In [1]:

    

from lib.processors.modelnet10 import prepare


    

In [2]:

    

path2data = '/path/to/modelnet10'
path2save = '/path/to/directory/where/results/will/be/stored'

prepare(path2data, path2save)


    

    




bathtub - processed
bed - processed
chair - processed
desk - processed
dresser - processed
monitor - processed
night_stand - processed
sofa - processed
table - processed
toilet - processed

Data is processed and saved to /home/klokov/Data/ModelNet10_data//modelnet10.h5

class2label = {
    "bathtub": 0,
    "bed": 1,
    "chair": 2,
    "desk": 3,
    "dresser": 4,
    "monitor": 5,
    "night_stand": 6,
    "sofa": 7,
    "table": 8,
    "toilet": 9
}

In [1]:

    

from lib.processors.modelnet40 import prepare


    

In [ ]:

    

path2data = '/path/to/modelnet40'
path2save = '/path/to/directory/where/results/will/be/stored'

prepare(path2data, path2save)


    

    




airplane - processed
bathtub - processed
bed - processed
bench - processed
bookshelf - processed
bottle - processed
bowl - processed
car - processed
chair - processed
cone - processed
cup - processed
curtain - processed
desk - processed
door - processed
dresser - processed
flower_pot - processed
glass_box - processed
guitar - processed
keyboard - processed
lamp - processed
laptop - processed
mantel - processed
monitor - processed
night_stand - processed
person - processed
piano - processed
plant - processed
radio - processed
range_hood - processed
sink - processed
sofa - processed
stairs - processed
stool - processed
table - processed
tent - processed
toilet - processed
tv_stand - processed
vase - processed
wardrobe - processed
xbox - processed

Data is processed and saved to /home/klokov/Data/ModelNet40_data//modelnet40.h5

class2label = {
    "airplane": 0,
    "bathtub": 1,
    "bed": 2,
    "bench": 3,
    "bookshelf": 4,
    "bottle": 5,
    "bowl": 6,
    "car": 7,
    "chair": 8,
    "cone": 9,
    "cup": 10,
    "curtain": 11,
    "desk": 12,
    "door": 13,
    "dresser": 14,
    "flower_pot": 15,
    "glass_box": 16,
    "guitar": 17,
    "keyboard": 18,
    "lamp": 19,
    "laptop": 20,
    "mantel": 21,
    "monitor": 22,
    "night_stand": 23,
    "person": 24,
    "piano": 25,
    "plant": 26,
    "radio": 27,
    "range_hood": 28,
    "sink": 29,
    "sofa": 30,
    "stairs": 31,
    "stool": 32,
    "table": 33,
    "tent": 34,
    "toilet": 35,
    "tv_stand": 36,
    "vase": 37,
    "wardrobe": 38,
    "xbox": 39
}

In [1]:

    

from lib.processors.shapenet import prepare


    

In [2]:

    

path2data = '/path/to/shapenet'
path2save = '/path/to/directory/where/results/will/be/stored'
pose = 'normal'# or 'perturbed'

prepare(path2data, path2save, pose=pose)


    

    




Data is processed and saved to /home/klokov/Data/ShapeNet_data//shapenet_normal.h5

In [1]:

    

from lib.processors.shapenet_partanno import prepare


    

In [2]:

    

path2data = '/path/to/shapenet_partanno'
path2save = '/path/to/directory/where/results/will/be/stored'

prepare(path2data, path2save)


    

    




Data is processed and saved to /home/klokov/Data/ShapeNet_seg/shapenet_partanno.h5

label2name = {
    0: "Airplane",
    1: "Bag",
    2: "Cap",
    3: "Car",
    4: "Chair",
    5: "Earphone",
    6: "Guitar",
    7: "Knife",
    8: "Lamp",
    9: "Laptop",
    10: "Motorbike",
    11: "Mug",
    12: "Pistol",
    13: "Rocket",
    14: "Skateboard",
    15: "Table"
}

label2point_labels = {
    0: [0 1 2 3],
    1: [4 5],
    2: [6 7],
    3: [ 8  9 10 11],
    4: [12 13 14 15],
    5: [16 17 18],
    6: [19 20 21],
    7: [22 23],
    8: [24 25 26 27],
    9: [28 29],
    10: [30 31 32 33 34 35],
    11: [36 37],
    12: [38 39 40],
    13: [41 42 43],
    14: [44 45 46],
    15: [47 48 49]
}