Datasets:

HairCS2027
/

HairCS

Error code:   DatasetGenerationError
Exception:    UnicodeDecodeError
Message:      'utf-8' codec can't decode byte 0x89 in position 0: invalid start byte
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/csv/csv.py", line 196, in _generate_tables
                  csv_file_reader = pd.read_csv(file, iterator=True, dtype=dtype, **self.config.pd_read_csv_kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/streaming.py", line 73, in wrapper
                  return function(*args, download_config=download_config, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1279, in xpandas_read_csv
                  return pd.read_csv(xopen(filepath_or_buffer, "rb", download_config=download_config), **kwargs)
                         ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1026, in read_csv
                  return _read(filepath_or_buffer, kwds)
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 620, in _read
                  parser = TextFileReader(filepath_or_buffer, **kwds)
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1620, in __init__
                  self._engine = self._make_engine(f, self.engine)
                                 ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/readers.py", line 1898, in _make_engine
                  return mapping[engine](f, **self.options)
                         ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 93, in __init__
                  self._reader = parsers.TextReader(src, **kwds)
                                 ~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "pandas/_libs/parsers.pyx", line 574, in pandas._libs.parsers.TextReader.__cinit__
                File "pandas/_libs/parsers.pyx", line 663, in pandas._libs.parsers.TextReader._get_header
                File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
                File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
                File "pandas/_libs/parsers.pyx", line 2053, in pandas._libs.parsers.raise_parser_error
                File "<frozen codecs>", line 325, in decode
              UnicodeDecodeError: 'utf-8' codec can't decode byte 0x89 in position 0: invalid start byte
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

number int64	class string
0	long
1	long
2	long
3	bob
4	long
5	short
6	long
7	long
8	shoulder
9	long
10	bob
11	bob
12	long
13	gather
14	long
15	long
16	long
17	long
18	gather
19	shoulder
20	short
21	long
22	long
23	long
24	long
25	long
26	long
27	long
28	short
29	long
30	short
31	bob
32	long
33	long
34	gather
35	long
36	short
37	gather
38	gather
39	long
40	gather
41	shoulder
42	gather
43	shoulder
44	long
45	long
46	long
47	gather
48	gather
49	gather
50	bob
51	gather
52	long
53	long
54	gather
55	long
56	shoulder
57	shoulder
58	long
59	long
60	long
61	short
62	long
63	bob
64	short
65	bob
66	gather
67	short
68	long
69	long
70	long
71	shoulder
72	long
73	bob
74	shoulder
75	gather
76	bob
77	long
78	long
79	long
80	bob
81	shoulder
82	gather
83	long
84	short
85	shoulder
86	short
87	short
88	short
89	gather
90	long
91	gather
92	bob
93	bob
94	bob
95	gather
96	gather
97	bob
98	long
99	gather

End of preview.

HairCS

HairCS is a strand-based hair dataset: 53,336 hair assets in 13 versions, each stored as a point cloud of 60,000 strands x 64 samples (xyz, float16), plus a rendered preview image of every asset, per-asset hairstyle labels, the head/scalp geometry the hair is grown on, and a small Python toolkit (viewer and strand-to-surface conversion).

All versions share the same head and the same coordinate frame (see meta/).

Versions

Version	Assets	Description
`v0`	1,076	Base hair
`v1`	1,076	`v0` + scale and fuzz modifier
`v2`	818	Curly profile 1
`v3`	844	Curly profile 2
`v4`	650	Curly + scale and fuzz modifier
`v5`	1,539	Blend: bob (`00000`-`00065`) and shoulder (`00066`-`01538`)
`v6`	1,539	`v5` + curly profile 1
`v7`	6,086	Blend: shoulder
`v8`	6,086	`v7` + curly profile 1
`v9`	8,585	Blend: short
`v10`	8,585	`v9` + curly profile 1
`v11`	8,226	Blend: long
`v12`	8,226	`v11` + curly profile 1

Terminology:

Blend – assets produced with the hair blending method described in the paper.
Curly profile 1 – the helix operator from the paper, with its first parameter profile.
Curly profile 2 – the helix operator with a second parameter profile.
Scale and fuzz modifier – per-strand scaling plus a fuzz perturbation applied on top of the base hair.

Repository layout

data/vN/XXXXX.npz        one asset per file, key "P": (60000, 64, 3) float16, samples ordered root -> tip
render/vN.zip            one PNG preview per asset, named XXXX.png (4-digit index, same order as data/vN)
label/vN.csv             hairstyle class per asset (columns: number,class)
meta/                    head and scalp geometry shared by all versions (OBJ)
  full_body_geo.obj
  head_water_tight_boundary.obj
  head_with_uv.obj
  scalp_with_uv.obj
argument/                viewer + strand-to-surface tools (see argument/README.md)

Every data/vN/ folder holds exactly the number of assets listed in the table, numbered 00000 to N-1.

Loading an asset

import numpy as np

d = np.load("data/v0/00000.npz")
P = d["P"].astype(np.float32)     # (60000, 64, 3): 60000 strands, 64 samples per strand, xyz
roots, tips = P[:, 0], P[:, -1]   # samples are ordered root -> tip

The head meshes in meta/ are in the same coordinate frame as the strands, so an asset can be placed on head_with_uv.obj or scalp_with_uv.obj without any transform.

Labels

label/vN.csv gives one hairstyle class per asset:

Class	Meaning
`short`	short hair
`bob`	bob cut
`shoulder`	shoulder-length hair
`long`	long hair
`gather`	gathered / tied-back hair

For v0-v6 the classes were assigned per asset. For v7-v12 every asset of a version shares the class of the blend target of that version (v7/v8: shoulder, v9/v10: short, v11/v12: long).

Downloading

The full dataset is about 963 GB. Fetch only what you need with --include:

pip install -U huggingface_hub
hf download HairCS2027/HairCS --repo-type dataset --local-dir HairCS \
    --include "meta/*" "label/*" "argument/*"            # small files, ~25 MB
hf download HairCS2027/HairCS --repo-type dataset --local-dir HairCS \
    --include "data/v4/*" "render/v4.zip"                 # one version, ~11 GB

Folder	Size
`data/`	~932 GB (13 versions, 10 to 154 GB each)
`render/`	~31 GB (13 zips, 0.3 to 7 GB each)
`meta/`, `label/`, `argument/`	< 25 MB

Tools

argument/ contains a strand viewer (run_viewer.py) and a tool that wraps an asset in a watertight mesh (run_strand2surface.py, with a batch runner and optional GPU path). Usage and the expected on-disk layout are described in argument/README.md.

License

CC BY-NC 4.0. Non-commercial use only.

Citation

The accompanying paper is under review. A citation entry will be added on publication.

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Total file size:

963 GB