def get_image_to_chip_transform(bbox, chipsz, theta):
"""
transforms image space into chipspace
Args:
bbox - bounding box of chip in image space
chipsz - size of the chip
theta - rotation of the bounding box
Sympy:
# https://groups.google.com/forum/#!topic/sympy/k1HnZK_bNNA
from vtool.patch import * # NOQA
import sympy
import sympy.abc
theta = sympy.abc.theta
x, y, w, h, target_area = sympy.symbols('x y w h, a')
gx, gy = sympy.symbols('gx, gy')
round = sympy.floor # hack
ht = sympy.sqrt(target_area * h / w)
wt = w * ht / h
cw_, ch_ = round(wt), round(ht)
from vtool import ltool
T1 = ltool.translation_mat3x3(tx1, ty1, dtype=None)
S = ltool.scale_mat3x3(sx, sy, dtype=None)
R = ltool.rotation_mat3x3(-theta, sympy.sin, sympy.cos)
T2 = ltool.translation_mat3x3(tx2, ty2, dtype=None)
def add_matmul_hold_prop(mat):
#import functools
mat = sympy.Matrix(mat)
def matmul_hold(other, hold=False):
new = sympy.MatMul(mat, other, hold=hold)
add_matmul_hold_prop(new)
return new
setattr(mat, 'matmul_hold', matmul_hold)
return mat
T1 = add_matmul_hold_prop(T1)
T2 = add_matmul_hold_prop(T2)
R = add_matmul_hold_prop(R)
S = add_matmul_hold_prop(S)
C = T2.multiply(R.multiply(S.multiply(T1)))
sympy.simplify(C)
"""
(x, y, w, h) = bbox
(cw_, ch_) = chipsz
tx1 = -(x + (w / 2.0))
ty1 = -(y + (h / 2.0))
sx = (cw_ / w)
sy = (ch_ / h)
tx2 = (cw_ / 2.0)
ty2 = (ch_ / 2.0)
# Translate from bbox center to (0, 0)
T1 = ltool.translation_mat3x3(tx1, ty1)
# Scale to chip height
S = ltool.scale_mat3x3(sx, sy)
# Rotate to chip orientation
R = ltool.rotation_mat3x3(-theta)
# Translate from (0, 0) to chip center
T2 = ltool.translation_mat3x3(tx2, ty2)
# Merge into single transformation (operate left-to-right aka data on left)
C = T2.dot(R.dot(S.dot(T1)))
return C
def get_image_to_chip_transform(bbox, chipsz, theta):
"""
transforms image space into chipspace
Args:
bbox - bounding box of chip in image space
chipsz - size of the chip
theta - rotation of the bounding box
Sympy:
# https://groups.google.com/forum/#!topic/sympy/k1HnZK_bNNA
from vtool.patch import * # NOQA
import sympy
import sympy.abc
theta = sympy.abc.theta
x, y, w, h, target_area = sympy.symbols('x y w h, a')
gx, gy = sympy.symbols('gx, gy')
round = sympy.floor # hack
ht = sympy.sqrt(target_area * h / w)
wt = w * ht / h
cw_, ch_ = round(wt), round(ht)
from vtool import ltool
T1 = ltool.translation_mat3x3(tx1, ty1, dtype=None)
S = ltool.scale_mat3x3(sx, sy, dtype=None)
R = ltool.rotation_mat3x3(-theta, sympy.sin, sympy.cos)
T2 = ltool.translation_mat3x3(tx2, ty2, dtype=None)
def add_matmul_hold_prop(mat):
#import functools
mat = sympy.Matrix(mat)
def matmul_hold(other, hold=False):
new = sympy.MatMul(mat, other, hold=hold)
add_matmul_hold_prop(new)
return new
setattr(mat, 'matmul_hold', matmul_hold)
return mat
T1 = add_matmul_hold_prop(T1)
T2 = add_matmul_hold_prop(T2)
R = add_matmul_hold_prop(R)
S = add_matmul_hold_prop(S)
C = T2.multiply(R.multiply(S.multiply(T1)))
sympy.simplify(C)
"""
(x, y, w, h) = bbox
(cw_, ch_) = chipsz
tx1 = -(x + (w / 2.0))
ty1 = -(y + (h / 2.0))
sx = (cw_ / w)
sy = (ch_ / h)
tx2 = (cw_ / 2.0)
ty2 = (ch_ / 2.0)
# Translate from bbox center to (0, 0)
T1 = ltool.translation_mat3x3(tx1, ty1)
# Scale to chip height
S = ltool.scale_mat3x3(sx, sy)
# Rotate to chip orientation
R = ltool.rotation_mat3x3(-theta)
# Translate from (0, 0) to chip center
T2 = ltool.translation_mat3x3(tx2, ty2)
# Merge into single transformation (operate left-to-right aka data on left)
C = T2.dot(R.dot(S.dot(T1)))
return C