def __init__(self,
path_to_data,
sigma=0,
img_size=(480, 640),
split='test',
mvg_aug=False,
align_flag=True):
self.name = 'nogt'
self.root = os.path.expanduser(path_to_data)
self.split = 'test'
self.files = collections.defaultdict(list)
self.img_size = img_size
self.perform_calib = True
for split in ['test']:
path = pjoin(self.root, split + '_list.txt')
file_list = tuple(open(path, 'r'))
file_list = [id_.rstrip() for id_ in file_list]
self.files[split] = file_list
self.len = len(self.files[self.split])
self.warp_by_flow = warp_by_flow(img_size[0], img_size[1], 1)
flen = 520 #camparam[param_depth]['fx']
norm = plane_correction(flen, img_size, False)
# norm = np.expand_dims(norm, 2)
self.plane_correction = norm
def __init__(self,
path_to_data,
sigma=0,
split='train',
img_size=(480, 640),
mvg_aug=True,
align_flag=False):
self.use_sigma = False
if sigma > 0:
self.use_sigma = True
self.name = 'simtof'
self.root = os.path.expanduser(path_to_data)
self.split = split
self.files = collections.defaultdict(list)
self.img_size = img_size
self.mvg_aug = mvg_aug
self.align = align_flag
### set paths ####
if self.align or self.mvg_aug:
self.gt_path = 'gt_depth_rgb/'
else:
self.gt_path = 'gt_depth_rgb_small_pt/'
### end set paths ###
for split in ['train', 'test']:
path = pjoin(self.root, split + '_list.txt')
file_list = tuple(open(path, 'r'))
file_list = [id_.rstrip() for id_ in file_list]
self.files[split] = file_list
camparam = param_buffer(path_to_data + 'calib.bin')
camparam = adjust_rotation(camparam, [1, 0, 0, 0, 1, 0, 0, 0, 1])
camparam = adjust_translation(camparam, [0, 0, 0])
camparam = adjust_distorsion(camparam, 0, 0)
self.camparam = camparam
rototrans_instance = RotoTransParam()
self.avgrot = rototrans_instance.avgrot
self.avgprpt = rototrans_instance.avgprpt
self.avgtrans = rototrans_instance.avgtrans
print(img_size)
self.warp_by_flow = warp_by_flow(img_size[0], img_size[1], 1)
norm = plane_correction(63.5, img_size)
# norm = np.expand_dims(norm, 2)
self.plane_correction = norm
self.sigma = sigma
self.len = len(self.files[self.split])
def __init__(self,
path_to_data,
sigma=0,
split='train',
img_size=(480, 640),
mvg_aug=True,
align_flag=False):
self.use_sigma = False
if sigma > 0:
self.use_sigma = True,
self.name = 'real'
self.root = os.path.expanduser(path_to_data +
'RealData/vivo_data/test_vivo5/')
self.split = split
self.files = collections.defaultdict(list)
self.img_size = img_size
self.mvg_aug = mvg_aug
self.align = align_flag
for split in ['train', 'test']:
path = pjoin(self.root, split + '_list.txt')
file_list = tuple(open(path, 'r'))
file_list = [id_.rstrip() for id_ in file_list]
self.files[split] = file_list
camparam = param_buffer_st(self.root + 'calib_verify.bin')
camparam = adjust_rotation(camparam, [1, 0, 0, 0, 1, 0, 0, 0, 1])
camparam = adjust_translation(camparam, [0, 0, 0])
camparam = adjust_distorsion(camparam, 0, 0)
self.path_to_data = path_to_data
self.camparam = camparam
rototrans_instance = RotoTransParam()
self.avgrot = rototrans_instance.avgrot
self.avgprpt = rototrans_instance.avgprpt
self.avgtrans = rototrans_instance.avgtrans
self.warp_by_flow = warp_by_flow(img_size[0], img_size[1], 1)
flen = 520 #camparam[param_depth]['fx']
norm = plane_correction(flen, img_size, False)
# norm = np.expand_dims(norm, 2)
self.plane_correction = norm
self.sigma = sigma
self.len = len(self.files[self.split])