object_id large_stringlengths 8 16 | class large_stringclasses 10
values | split large_stringclasses 1
value | object_path large_stringlengths 22 38 | __index_level_0__ int64 50 4.9k |
|---|---|---|---|---|
bathtub_0001 | bathtub | train | bathtub/train/bathtub_0001.off | 50 |
bathtub_0002 | bathtub | train | bathtub/train/bathtub_0002.off | 51 |
bathtub_0003 | bathtub | train | bathtub/train/bathtub_0003.off | 52 |
bathtub_0004 | bathtub | train | bathtub/train/bathtub_0004.off | 53 |
bathtub_0005 | bathtub | train | bathtub/train/bathtub_0005.off | 54 |
bathtub_0006 | bathtub | train | bathtub/train/bathtub_0006.off | 55 |
bathtub_0007 | bathtub | train | bathtub/train/bathtub_0007.off | 56 |
bathtub_0008 | bathtub | train | bathtub/train/bathtub_0008.off | 57 |
bathtub_0009 | bathtub | train | bathtub/train/bathtub_0009.off | 58 |
bathtub_0010 | bathtub | train | bathtub/train/bathtub_0010.off | 59 |
bathtub_0011 | bathtub | train | bathtub/train/bathtub_0011.off | 60 |
bathtub_0012 | bathtub | train | bathtub/train/bathtub_0012.off | 61 |
bathtub_0013 | bathtub | train | bathtub/train/bathtub_0013.off | 62 |
bathtub_0014 | bathtub | train | bathtub/train/bathtub_0014.off | 63 |
bathtub_0015 | bathtub | train | bathtub/train/bathtub_0015.off | 64 |
bathtub_0016 | bathtub | train | bathtub/train/bathtub_0016.off | 65 |
bathtub_0017 | bathtub | train | bathtub/train/bathtub_0017.off | 66 |
bathtub_0018 | bathtub | train | bathtub/train/bathtub_0018.off | 67 |
bathtub_0019 | bathtub | train | bathtub/train/bathtub_0019.off | 68 |
bathtub_0020 | bathtub | train | bathtub/train/bathtub_0020.off | 69 |
bathtub_0021 | bathtub | train | bathtub/train/bathtub_0021.off | 70 |
bathtub_0022 | bathtub | train | bathtub/train/bathtub_0022.off | 71 |
bathtub_0023 | bathtub | train | bathtub/train/bathtub_0023.off | 72 |
bathtub_0024 | bathtub | train | bathtub/train/bathtub_0024.off | 73 |
bathtub_0025 | bathtub | train | bathtub/train/bathtub_0025.off | 74 |
bathtub_0026 | bathtub | train | bathtub/train/bathtub_0026.off | 75 |
bathtub_0027 | bathtub | train | bathtub/train/bathtub_0027.off | 76 |
bathtub_0028 | bathtub | train | bathtub/train/bathtub_0028.off | 77 |
bathtub_0029 | bathtub | train | bathtub/train/bathtub_0029.off | 78 |
bathtub_0030 | bathtub | train | bathtub/train/bathtub_0030.off | 79 |
bathtub_0031 | bathtub | train | bathtub/train/bathtub_0031.off | 80 |
bathtub_0032 | bathtub | train | bathtub/train/bathtub_0032.off | 81 |
bathtub_0033 | bathtub | train | bathtub/train/bathtub_0033.off | 82 |
bathtub_0034 | bathtub | train | bathtub/train/bathtub_0034.off | 83 |
bathtub_0035 | bathtub | train | bathtub/train/bathtub_0035.off | 84 |
bathtub_0036 | bathtub | train | bathtub/train/bathtub_0036.off | 85 |
bathtub_0037 | bathtub | train | bathtub/train/bathtub_0037.off | 86 |
bathtub_0038 | bathtub | train | bathtub/train/bathtub_0038.off | 87 |
bathtub_0039 | bathtub | train | bathtub/train/bathtub_0039.off | 88 |
bathtub_0040 | bathtub | train | bathtub/train/bathtub_0040.off | 89 |
bathtub_0041 | bathtub | train | bathtub/train/bathtub_0041.off | 90 |
bathtub_0042 | bathtub | train | bathtub/train/bathtub_0042.off | 91 |
bathtub_0043 | bathtub | train | bathtub/train/bathtub_0043.off | 92 |
bathtub_0044 | bathtub | train | bathtub/train/bathtub_0044.off | 93 |
bathtub_0045 | bathtub | train | bathtub/train/bathtub_0045.off | 94 |
bathtub_0046 | bathtub | train | bathtub/train/bathtub_0046.off | 95 |
bathtub_0047 | bathtub | train | bathtub/train/bathtub_0047.off | 96 |
bathtub_0048 | bathtub | train | bathtub/train/bathtub_0048.off | 97 |
bathtub_0049 | bathtub | train | bathtub/train/bathtub_0049.off | 98 |
bathtub_0050 | bathtub | train | bathtub/train/bathtub_0050.off | 99 |
bathtub_0051 | bathtub | train | bathtub/train/bathtub_0051.off | 100 |
bathtub_0052 | bathtub | train | bathtub/train/bathtub_0052.off | 101 |
bathtub_0053 | bathtub | train | bathtub/train/bathtub_0053.off | 102 |
bathtub_0054 | bathtub | train | bathtub/train/bathtub_0054.off | 103 |
bathtub_0055 | bathtub | train | bathtub/train/bathtub_0055.off | 104 |
bathtub_0056 | bathtub | train | bathtub/train/bathtub_0056.off | 105 |
bathtub_0057 | bathtub | train | bathtub/train/bathtub_0057.off | 106 |
bathtub_0058 | bathtub | train | bathtub/train/bathtub_0058.off | 107 |
bathtub_0059 | bathtub | train | bathtub/train/bathtub_0059.off | 108 |
bathtub_0060 | bathtub | train | bathtub/train/bathtub_0060.off | 109 |
bathtub_0061 | bathtub | train | bathtub/train/bathtub_0061.off | 110 |
bathtub_0062 | bathtub | train | bathtub/train/bathtub_0062.off | 111 |
bathtub_0063 | bathtub | train | bathtub/train/bathtub_0063.off | 112 |
bathtub_0064 | bathtub | train | bathtub/train/bathtub_0064.off | 113 |
bathtub_0065 | bathtub | train | bathtub/train/bathtub_0065.off | 114 |
bathtub_0066 | bathtub | train | bathtub/train/bathtub_0066.off | 115 |
bathtub_0067 | bathtub | train | bathtub/train/bathtub_0067.off | 116 |
bathtub_0068 | bathtub | train | bathtub/train/bathtub_0068.off | 117 |
bathtub_0069 | bathtub | train | bathtub/train/bathtub_0069.off | 118 |
bathtub_0070 | bathtub | train | bathtub/train/bathtub_0070.off | 119 |
bathtub_0071 | bathtub | train | bathtub/train/bathtub_0071.off | 120 |
bathtub_0072 | bathtub | train | bathtub/train/bathtub_0072.off | 121 |
bathtub_0073 | bathtub | train | bathtub/train/bathtub_0073.off | 122 |
bathtub_0074 | bathtub | train | bathtub/train/bathtub_0074.off | 123 |
bathtub_0075 | bathtub | train | bathtub/train/bathtub_0075.off | 124 |
bathtub_0076 | bathtub | train | bathtub/train/bathtub_0076.off | 125 |
bathtub_0077 | bathtub | train | bathtub/train/bathtub_0077.off | 126 |
bathtub_0078 | bathtub | train | bathtub/train/bathtub_0078.off | 127 |
bathtub_0079 | bathtub | train | bathtub/train/bathtub_0079.off | 128 |
bathtub_0080 | bathtub | train | bathtub/train/bathtub_0080.off | 129 |
bathtub_0081 | bathtub | train | bathtub/train/bathtub_0081.off | 130 |
bathtub_0082 | bathtub | train | bathtub/train/bathtub_0082.off | 131 |
bathtub_0083 | bathtub | train | bathtub/train/bathtub_0083.off | 132 |
bathtub_0084 | bathtub | train | bathtub/train/bathtub_0084.off | 133 |
bathtub_0085 | bathtub | train | bathtub/train/bathtub_0085.off | 134 |
bathtub_0086 | bathtub | train | bathtub/train/bathtub_0086.off | 135 |
bathtub_0087 | bathtub | train | bathtub/train/bathtub_0087.off | 136 |
bathtub_0088 | bathtub | train | bathtub/train/bathtub_0088.off | 137 |
bathtub_0089 | bathtub | train | bathtub/train/bathtub_0089.off | 138 |
bathtub_0090 | bathtub | train | bathtub/train/bathtub_0090.off | 139 |
bathtub_0091 | bathtub | train | bathtub/train/bathtub_0091.off | 140 |
bathtub_0092 | bathtub | train | bathtub/train/bathtub_0092.off | 141 |
bathtub_0093 | bathtub | train | bathtub/train/bathtub_0093.off | 142 |
bathtub_0094 | bathtub | train | bathtub/train/bathtub_0094.off | 143 |
bathtub_0095 | bathtub | train | bathtub/train/bathtub_0095.off | 144 |
bathtub_0096 | bathtub | train | bathtub/train/bathtub_0096.off | 145 |
bathtub_0097 | bathtub | train | bathtub/train/bathtub_0097.off | 146 |
bathtub_0098 | bathtub | train | bathtub/train/bathtub_0098.off | 147 |
bathtub_0099 | bathtub | train | bathtub/train/bathtub_0099.off | 148 |
bathtub_0100 | bathtub | train | bathtub/train/bathtub_0100.off | 149 |
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ModelNet10
ModelNet10 is a subset of ModelNet with 10 object categories of 3D CAD models, widely used for shape classification and point-cloud experiments. This repository packages the meshes as OFF files with a CSV index for use with the Hugging Face datasets library.
Dataset structure
metadata_modelnet10.csv— index with columns:object_id,class,split,object_pathModelNet10/— mesh files (.off) organized by category and split
Each example exposes string fields object_id, class, split, and file_path (absolute path to the .off file after resolution).
Usage
Load from the Hub (downloads and caches on first use):
from datasets import load_dataset
ds = load_dataset("naderalfares/ModelNet10")
Load from a local directory that contains metadata_modelnet10.csv and the ModelNet10/ folder:
from datasets import load_dataset
ds = load_dataset(
"path/to/modelnet10.py",
name="default",
data_dir="path/to/ModelNet10",
)
Access splits:
train = ds["train"]
row = train[0]
print(row["class"], row["file_path"])
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