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keremberke/valorant-object-detection

Dataset Labels

['dropped spike', 'enemy', 'planted spike', 'teammate']

Number of Images

{'valid': 1983, 'train': 6927, 'test': 988}

How to Use

pip install datasets
  • Load the dataset:
from datasets import load_dataset

ds = load_dataset("keremberke/valorant-object-detection", name="full")
example = ds['train'][0]

Roboflow Dataset Page

https://universe.roboflow.com/daniels-magonis-0pjzx/valorant-9ufcp/dataset/3

Citation

@misc{ valorant-9ufcp_dataset,
    title = { valorant Dataset },
    type = { Open Source Dataset },
    author = { Daniels Magonis },
    howpublished = { \\url{ https://universe.roboflow.com/daniels-magonis-0pjzx/valorant-9ufcp } },
    url = { https://universe.roboflow.com/daniels-magonis-0pjzx/valorant-9ufcp },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { nov },
    note = { visited on 2023-01-27 },
}

License

CC BY 4.0

Dataset Summary

This dataset was exported via roboflow.com on December 22, 2022 at 5:10 PM 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 unstructured image data
  • annotate, and create datasets
  • export, train, and deploy computer vision models
  • use active learning to improve your dataset over time

It includes 9898 images. Planted are annotated in COCO format.

The following pre-processing was applied to each image:

  • Resize to 416x416 (Stretch)

No image augmentation techniques were applied.

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