Meta Album Birds Dataset: 800 Images of 20 Bird Species

800 images of birds across 20 species, preprocessed to a resolution of 128x128 pixels. The dataset is derived from a larger Kaggle collection originally containing over 49,000 images of 315 species. It was created by Dustin Carrion for the Meta-Album project in March 2022.

Use Cases

• Benchmarking few-shot learning algorithms based on the standardized 20-class subset.
• Training image classifiers for bird species identification based on the provided 128x128 pixel images.
• Studying dataset bias in natural image backgrounds based on the description mentioning backgrounds can lead to bias.
• Analyzing class imbalance in visual datasets based on the description mentioning imbalance in male-to-female image ratios.

Strengths

• Contains 800 images across 20 distinct classes, providing a defined scale for experiments.
• Images are uniformly preprocessed to a resolution of 128x128 pixels, ensuring consistent input size.
• Derived from a larger source dataset with over 49,000 images, suggesting a foundation of real-world data.

Limitations

• The dataset is described as imbalanced regarding the ratio of male to female species images.
• Images retain natural backgrounds which, according to the description, can lead to bias.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Kaggle dataset 'BIRDS 400 - SPECIES IMAGE CLASSIFICATION' by Gerald Piosenka.

Collection Method

Preprocessed (resized) subset created for the Meta-Album benchmark collection.