np.asarray(lidar_3d.colors)[list(set(deleted))] = [1, 0, 0]
o3d.visualization.draw_geometries([lidar_3d])
return filtered
if __name__ == '__main__':
BASE = '/home/datasets/CADC/cadcd/'
BASE_mod = '/home/datasets_mod/CADC/cadcd/'
date = '2018_03_06'
seq = 16
frame = 38
lidar_type = 'aggregated' # raw, dror, aggregated
annotations_path = BASE + date + '/' + format(seq, '04') + "/3d_ann.json"
annotation = load_annotation(annotations_path)[frame]
calib_path = BASE + date + '/' + "calib"
calib = load_calibration(calib_path)
if lidar_type == 'raw':
lidar_path = BASE + date + '/' + format(seq, '04') + \
"/labeled/lidar_points/data/" + format(frame, '010') + ".bin"
lidar = np.fromfile(lidar_path, dtype= np.float32).reshape((-1, 4))[:,:3]
elif lidar_type == 'dror':
lidar_path = BASE_mod + date + '/' + format(seq, '04') + \
"/labeled/lidar_points/lidar_dror/" + format(frame, '010') + ".npy"
lidar = np.load(lidar_path).reshape((-1, 4))[:,:3]
elif lidar_type == 'aggregated':
lidar_path = BASE_mod + date + '/' + format(seq, '04') + \
"/labeled/lidar_points/lidar_aggregated/" + format(frame, '010') + ".npy"
assert n_aggregate % 2 == 1
show_3D = True
show_cam0 = False
show_allcam = False
# if show_cam0 or show_allcam:
# cmap = cm.get_cmap('jet')
# if show_cam0:
# _, ax_cam0 = plt.subplots(1, 3)
# if show_allcam:
# _, ax_allcam = plt.subplots(3, 8)
# Load 3d annotations
annotations_path = BASE + date + '/' + format(seq, '04') + "/3d_ann.json"
annotations = load_annotation(annotations_path)
# Load novatel IMU data
novatel_path = BASE + date + '/' + format(seq,
'04') + "/labeled/novatel/data/"
novatel = load_novatel_data(novatel_path)
poses = convert_novatel_to_pose(novatel)
# calib_path = BASE + date + '/' + "calib/"
# calib = load_calibration(calib_path)
lidars_no_mobile = []
for frame in range(len(annotations)):
lidar_no_mobile_path = BASE_mod + date + '/' + format(seq, '04') + "/labeled/lidar_points/lidar_no_mobile/" + \
format(frame, '010') + ".npy"
lidar_no_mobile = np.load(lidar_no_mobile_path).reshape((-1, 3))
if VISUALIZE:
import matplotlib.pyplot as plt
import matplotlib.cm as cm
plt.ion()
_, ax = plt.subplots(2, 2)
cmap = cm.get_cmap('jet')
for row in trange(start_row, len(cadc_stats)):
# print('\n------ Date %s, Sequence %d ------' % (cadc_stats.iloc[row, 0], cadc_stats.iloc[row, 1]))
date = cadc_stats.iloc[row, 0]
seq = cadc_stats.iloc[row, 1]
n_frame = cadc_stats.iloc[row, 2]
annotation_path = BASE + date + '/' + format(seq, '04') + "/3d_ann.json"
# Load 3d annotations
annotation = load_annotation(annotation_path)
calib_path = BASE + date + '/' + "calib/"
calib = load_calibration(calib_path)
T_CAM_LIDAR = []
T_IMG_CAM = []
for cam in range(8):
# Projection matrix from lidar to camera (extrinsics)
T_CAM_LIDAR.append(
np.linalg.inv(
np.array(calib['extrinsics']['T_LIDAR_CAM0' +
str(cam)]))[:3, :4])
# Projection matrix from camera to image (intrinsics)
T_IMG_CAM.append(
np.array(calib['CAM0' +
str(cam)]['camera_matrix']['data']).reshape(3, 3))