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README.md

@@ -1,301 +1,202 @@
 ---
-dataset_info:
-- config_name: all
-  features:
-  - name: image
-    dtype: image
-  - name: smooth-or-featured-gz2_smooth
-    dtype: int32
-  - name: smooth-or-featured-gz2_featured-or-disk
-    dtype: int32
-  - name: smooth-or-featured-gz2_artifact
-    dtype: int32
-  - name: disk-edge-on-gz2_yes
-    dtype: int32
-  - name: disk-edge-on-gz2_no
-    dtype: int32
-  - name: has-spiral-arms-gz2_yes
-    dtype: int32
-  - name: has-spiral-arms-gz2_no
-    dtype: int32
-  - name: bar-gz2_yes
-    dtype: int32
-  - name: bar-gz2_no
-    dtype: int32
-  - name: bulge-size-gz2_dominant
-    dtype: int32
-  - name: bulge-size-gz2_obvious
-    dtype: int32
-  - name: bulge-size-gz2_just-noticeable
-    dtype: int32
-  - name: bulge-size-gz2_no
-    dtype: int32
-  - name: something-odd-gz2_yes
-    dtype: int32
-  - name: something-odd-gz2_no
-    dtype: int32
-  - name: how-rounded-gz2_round
-    dtype: int32
-  - name: how-rounded-gz2_in-between
-    dtype: int32
-  - name: how-rounded-gz2_cigar
-    dtype: int32
-  - name: bulge-shape-gz2_round
-    dtype: int32
-  - name: bulge-shape-gz2_boxy
-    dtype: int32
-  - name: bulge-shape-gz2_no-bulge
-    dtype: int32
-  - name: spiral-winding-gz2_tight
-    dtype: int32
-  - name: spiral-winding-gz2_medium
-    dtype: int32
-  - name: spiral-winding-gz2_loose
-    dtype: int32
-  - name: spiral-arm-count-gz2_1
-    dtype: int32
-  - name: spiral-arm-count-gz2_2
-    dtype: int32
-  - name: spiral-arm-count-gz2_3
-    dtype: int32
-  - name: spiral-arm-count-gz2_4
-    dtype: int32
-  - name: spiral-arm-count-gz2_more-than-4
-    dtype: int32
-  - name: spiral-arm-count-gz2_cant-tell
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 2256229125.75
-    num_examples: 166850
-  - name: test
-    num_bytes: 569483438.048
-    num_examples: 41713
-  download_size: 2837900425
-  dataset_size: 2825712563.798
-- config_name: evo
-  features:
-  - name: image
-    dtype: image
-  - name: smooth-or-featured-gz2_smooth
-    dtype: int32
-  - name: smooth-or-featured-gz2_featured-or-disk
-    dtype: int32
-  - name: smooth-or-featured-gz2_artifact
-    dtype: int32
-  - name: disk-edge-on-gz2_yes
-    dtype: int32
-  - name: disk-edge-on-gz2_no
-    dtype: int32
-  - name: has-spiral-arms-gz2_yes
-    dtype: int32
-  - name: has-spiral-arms-gz2_no
-    dtype: int32
-  - name: bar-gz2_yes
-    dtype: int32
-  - name: bar-gz2_no
-    dtype: int32
-  - name: bulge-size-gz2_dominant
-    dtype: int32
-  - name: bulge-size-gz2_obvious
-    dtype: int32
-  - name: bulge-size-gz2_just-noticeable
-    dtype: int32
-  - name: bulge-size-gz2_no
-    dtype: int32
-  - name: something-odd-gz2_yes
-    dtype: int32
-  - name: something-odd-gz2_no
-    dtype: int32
-  - name: how-rounded-gz2_round
-    dtype: int32
-  - name: how-rounded-gz2_in-between
-    dtype: int32
-  - name: how-rounded-gz2_cigar
-    dtype: int32
-  - name: bulge-shape-gz2_round
-    dtype: int32
-  - name: bulge-shape-gz2_boxy
-    dtype: int32
-  - name: bulge-shape-gz2_no-bulge
-    dtype: int32
-  - name: spiral-winding-gz2_tight
-    dtype: int32
-  - name: spiral-winding-gz2_medium
-    dtype: int32
-  - name: spiral-winding-gz2_loose
-    dtype: int32
-  - name: spiral-arm-count-gz2_1
-    dtype: int32
-  - name: spiral-arm-count-gz2_2
-    dtype: int32
-  - name: spiral-arm-count-gz2_3
-    dtype: int32
-  - name: spiral-arm-count-gz2_4
-    dtype: int32
-  - name: spiral-arm-count-gz2_more-than-4
-    dtype: int32
-  - name: spiral-arm-count-gz2_cant-tell
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 2315617466.771
-    num_examples: 172377
-  - name: test
-    num_bytes: 257291889.006
-    num_examples: 18797
-  download_size: 2589561260
-  dataset_size: 2572909355.777
-configs:
-- config_name: all
-  data_files:
-  - split: train
-    path: all/train-*
-  - split: test
-    path: all/test-*
-- config_name: evo
-  default: true
-  data_files:
-  - split: train
-    path: evo/train-*
-  - split: test
-    path: evo/test-*
+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 2
+arxiv: 2404.02973
+tags:
+- galaxy zoo
+- physics
+- astronomy
+- galaxies
+- citizen science
 ---
 
-# Dataset Card for Dataset Name
+# GZ Campaign Datasets
 
-<!-- Provide a quick summary of the dataset. -->
+## Dataset Summary
 
-This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
+[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.
 
-## Dataset Details
+- **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**.
 
-### Dataset Description
+## Downloading
 
-<!-- Provide a longer summary of what this dataset is. -->
+Install the Datasets library
 
+    pip install datasets
 
+and then log in to your HuggingFace account
 
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
+    huggingface-cli login
 
-### Dataset Sources [optional]
+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/gz2, click "request access", ping Mike, then wait for approval. 
+Gating will be removed on publication.
 
-<!-- Provide the basic links for the dataset. -->
+*Currently: the `gz_h2o` and `gz_ukidss` datasets
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+## Usage
 
-## Uses
+```python
+from datasets import load_dataset
 
-<!-- Address questions around how the dataset is intended to be used. -->
+# . split='train' picks which split to load
+dataset = load_dataset(
+    'mwalmsley/gz2', # 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)
+```
 
-### Direct Use
+Then use the `dataset` object as with any other HuggingFace dataset, e.g., 
 
-<!-- This section describes suitable use cases for the dataset. -->
+```python
+from torch.utils.data import DataLoader
 
-[More Information Needed]
+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
+```
 
-### Out-of-Scope Use
+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`.
 
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-
-[More Information Needed]
 
 ## Dataset Structure
 
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
-
-[More Information Needed]
-
-## Dataset Creation
-
-### Curation Rationale
-
-<!-- Motivation for the creation of this dataset. -->
-
-[More Information Needed]
-
-### Source Data
-
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-
-#### Data Collection and Processing
-
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-
-[More Information Needed]
-
-#### Who are the source data producers?
-
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-
-[More Information Needed]
-
-### Annotations [optional]
+Each dataset is structured like:
 
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
+```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`.
 
-#### Annotation process
+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.** 
 
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
+`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.
 
-[More Information Needed]
+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)).
 
-#### Who are the annotators?
+(we will shortly add keys for the astronomical identifiers i.e. the sky coordinates and telescope source unique ids)
 
-<!-- This section describes the people or systems who created the annotations. -->
 
-[More Information Needed]
+## Key Limitations
 
-#### Personal and Sensitive Information
+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).
 
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
 
-[More Information Needed]
+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.**
 
-## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+## Citation Information
 
-[More Information Needed]
+The machine-learning friendly versions of each dataset are described in a recently-submitted paper. Citation information will be added if accepted.
 
-### Recommendations
+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).
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+### Galaxy Zoo 2
 
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
+    @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},
+}
 
-## Citation [optional]
+### Galaxy Zoo Hubble
 
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+    @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}
+    }
 
-**BibTeX:**
+### Galaxy Zoo CANDELS
 
-[More Information Needed]
+    @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}
+    }
 
-**APA:**
+### Galaxy Zoo DESI
 
-[More Information Needed]
+ (two citations due to being released over two papers)
 
-## Glossary [optional]
+    @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}
+    }
 
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
 
-[More Information Needed]
+    @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}
+    }
 
-## More Information [optional]
 
-[More Information Needed]
+### Galaxy Zoo UKIDSS 
 
-## Dataset Card Authors [optional]
+Not yet published.
 
-[More Information Needed]
+### Galaxy Zoo Cosmic Dawn (a.k.a. H2O)
 
-## Dataset Card Contact
 
-[More Information Needed]
+Not yet published.