Datasets:
Tasks:
Object Detection
Size:
1K - 10K
task_categories: | |
- object-detection | |
tags: | |
- roboflow | |
- roboflow2huggingface | |
<div align="center"> | |
<img width="640" alt="keremberke/valorant-object-detection" src="https://huggingface.co/datasets/keremberke/valorant-object-detection/resolve/main/thumbnail.jpg"> | |
</div> | |
### Dataset Labels | |
``` | |
['dropped spike', 'enemy', 'planted spike', 'teammate'] | |
``` | |
### Number of Images | |
```json | |
{'valid': 1983, 'train': 6927, 'test': 988} | |
``` | |
### How to Use | |
- Install [datasets](https://pypi.org/project/datasets/): | |
```bash | |
pip install datasets | |
``` | |
- Load the dataset: | |
```python | |
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](https://universe.roboflow.com/daniels-magonis-0pjzx/valorant-9ufcp/dataset/3?ref=roboflow2huggingface) | |
### 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. | |