Deep Feature Interpolation for Image Content Changes
Paper • 1611.05507 • Published
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: ValueError
Message: Invalid string class label edu-manufold-images@c36b086b73961f80e426ff7d499f073be663b5f6
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2368, in __iter__
example = _apply_feature_types_on_example(
example, self.features, token_per_repo_id=self.token_per_repo_id
)
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2285, in _apply_feature_types_on_example
encoded_example = features.encode_example(example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 2162, in encode_example
return encode_nested_example(self, example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1446, in encode_nested_example
{k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1469, in encode_nested_example
return schema.encode_example(obj) if obj is not None else None
~~~~~~~~~~~~~~~~~~~~~^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1144, in encode_example
example_data = self.str2int(example_data)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1081, in str2int
output = [self._strval2int(value) for value in values]
~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1102, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label edu-manufold-images@c36b086b73961f80e426ff7d499f073be663b5f6Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
EDU Manufold Images
Kurirani podskupovi za edukativni notebook EDU-manufold.ipynb (Deep Feature Interpolation, Upchurch et al., CVPR 2017 — https://arxiv.org/abs/1611.05507).
| Folder | n | Izvor | Kriterijum |
|---|---|---|---|
young/ |
100 | UTKFace (Aligned & Cropped) | starost 18–30, balansirano po polu |
old/ |
100 | UTKFace (Aligned & Cropped) | starost 65+, balansirano po polu |
day/ |
50 | Transient Attributes | daylight > 0.8, night < 0.1 |
night/ |
50 | Transient Attributes | night > 0.8, daylight < 0.1 |
autumn/ |
50 | Transient Attributes | autumn > 0.7, winter < 0.2, snow < 0.1 |
winter/ |
50 | Transient Attributes | winter > 0.7, snow > 0.6, autumn < 0.2 |
Day/night i autumn/winter parovi su birani sa istih webkamera (isti kadar), tako da razlika prosečnih featurea nosi atribut, a ne kompoziciju scene. Scene su smanjene na max 400 px. Izbor je deterministički (seed 0).
Izvorni datasetovi i licence
- UTKFace — Zhang, Song, Qi: Age Progression/Regression by Conditional Adversarial Autoencoder, CVPR 2017. https://susanqq.github.io/UTKFace/ — dostupno isključivo za nekomercijalna istraživanja; ista ograničenja važe i za ovaj podskup.
- Transient Attributes — Laffont, Ren, Tao, Qian, Hays: Transient Attributes for High-Level Understanding and Editing of Outdoor Scenes, SIGGRAPH 2014. http://transattr.cs.brown.edu/
Ovaj repo je isključivo edukativni; sva prava na slike pripadaju izvornim autorima/datasetovima.
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