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# Dataset Card for Animals with Attributes 2 (AwA2) |
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<!-- Provide a quick summary of the dataset. --> |
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## Dataset Details |
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### Dataset Description |
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<!-- Provide a longer summary of what this dataset is. --> |
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The Animals with Attributes 2 (AwA2) dataset is originally designed for zero-shot learning (ZSL), transfer learning, and attribute-based classification. It consists of 37,322 images across 50 animal classes, making it a widely used benchmark for recognizing unseen categories using shared semantic attributes. |
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However, in our repository, we use AwA2 as a standard image classification dataset, focusing on image-label pairs rather than attribute-based learning. The dataset provides images with their respective animal class labels, enabling supervised learning and evaluation of traditional deep learning models. |
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- **License:** Public domain images with individual license files in the archive. |
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### Dataset Sources |
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<!-- Provide the basic links for the dataset. --> |
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- **Homepage:** https://cvml.ista.ac.at/AwA2/ |
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- **Paper:** Xian, Y., Lampert, C. H., Schiele, B., & Akata, Z. (2018). Zero-shot learning—a comprehensive evaluation of the good, the bad and the ugly. IEEE transactions on pattern analysis and machine intelligence, 41(9), 2251-2265. |
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## Dataset Structure |
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<!-- 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. --> |
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Total images: 37,322 |
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Classes: 50 animal categories |
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Image specs: JPEG format, RGB images |
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Class Labels: antelope, grizzly bear, killer whale, beaver, dalmatian, persian cat, horse, german shepherd, blue whale, siamese cat, skunk, mole, tiger, hippopotamus, leopard, moose, spider monkey, humpback whale, elephant, gorilla, ox, fox, sheep, seal, chimpanzee, hamster, squirrel, rhinoceros, rabbit, bat, giraffe, wolf, chihuahua, rat, weasel, otter, buffalo, zebra, giant panda, deer, bobcat, pig, lion, mouse, polar bear, collie, walrus, raccoon, cow, dolphin. |
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## Example Usage |
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Below is a quick example of how to load this dataset via the Hugging Face Datasets library. |
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``` |
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from datasets import load_dataset |
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# Load the dataset |
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dataset = load_dataset("randall-lab/awa2", split="test", trust_remote_code=True) |
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# Access a sample from the dataset |
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example = dataset[0] |
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image = example["image"] |
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label = example["label"] |
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image.show() # Display the image |
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print(f"Label: {label}") |
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``` |
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## Citation |
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<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> |
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**BibTeX:** |
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@article{xian2018zero, |
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title={Zero-shot learning—a comprehensive evaluation of the good, the bad and the ugly}, |
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author={Xian, Yongqin and Lampert, Christoph H and Schiele, Bernt and Akata, Zeynep}, |
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journal={IEEE transactions on pattern analysis and machine intelligence}, |
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volume={41}, |
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number={9}, |
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pages={2251--2265}, |
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year={2018}, |
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publisher={IEEE} |
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} |
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