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data_aug.py
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data_aug.py
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import numpy as np
from config import config as cfg
import cv2
import matplotlib.pyplot as plt
def draw_polygon(img, box_corner, color = (255, 255, 255),thickness = 1):
tup0 = (box_corner[0, 1],box_corner[0, 0])
tup1 = (box_corner[1, 1],box_corner[1, 0])
tup2 = (box_corner[2, 1],box_corner[2, 0])
tup3 = (box_corner[3, 1],box_corner[3, 0])
cv2.line(img, tup0, tup1, color, thickness, cv2.LINE_AA)
cv2.line(img, tup1, tup2, color, thickness, cv2.LINE_AA)
cv2.line(img, tup2, tup3, color, thickness, cv2.LINE_AA)
cv2.line(img, tup3, tup0, color, thickness, cv2.LINE_AA)
return img
def point_transform(points, tx, ty, tz, rx=0, ry=0, rz=0):
# Input:
# points: (N, 3)
# rx/y/z: in radians
# Output:
# points: (N, 3)
N = points.shape[0]
points = np.hstack([points, np.ones((N, 1))])
mat1 = np.eye(4)
mat1[3, 0:3] = tx, ty, tz
points = np.matmul(points, mat1)
if rx != 0:
mat = np.zeros((4, 4))
mat[0, 0] = 1
mat[3, 3] = 1
mat[1, 1] = np.cos(rx)
mat[1, 2] = -np.sin(rx)
mat[2, 1] = np.sin(rx)
mat[2, 2] = np.cos(rx)
points = np.matmul(points, mat)
if ry != 0:
mat = np.zeros((4, 4))
mat[1, 1] = 1
mat[3, 3] = 1
mat[0, 0] = np.cos(ry)
mat[0, 2] = np.sin(ry)
mat[2, 0] = -np.sin(ry)
mat[2, 2] = np.cos(ry)
points = np.matmul(points, mat)
if rz != 0:
mat = np.zeros((4, 4))
mat[2, 2] = 1
mat[3, 3] = 1
mat[0, 0] = np.cos(rz)
mat[0, 1] = -np.sin(rz)
mat[1, 0] = np.sin(rz)
mat[1, 1] = np.cos(rz)
points = np.matmul(points, mat)
return points[:, 0:3]
def box_transform(boxes_corner, tx, ty, tz, r=0):
# boxes_corner (N, 8, 3)
for idx in range(len(boxes_corner)):
boxes_corner[idx] = point_transform(boxes_corner[idx], tx, ty, tz, rz=r)
return boxes_corner
def cal_iou2d(box1_corner, box2_corner):
box1_corner = np.reshape(box1_corner, [4, 2])
box2_corner = np.reshape(box2_corner, [4, 2])
box1_corner = ((cfg.W, cfg.H)-(box1_corner - (cfg.xrange[0], cfg.yrange[0])) / (cfg.vw, cfg.vh)).astype(np.int32)
box2_corner = ((cfg.W, cfg.H)-(box2_corner - (cfg.xrange[0], cfg.yrange[0])) / (cfg.vw, cfg.vh)).astype(np.int32)
buf1 = np.zeros((cfg.H, cfg.W, 3))
buf2 = np.zeros((cfg.H, cfg.W, 3))
buf1 = cv2.fillConvexPoly(buf1, box1_corner, color=(1,1,1))[..., 0]
buf2 = cv2.fillConvexPoly(buf2, box2_corner, color=(1,1,1))[..., 0]
indiv = np.sum(np.absolute(buf1-buf2))
share = np.sum((buf1 + buf2) == 2)
if indiv == 0:
return 0.0 # when target is out of bound
return share / (indiv + share)
def aug_data(lidar, gt_box3d_corner):
np.random.seed()
choice = np.random.randint(1, 10)
if choice >= 7:
for idx in range(len(gt_box3d_corner)):
# TODO: precisely gather the point
is_collision = True
_count = 0
while is_collision and _count < 100:
t_rz = np.random.uniform(-np.pi / 10, np.pi / 10)
t_x = np.random.normal()
t_y = np.random.normal()
t_z = np.random.normal()
# check collision
tmp = box_transform(
gt_box3d_corner[[idx]], t_x, t_y, t_z, t_rz)
is_collision = False
for idy in range(idx):
iou = cal_iou2d(tmp[0,:4,:2],gt_box3d_corner[idy,:4,:2])
if iou > 0:
is_collision = True
_count += 1
break
if not is_collision:
box_corner = gt_box3d_corner[idx]
minx = np.min(box_corner[:, 0])
miny = np.min(box_corner[:, 1])
minz = np.min(box_corner[:, 2])
maxx = np.max(box_corner[:, 0])
maxy = np.max(box_corner[:, 1])
maxz = np.max(box_corner[:, 2])
bound_x = np.logical_and(
lidar[:, 0] >= minx, lidar[:, 0] <= maxx)
bound_y = np.logical_and(
lidar[:, 1] >= miny, lidar[:, 1] <= maxy)
bound_z = np.logical_and(
lidar[:, 2] >= minz, lidar[:, 2] <= maxz)
bound_box = np.logical_and(
np.logical_and(bound_x, bound_y), bound_z)
lidar[bound_box, 0:3] = point_transform(
lidar[bound_box, 0:3], t_x, t_y, t_z, rz=t_rz)
gt_box3d_corner[idx] = box_transform(
gt_box3d_corner[[idx]], t_x, t_y, t_z, t_rz)
gt_box3d = gt_box3d_corner
elif choice < 7 and choice >= 4:
# global rotation
angle = np.random.uniform(-np.pi / 4, np.pi / 4)
lidar[:, 0:3] = point_transform(lidar[:, 0:3], 0, 0, 0, rz=angle)
gt_box3d = box_transform(gt_box3d_corner, 0, 0, 0, r=angle)
else:
# global scaling
factor = np.random.uniform(0.95, 1.05)
lidar[:, 0:3] = lidar[:, 0:3] * factor
gt_box3d = gt_box3d_corner * factor
return lidar, gt_box3d