in datasets/scannet.py [0:0]
def __init__(self):
self.num_semcls = 18
self.num_angle_bin = 1
self.max_num_obj = 64
self.type2class = {
"cabinet": 0,
"bed": 1,
"chair": 2,
"sofa": 3,
"table": 4,
"door": 5,
"window": 6,
"bookshelf": 7,
"picture": 8,
"counter": 9,
"desk": 10,
"curtain": 11,
"refrigerator": 12,
"showercurtrain": 13,
"toilet": 14,
"sink": 15,
"bathtub": 16,
"garbagebin": 17,
}
self.class2type = {self.type2class[t]: t for t in self.type2class}
self.nyu40ids = np.array(
[3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16, 24, 28, 33, 34, 36, 39]
)
self.nyu40id2class = {
nyu40id: i for i, nyu40id in enumerate(list(self.nyu40ids))
}
# Semantic Segmentation Classes. Not used in 3DETR
self.num_class_semseg = 20
self.type2class_semseg = {
"wall": 0,
"floor": 1,
"cabinet": 2,
"bed": 3,
"chair": 4,
"sofa": 5,
"table": 6,
"door": 7,
"window": 8,
"bookshelf": 9,
"picture": 10,
"counter": 11,
"desk": 12,
"curtain": 13,
"refrigerator": 14,
"showercurtrain": 15,
"toilet": 16,
"sink": 17,
"bathtub": 18,
"garbagebin": 19,
}
self.class2type_semseg = {
self.type2class_semseg[t]: t for t in self.type2class_semseg
}
self.nyu40ids_semseg = np.array(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16, 24, 28, 33, 34, 36, 39]
)
self.nyu40id2class_semseg = {
nyu40id: i for i, nyu40id in enumerate(list(self.nyu40ids_semseg))
}