File size: 14,916 Bytes
bd77049
292fffb
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1566a98
 
 
 
 
 
 
 
 
 
 
0a59645
 
1566a98
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0a59645
 
 
 
 
bd77049
292fffb
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
---
annotations_creators:
- crowdsourced
license: cc-by-nc-sa-4.0
size_categories:
- 10K<n<100K
task_categories:
- image-classification
- image-feature-extraction
pretty_name: Galaxy Zoo UKIDSS
arxiv: 2404.02973
tags:
- galaxy zoo
- physics
- astronomy
- galaxies
- citizen science
configs:
- config_name: default
  data_files:
  - split: test
    path: data/test-*
  - split: train
    path: data/train-*
- config_name: tiny
  data_files:
  - split: train
    path: tiny/train-*
  - split: test
    path: tiny/test-*
dataset_info:
  config_name: tiny
  features:
  - name: image
    dtype: image
  - name: id_str
    dtype: string
  - name: dataset_name
    dtype: string
  - name: smooth-or-featured-ukidss_smooth
    dtype: int32
  - name: smooth-or-featured-ukidss_smooth_fraction
    dtype: float32
  - name: smooth-or-featured-ukidss_total-votes
    dtype: int32
  - name: smooth-or-featured-ukidss_featured-or-disk
    dtype: int32
  - name: smooth-or-featured-ukidss_featured-or-disk_fraction
    dtype: float32
  - name: smooth-or-featured-ukidss_artifact
    dtype: int32
  - name: smooth-or-featured-ukidss_artifact_fraction
    dtype: float32
  - name: disk-edge-on-ukidss_yes
    dtype: int32
  - name: disk-edge-on-ukidss_yes_fraction
    dtype: float32
  - name: disk-edge-on-ukidss_total-votes
    dtype: int32
  - name: disk-edge-on-ukidss_no
    dtype: int32
  - name: disk-edge-on-ukidss_no_fraction
    dtype: float32
  - name: has-spiral-arms-ukidss_yes
    dtype: int32
  - name: has-spiral-arms-ukidss_yes_fraction
    dtype: float32
  - name: has-spiral-arms-ukidss_total-votes
    dtype: int32
  - name: has-spiral-arms-ukidss_no
    dtype: int32
  - name: has-spiral-arms-ukidss_no_fraction
    dtype: float32
  - name: bar-ukidss_yes
    dtype: int32
  - name: bar-ukidss_yes_fraction
    dtype: float32
  - name: bar-ukidss_total-votes
    dtype: int32
  - name: bar-ukidss_no
    dtype: int32
  - name: bar-ukidss_no_fraction
    dtype: float32
  - name: bulge-size-ukidss_dominant
    dtype: int32
  - name: bulge-size-ukidss_dominant_fraction
    dtype: float32
  - name: bulge-size-ukidss_total-votes
    dtype: int32
  - name: bulge-size-ukidss_obvious
    dtype: int32
  - name: bulge-size-ukidss_obvious_fraction
    dtype: float32
  - name: bulge-size-ukidss_just-noticeable
    dtype: int32
  - name: bulge-size-ukidss_just-noticeable_fraction
    dtype: float32
  - name: bulge-size-ukidss_no
    dtype: int32
  - name: bulge-size-ukidss_no_fraction
    dtype: float32
  - name: something-odd-ukidss_yes
    dtype: int32
  - name: something-odd-ukidss_yes_fraction
    dtype: float32
  - name: something-odd-ukidss_total-votes
    dtype: int32
  - name: something-odd-ukidss_no
    dtype: int32
  - name: something-odd-ukidss_no_fraction
    dtype: float32
  - name: how-rounded-ukidss_round
    dtype: int32
  - name: how-rounded-ukidss_round_fraction
    dtype: float32
  - name: how-rounded-ukidss_total-votes
    dtype: int32
  - name: how-rounded-ukidss_in-between
    dtype: int32
  - name: how-rounded-ukidss_in-between_fraction
    dtype: float32
  - name: how-rounded-ukidss_cigar
    dtype: int32
  - name: how-rounded-ukidss_cigar_fraction
    dtype: float32
  - name: bulge-shape-ukidss_round
    dtype: int32
  - name: bulge-shape-ukidss_round_fraction
    dtype: float32
  - name: bulge-shape-ukidss_total-votes
    dtype: int32
  - name: bulge-shape-ukidss_boxy
    dtype: int32
  - name: bulge-shape-ukidss_boxy_fraction
    dtype: float32
  - name: bulge-shape-ukidss_no-bulge
    dtype: int32
  - name: bulge-shape-ukidss_no-bulge_fraction
    dtype: float32
  - name: spiral-winding-ukidss_tight
    dtype: int32
  - name: spiral-winding-ukidss_tight_fraction
    dtype: float32
  - name: spiral-winding-ukidss_total-votes
    dtype: int32
  - name: spiral-winding-ukidss_medium
    dtype: int32
  - name: spiral-winding-ukidss_medium_fraction
    dtype: float32
  - name: spiral-winding-ukidss_loose
    dtype: int32
  - name: spiral-winding-ukidss_loose_fraction
    dtype: float32
  - name: spiral-arm-count-ukidss_1
    dtype: int32
  - name: spiral-arm-count-ukidss_1_fraction
    dtype: float32
  - name: spiral-arm-count-ukidss_total-votes
    dtype: int32
  - name: spiral-arm-count-ukidss_2
    dtype: int32
  - name: spiral-arm-count-ukidss_2_fraction
    dtype: float32
  - name: spiral-arm-count-ukidss_3
    dtype: int32
  - name: spiral-arm-count-ukidss_3_fraction
    dtype: float32
  - name: spiral-arm-count-ukidss_4
    dtype: int32
  - name: spiral-arm-count-ukidss_4_fraction
    dtype: float32
  - name: spiral-arm-count-ukidss_more-than-4
    dtype: int32
  - name: spiral-arm-count-ukidss_more-than-4_fraction
    dtype: float32
  - name: spiral-arm-count-ukidss_cant-tell
    dtype: int32
  - name: spiral-arm-count-ukidss_cant-tell_fraction
    dtype: float32
  - name: summary
    dtype: string
  splits:
  - name: train
    num_bytes: 62935806.0
    num_examples: 566
  - name: test
    num_bytes: 15637560.0
    num_examples: 141
  download_size: 78648500
  dataset_size: 78573366.0
---

# GZ Campaign Datasets

## Dataset Summary

[Galaxy Zoo](www.galaxyzoo.org) volunteers label telescope images of galaxies according to their visible features: spiral arms, galaxy-galaxy collisions, and so on. 
These datasets share the galaxy images and volunteer labels in a machine-learning-friendly format. We use these datasets to train [our foundation models](https://arxiv.org/abs/2404.02973). We hope they'll help you too.

- **Curated by:** [Mike Walmsley](https://walmsley.dev/)
- **License:** [cc-by-nc-sa-4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en). We specifically require **all models trained on these datasets to be released as source code by publication**.

## Downloading

Install the Datasets library

    pip install datasets

and then log in to your HuggingFace account

    huggingface-cli login

All unpublished* datasets are temporarily "gated" i.e. you must have requested and been approved for access. Galaxy Zoo team members should go to https://huggingface.co/mwalmsley/datasets/gz_ukidss, click "request access", ping Mike, then wait for approval. 
Gating will be removed on publication.

*Currently: the `gz_h2o` and `gz_ukidss` datasets

## Usage

```python
from datasets import load_dataset

# . split='train' picks which split to load
dataset = load_dataset(
    'mwalmsley/gz_ukidss', # each dataset has a random fixed train/test split
    split='train'
     # some datasets also allow name=subset (e.g. name="tiny" for gz_evo). see the viewer for subset options
) 
dataset.set_format('torch')  # your framework of choice e.g. numpy, tensorflow, jax, etc
print(dataset_name, dataset[0]['image'].shape)
```

Then use the `dataset` object as with any other HuggingFace dataset, e.g., 

```python
from torch.utils.data import DataLoader

dataloader = DataLoader(ds, batch_size=4, num_workers=1)
for batch in dataloader:
    print(batch.keys()) 
    # the image key, plus a key counting the volunteer votes for each answer 
    # (e.g. smooth-or-featured-gz2_smooth)
    print(batch['image'].shape)
    break
```

You may find these HuggingFace docs useful:
- [PyTorch loading options](https://huggingface.co/docs/datasets/en/use_with_pytorch#data-loading).
- [Applying transforms/augmentations](https://huggingface.co/docs/datasets/en/image_process#apply-transforms).
- [Frameworks supported](https://huggingface.co/docs/datasets/v2.19.0/en/package_reference/main_classes#datasets.Dataset.set_format) by `set_format`.


## Dataset Structure

Each dataset is structured like:

```json
{
  'image': ..., # image of a galaxy
  'smooth-or-featured-[campaign]_smooth': 4,
  'smooth-or-featured-[campaign]_featured-or-disk': 12,
  ...  # and so on for many questions and answers
}
```

Images are loaded according to your `set_format` choice above. For example, ```set_format("torch")``` gives a (3, 424, 424) CHW `Torch.Tensor`.

The other keys are formatted like `[question]_[answer]`, where `question` is what the volunteers were asked (e.g. "smooth or featured?" and `answer` is the choice selected (e.g. "smooth"). **The values are the count of volunteers who selected each answer.** 

`question` is appended with a string noting in which Galaxy Zoo campaign this question was asked e.g. `smooth-or-featured-gz2`. For most datasets, all questions were asked during the same campaign. For GZ DESI, there are three campaigns (`dr12`, `dr5`, and `dr8`) with very similar questions.

GZ Evo combines all the published datasets (currently GZ2, GZ DESI, GZ CANDELS, GZ Hubble, and GZ UKIDSS) into a single dataset aimed at multi-task learning. This is helpful for [building models that adapt to new tasks and new telescopes]((https://arxiv.org/abs/2404.02973)).

(we will shortly add keys for the astronomical identifiers i.e. the sky coordinates and telescope source unique ids)


## Key Limitations

Because the volunteers are answering a decision tree, the questions asked depend on the previous answers, and so each galaxy and each question can have very different total numbers of votes. This interferes with typical metrics that use aggregated labels (e.g. classification of the most voted, regression on the mean vote fraction, etc.) because we have different levels of confidence in the aggregated labels for each galaxy. We suggest a custom loss to handle this. Please see the Datasets and Benchmarks paper for more details (under review, sorry).


All labels are imperfect. The vote counts may not always reflect the true appearance of each galaxy. Additionally,
the true appearance of each galaxy may be uncertain - even to expert astronomers.
We therefore caution against over-interpreting small changes in performance to indicate a method is "superior". **These datasets should not be used as a precise performance benchmark.**


## Citation Information

The machine-learning friendly versions of each dataset are described in a recently-submitted paper. Citation information will be added if accepted.

For each specific dataset you use, please also cite the original Galaxy Zoo data release paper (listed below) and the telescope description paper (cited therein).

### Galaxy Zoo 2

    @article{10.1093/mnras/stt1458,
    author = {Willett, Kyle W. and Lintott, Chris J. and Bamford, Steven P. and Masters, Karen L. and Simmons, Brooke D. and Casteels, Kevin R. V. and Edmondson, Edward M. and Fortson, Lucy F. and Kaviraj, Sugata and Keel, William C. and Melvin, Thomas and Nichol, Robert C. and Raddick, M. Jordan and Schawinski, Kevin and Simpson, Robert J. and Skibba, Ramin A. and Smith, Arfon M. and Thomas, Daniel},
    title = "{Galaxy Zoo 2: detailed morphological classifications for 304 122 galaxies from the Sloan Digital Sky Survey}",
    journal = {Monthly Notices of the Royal Astronomical Society},
    volume = {435},
    number = {4},
    pages = {2835-2860},
    year = {2013},
    month = {09},
    issn = {0035-8711},
    doi = {10.1093/mnras/stt1458},
}

### Galaxy Zoo Hubble

    @article{2017MNRAS.464.4176W,
    author = {Willett, Kyle W. and Galloway, Melanie A. and Bamford, Steven P. and Lintott, Chris J. and Masters, Karen L. and Scarlata, Claudia and Simmons, B.~D. and Beck, Melanie and {Cardamone}, Carolin N. and Cheung, Edmond and Edmondson, Edward M. and Fortson, Lucy F. and Griffith, Roger L. and H{\"a}u{\ss}ler, Boris and Han, Anna and Hart, Ross and Melvin, Thomas and Parrish, Michael and Schawinski, Kevin and Smethurst, R.~J. and {Smith}, Arfon M.},
    title = "{Galaxy Zoo: morphological classifications for 120 000 galaxies in HST legacy imaging}",
    journal = {Monthly Notices of the Royal Astronomical Society},
    year = 2017,
    month = feb,
    volume = {464},
    number = {4},
    pages = {4176-4203},
    doi = {10.1093/mnras/stw2568}
    }

### Galaxy Zoo CANDELS

    @article{10.1093/mnras/stw2587,
    author = {Simmons, B. D. and Lintott, Chris and Willett, Kyle W. and Masters, Karen L. and Kartaltepe, Jeyhan S. and Häußler, Boris and Kaviraj, Sugata and Krawczyk, Coleman and Kruk, S. J. and McIntosh, Daniel H. and Smethurst, R. J. and Nichol, Robert C. and Scarlata, Claudia and Schawinski, Kevin and Conselice, Christopher J. and Almaini, Omar and Ferguson, Henry C. and Fortson, Lucy and Hartley, William and Kocevski, Dale and Koekemoer, Anton M. and Mortlock, Alice and Newman, Jeffrey A. and Bamford, Steven P. and Grogin, N. A. and Lucas, Ray A. and Hathi, Nimish P. and McGrath, Elizabeth and Peth, Michael and Pforr, Janine and Rizer, Zachary and Wuyts, Stijn and Barro, Guillermo and Bell, Eric F. and Castellano, Marco and Dahlen, Tomas and Dekel, Avishai and Ownsworth, Jamie and Faber, Sandra M. and Finkelstein, Steven L. and Fontana, Adriano and Galametz, Audrey and Grützbauch, Ruth and Koo, David and Lotz, Jennifer and Mobasher, Bahram and Mozena, Mark and Salvato, Mara and Wiklind, Tommy},
    title = "{Galaxy Zoo: quantitative visual morphological classifications for 48 000 galaxies from CANDELS★}",
    journal = {Monthly Notices of the Royal Astronomical Society},
    volume = {464},
    number = {4},
    pages = {4420-4447},
    year = {2016},
    month = {10},
    doi = {10.1093/mnras/stw2587}
    }

### Galaxy Zoo DESI

 (two citations due to being released over two papers)

    @article{10.1093/mnras/stab2093,
    author = {Walmsley, Mike and Lintott, Chris and Géron, Tobias and Kruk, Sandor and Krawczyk, Coleman and Willett, Kyle W and Bamford, Steven and Kelvin, Lee S and Fortson, Lucy and Gal, Yarin and Keel, William and Masters, Karen L and Mehta, Vihang and Simmons, Brooke D and Smethurst, Rebecca and Smith, Lewis and Baeten, Elisabeth M and Macmillan, Christine},
    title = "{Galaxy Zoo DECaLS: Detailed visual morphology measurements from volunteers and deep learning for 314 000 galaxies}",
    journal = {Monthly Notices of the Royal Astronomical Society},
    volume = {509},
    number = {3},
    pages = {3966-3988},
    year = {2021},
    month = {09},
    issn = {0035-8711},
    doi = {10.1093/mnras/stab2093}
    }


    @article{10.1093/mnras/stad2919,
    author = {Walmsley, Mike and Géron, Tobias and Kruk, Sandor and Scaife, Anna M M and Lintott, Chris and Masters, Karen L and Dawson, James M and Dickinson, Hugh and Fortson, Lucy and Garland, Izzy L and Mantha, Kameswara and O’Ryan, David and Popp, Jürgen and Simmons, Brooke and Baeten, Elisabeth M and Macmillan, Christine},
    title = "{Galaxy Zoo DESI: Detailed morphology measurements for 8.7M galaxies in the DESI Legacy Imaging Surveys}",
    journal = {Monthly Notices of the Royal Astronomical Society},
    volume = {526},
    number = {3},
    pages = {4768-4786},
    year = {2023},
    month = {09},
    issn = {0035-8711},
    doi = {10.1093/mnras/stad2919}
    }


### Galaxy Zoo UKIDSS 

Not yet published.

### Galaxy Zoo Cosmic Dawn (a.k.a. H2O)


Not yet published.