--- task_categories: - object-detection tags: - roboflow - roboflow2huggingface ---
keremberke/valorant-object-detection
### 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.