def buildOBB2d(points):
"""
3D点群のOBB(Oriented Bounding Box)生成
max_p: 最大の頂点[xmax, ymax]
min_p: 最小の頂点[xmin, ymin]
l: OBBの対角線の長さ
"""
# 分散共分散行列Sを生成
S = np.cov(points, rowvar=0, bias=1)
# 固有ベクトルを算出
w, svd_vector = LA.eig(S)
# 固有値が小さい順に固有ベクトルを並べる
svd_vector = svd_vector[np.argsort(w)]
# 正規直交座標にする(=直行行列にする)
# u = [sの単位ベクトル, tの単位ベクトル]になる
u = np.asarray(
[svd_vector[i] / np.linalg.norm(svd_vector[i]) for i in range(2)])
# 点群の各点と各固有ベクトルとの内積を取る
# P V^T = [[p1*v1, p1*v2], ... ,[pN*v1, pN*v2]]
inner_product = np.dot(points, u.T)
# 各固有値の内積最大、最小を抽出(max_st_point = [s座標max, tmax])
max_st_point = np.amax(inner_product, axis=0)
min_st_point = np.amin(inner_product, axis=0)
# xyz座標に変換・・・単位ベクトル*座標
# max_xyz_point = [[xs, ys], [xt, yt]]
max_xy_point = np.asarray([u[i] * max_st_point[i] for i in range(2)])
min_xy_point = np.asarray([u[i] * min_st_point[i] for i in range(2)])
#################################################################
# 図形作成処理
# s, t軸の単位ベクトル
s, t = u
# 法線: s, -s, t, -s
# c: 法線と1点(smaxなど)との内積
lx1 = F2.line([s[0], s[1], np.dot(max_xy_point[0], s)])
lx2 = F2.line([-s[0], -s[1], -np.dot(min_xy_point[0], s)])
ly1 = F2.line([t[0], t[1], np.dot(max_xy_point[1], t)])
ly2 = F2.line([-t[0], -t[1], -np.dot(min_xy_point[1], t)])
OBB = F2.inter(lx1, F2.inter(lx2, F2.inter(ly1, ly2)))
# 対角線の長さ算出
vert_max = min_xy_point[0] + min_xy_point[1]
vert_min = max_xy_point[0] + max_xy_point[1]
l = np.linalg.norm(vert_max - vert_min)
# 面積算出
area = abs((max_st_point[0] - min_st_point[0]) *
(max_st_point[1] - min_st_point[1]))
return max_xy_point, min_xy_point, OBB, l, area
def ConstructAABBObject2d(max_p, min_p):
# 図形作成処理
lx1 = F.line([1, 0, max_p[0]])
lx2 = F.line([-1, 0, -min_p[0]])
ly1 = F.line([0, 1, max_p[1]])
ly2 = F.line([0, -1, -min_p[1]])
AABB = F.inter(lx1, F.inter(lx2, F.inter(ly1, ly2)))
return AABB
def LastIoU(goal, opti, AABB, path):
# Figureの初期化
#fig = plt.figure(figsize=(12, 8))
# intersectionの面積
inter_fig = F.inter(goal, opti)
inter_points = ContourPoints(inter_fig.f_rep, AABB=AABB, grid_step=1000)
inter_points = np.array(inter_points, dtype=np.float32)
inter_area = cv2.contourArea(cv2.convexHull(inter_points))
# unionの面積
union_fig = F.union(goal, opti)
union_points = ContourPoints(union_fig.f_rep, AABB=AABB, grid_step=1000)
union_points = np.array(union_points, dtype=np.float32)
union_area = cv2.contourArea(cv2.convexHull(union_points))
X1, Y1 = Disassemble2d(inter_points)
X2, Y2 = Disassemble2d(union_points)
plt.plot(X1, Y1, marker=".", linestyle="None", color="red")
plt.plot(X2, Y2, marker=".", linestyle="None", color="yellow")
plt.savefig(path)
plt.close()
if len(goal.p) != len(opti.p):
return -1
if inter_points.shape[0] <= 2:
return -2
# print("{} / {}".format(inter_area, union_area))
return inter_area / union_area
def buildAABB2d(points):
# (x,y)の最大と最小をとる
max_p = np.amax(points, axis=0)
min_p = np.amin(points, axis=0)
# 図形作成処理
lx1 = F.line([1, 0, max_p[0]])
lx2 = F.line([-1, 0, -min_p[0]])
ly1 = F.line([0, 1, max_p[1]])
ly2 = F.line([0, -1, -min_p[1]])
AABB = F.inter(lx1, F.inter(lx2, F.inter(ly1, ly2)))
# 面積算出
area = abs((max_p[0] - min_p[0]) * (max_p[1] - min_p[1]))
return max_p, min_p, AABB, LA.norm(max_p - min_p), area