_type, 3, 0, 0, 0, 0); \
cnp += 2 * sbin; \
dbp += 3 * sbin + 4; \
cap++; \
for (j = 1; j < cols - 1; j++) \
{ \
TNA(_for_type, 0, 1, cols + 1, cols, 0); \
TNA(_for_type, 1, 1, 1, 0, 0); \
TNA(_for_type, 2, -1, cols - 1, cols, 0); \
TNA(_for_type, 3, -1, -1, 0, 0); \
cnp += 2 * sbin; \
dbp += 3 * sbin + 4; \
cap++; \
} \
TNA(_for_type, 0, 0, cols, cols, 0); \
TNA(_for_type, 1, 0, 0, 0, 0); \
TNA(_for_type, 2, -1, cols - 1, cols, 0); \
TNA(_for_type, 3, -1, -1, 0, 0); \
cnp += 2 * sbin; \
dbp += 3 * sbin + 4; \
cap++; \
for (i = 1; i < rows - 1; i++) \
{ \
TNA(_for_type, 0, 1, cols + 1, cols, 0); \
TNA(_for_type, 1, 1, -cols + 1, -cols, 0); \
TNA(_for_type, 2, 0, cols, cols, 0); \
TNA(_for_type, 3, 0, -cols, -cols, 0); \
cnp += 2 * sbin; \
dbp += 3 * sbin + 4; \
cap++; \
for (j = 1; j < cols - 1; j++) \
{ \
TNA(_for_type, 0, 1, cols + 1, cols, 0); \
TNA(_for_type, 1, 1, -cols + 1, -cols, 0); \
TNA(_for_type, 2, -1, cols - 1, cols, 0); \
TNA(_for_type, 3, -1, -cols - 1, -cols, 0); \
cnp += 2 * sbin; \
dbp += 3 * sbin + 4; \
cap++; \
} \
TNA(_for_type, 0, 0, cols, cols, 0); \
TNA(_for_type, 1, 0, -cols, -cols, 0); \
TNA(_for_type, 2, -1, cols - 1, cols, 0); \
TNA(_for_type, 3, -1, -cols - 1, -cols, 0); \
cnp += 2 * sbin; \
dbp += 3 * sbin + 4; \
cap++; \
} \
TNA(_for_type, 0, 1, 1, 0, 0); \
TNA(_for_type, 1, 1, -cols + 1, -cols, 0); \
TNA(_for_type, 2, 0, 0, 0, 0); \
TNA(_for_type, 3, 0, -cols, -cols, 0); \
cnp += 2 * sbin; \
dbp += 3 * sbin + 4; \
cap++; \
for (j = 1; j < cols - 1; j++) \
{ \
TNA(_for_type, 0, 1, 1, 0, 0); \
TNA(_for_type, 1, 1, -cols + 1, -cols, 0); \
TNA(_for_type, 2, -1, -1, 0, 0); \
TNA(_for_type, 3, -1, -cols - 1, -cols, 0); \
cnp += 2 * sbin; \
dbp += 3 * sbin + 4; \
cap++; \
} \
TNA(_for_type, 0, 0, 0, 0, 0); \
TNA(_for_type, 1, 0, -cols, -cols, 0); \
TNA(_for_type, 2, -1, -1, 0, 0); \
TNA(_for_type, 3, -1, -cols - 1, -cols, 0);
ccv_matrix_typeof(db->type, for_block);
#undef for_block
#undef TNA
ccv_matrix_free(cn);
ccv_matrix_free(ca);
}
