Dataset Labels

['bird', 'black and brown camouflage helicopter', 'black and orange drone', 'black and white cargo aircraft', 'black and white commercial aircraft', 'black and white missile', 'black and yellow drone', 'black and yellow missile', 'black camouflage fighter jet', 'black cargo aircraft', 'black drone', 'black fighter jet', 'black fighter plane', 'black helicopter', 'blimp', 'blue and green fighter plane', 'blue and grey fighter jet', 'blue and red commercial aircraft', 'blue and red light aircraft', 'blue and white commercial aircraft', 'blue and white helicopter', 'blue and white light aircraft', 'blue and white missile', 'blue and yellow fighter jet', 'blue and yellow helicopter', 'blue camouflage fighter jet', 'blue commercial aircraft', 'blue helicopter', 'blue missile', 'blue- yellow- and black helicopter', 'blue- yellow- and green fighter plane', 'blue- yellow- and white cargo aircraft', 'glider', 'green and black camouflage helicopter', 'green and black missile', 'green and brown camouflage fighter jet', 'green and brown camouflage fighter plane', 'green and brown camouflage helicopter', 'green and grey helicopter', 'green and white fighter plane', 'green and yellow fighter plane', 'green camouflage helicopter', 'green fighter plane', 'green helicopter', 'green light aircraft', 'green missile', 'grey and black fighter plane', 'grey and black helicopter', 'grey and green cargo aircraft', 'grey and red commercial aircraft', 'grey and red fighter jet', 'grey and red missile', 'grey and white fighter plane', 'grey and white light aircraft', 'grey and yellow fighter plane', 'grey camouflage fighter jet', 'grey cargo aircraft', 'grey commercial aircraft', 'grey drone', 'grey fighter jet', 'grey fighter plane', 'grey helicopter', 'grey light aircraft', 'grey missile', 'grey- red- and blue commercial aircraft', 'orange and black fighter jet', 'orange light aircraft', 'red and black drone', 'red and grey missile', 'red and white fighter jet', 'red and white fighter plane', 'red and white helicopter', 'red and white light aircraft', 'red and white missile', 'red fighter jet', 'red fighter plane', 'red helicopter', 'red light aircraft', 'red- white- and blue fighter jet', 'red- white- and blue light aircraft', 'silver and blue fighter plane', 'silver fighter plane', 'white and black cargo aircraft', 'white and black drone', 'white and black fighter jet', 'white and black fighter plane', 'white and black helicopter', 'white and black light aircraft', 'white and blue cargo aircraft', 'white and blue commercial aircraft', 'white and blue fighter jet', 'white and blue fighter plane', 'white and blue helicopter', 'white and blue light aircraft', 'white and grey helicopter', 'white and orange commercial aircraft', 'white and orange light aircraft', 'white and red commercial aircraft', 'white and red fighter jet', 'white and red fighter plane', 'white and red helicopter', 'white and red light aircraft', 'white and red missile', 'white and yellow commercial aircraft', 'white cargo aircraft', 'white commercial aircraft', 'white drone', 'white fighter jet', 'white fighter plane', 'white helicopter', 'white light aircraft', 'white missile', 'white- black- and grey missile', 'white- black- and red drone', 'white- blue- and red commercial aircraft', 'white- red- and blue commercial aircraft', 'white- red- and green fighter plane', 'yellow and black fighter plane', 'yellow and green helicopter', 'yellow and red light aircraft', 'yellow commercial aircraft', 'yellow fighter jet', 'yellow fighter plane', 'yellow helicopter', 'yellow light aircraft', 'yellow missile', 'yellow- black- and red helicopter', 'yellow- red- and blue fighter plane', 'yellow- red- and grey helicopter']

Number of Images

{'valid': 645, 'train': 5808}

How to Use

Install datasets:

pip install datasets

Load the dataset:

from datasets import load_dataset

ds = load_dataset("flipwooyoung/roboflow", name="full")
example = ds['train'][0]

Roboflow Dataset Page

https://universe.roboflow.com/til2024/vlm-task/coco/5

Citation

License

MIT

Dataset Summary

This dataset was exported via roboflow.com on May 19, 2024 at 5:58 AM GMT

Roboflow is an end-to-end computer vision platform that helps you

collaborate with your team on computer vision projects
collect & organize images
understand and search unstructured image data
annotate, and create datasets
export, train, and deploy computer vision models
use active learning to improve your dataset over time

For state of the art Computer Vision training notebooks you can use with this dataset, visit https://github.com/roboflow/notebooks

To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com

The dataset includes 6453 images. Flying-stuff are annotated in COCO format.

The following pre-processing was applied to each image:

No image augmentation techniques were applied.