metadata

license: mit
task_categories:
  - image-classification
language:
  - en
tags:
  - biology
  - birds
  - fine-grained image classification
  - natural language description
size_categories:
  - 1K<n<10K

Dataset Card for CUB_200_2011

Dataset Description

Homepage: https://www.vision.caltech.edu/datasets/cub_200_2011/
Citation: @techreport{WahCUB_200_2011, Title = , Author = {Wah, C. and Branson, S. and Welinder, P. and Perona, P. and Belongie, S.}, Year = {2011} Institution = {California Institute of Technology}, Number = {CNS-TR-2011-001} }

Dataset Summary

The Caltech-UCSD Birds 200-2011 dataset (CUB-200-2011) is an extended version of the original CUB-200 dataset, featuring photos of 200 bird species primarily from North America. This 2011 version collects detailed natural language descriptions for each image through Amazon Mechanical Turk (AMT).

How to Use

  from datasets import load_dataset
  CUB_200 = load_dataset("KAKIZHOU/CUB-200")

Supported Tasks and Leaderboards

This dataset can support a variety of computer vision tasks, including but not limited to:

Fine-Grained Image Classification
Object Detection and Localization
Semantic Segmentation
Attribute-Based Recognition
Multitask Learning

Languages

The dataset includes annotations in English

Data Fields

images: Photographs of birds across 200 species.
annotations: This includes:
- bounding boxes: Specify the bird's location within the image.
- segmentation labels: Provide pixel-wise segmentation for precise object segmentation.
- part locations: 15 specific parts of the bird are annotated for detailed analysis.
- binary attributes: 312 attributes indicating the presence or absence of certain features or behaviors.
- natural language descriptions: Ten single-sentence descriptions per image, collected via AMT.

Data Splits

Training set: 8,855 images
Test set: 2,933 images