Datasets:
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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
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