manot/football-players
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--- task_categories: - object-detection tags: - roboflow - roboflow2huggingface --- <div align="center"> <img width="640" alt="manot/football-players" src="https://huggingface.co/datasets/manot/football-players/resolve/main/thumbnail.jpg"> </div> ### Dataset Labels ``` ['football', 'player'] ``` ### Number of Images ```json {'valid': 87, 'train': 119} ``` ### 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("manot/football-players", name="full") example = ds['train'][0] ``` ### Roboflow Dataset Page [https://universe.roboflow.com/konstantin-sargsyan-wucpb/football-players-2l81z/dataset/1](https://universe.roboflow.com/konstantin-sargsyan-wucpb/football-players-2l81z/dataset/1?ref=roboflow2huggingface) ### Citation ``` @misc{ football-players-2l81z_dataset, title = { football-players Dataset }, type = { Open Source Dataset }, author = { Konstantin Sargsyan }, howpublished = { \\url{ https://universe.roboflow.com/konstantin-sargsyan-wucpb/football-players-2l81z } }, url = { https://universe.roboflow.com/konstantin-sargsyan-wucpb/football-players-2l81z }, journal = { Roboflow Universe }, publisher = { Roboflow }, year = { 2023 }, month = { jun }, note = { visited on 2023-06-12 }, } ``` ### License MIT ### Dataset Summary This dataset was exported via roboflow.com on June 12, 2023 at 10:10 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 206 images. Players are annotated in COCO format. The following pre-processing was applied to each image: * Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) No image augmentation techniques were applied.
task_categories: - 目标检测（object-detection） tags: - Roboflow（roboflow） - roboflow2huggingface（roboflow2huggingface） --- <div align="center"> <img width="640" alt="manot/football-players" src="https://huggingface.co/datasets/manot/football-players/resolve/main/thumbnail.jpg"> </div> ### 数据集标签 ['football', 'player'] ### 图像数量 json {'valid': 87, 'train': 119} ### 使用方法 - 安装[datasets库（datasets）](https://pypi.org/project/datasets/): bash pip install datasets - 加载数据集: python from datasets import load_dataset ds = load_dataset("manot/football-players", name="full") example = ds['train'][0] ### Roboflow数据集页面 [https://universe.roboflow.com/konstantin-sargsyan-wucpb/football-players-2l81z/dataset/1](https://universe.roboflow.com/konstantin-sargsyan-wucpb/football-players-2l81z/dataset/1?ref=roboflow2huggingface) ### 引用格式 @misc{ football-players-2l81z_dataset, title = { football-players Dataset }, type = { Open Source Dataset }, author = { Konstantin Sargsyan }, howpublished = { url{ https://universe.roboflow.com/konstantin-sargsyan-wucpb/football-players-2l81z } }, url = { https://universe.roboflow.com/konstantin-sargsyan-wucpb/football-players-2l81z }, journal = { Roboflow Universe }, publisher = { Roboflow }, year = { 2023 }, month = { jun }, note = { visited on 2023-06-12 }, } ### 许可证 MIT许可证（MIT） ### 数据集摘要 本数据集于2023年6月12日格林威治标准时间上午10:10通过roboflow.com导出。 Roboflow是一款端到端的计算机视觉平台，可助力您完成以下操作： * 与团队协作开展计算机视觉项目 * 收集并整理图像 * 理解并检索非结构化图像数据 * 标注图像并构建数据集 * 导出、训练并部署计算机视觉模型 * 使用主动学习方法随时间迭代优化数据集 如需获取可配合本数据集使用的前沿计算机视觉训练笔记本，请访问 https://github.com/roboflow/notebooks 如需查找超过10万个其他数据集与预训练模型，请访问 https://universe.roboflow.com 本数据集共包含206张图像，数据集内的运动员标注采用COCO格式（COCO）。 已对每张图像应用以下预处理操作： * 像素数据自动定向（移除EXIF方向信息） * 拉伸调整至640×640分辨率 未应用任何图像增强技术。
数据集标签
[football, player]
图片数量
json {valid: 87, train: 119}
如何使用
- 安装 datasets:
bash pip install datasets
- 加载数据集:
python from datasets import load_dataset
ds = load_dataset("manot/football-players", name="full") example = ds[train][0]
引用
@misc{ football-players-2l81z_dataset, title = { football-players Dataset }, type = { Open Source Dataset }, author = { Konstantin Sargsyan }, howpublished = { \url{ https://universe.roboflow.com/konstantin-sargsyan-wucpb/football-players-2l81z } }, url = { https://universe.roboflow.com/konstantin-sargsyan-wucpb/football-players-2l81z }, journal = { Roboflow Universe }, publisher = { Roboflow }, year = { 2023 }, month = { jun }, note = { visited on 2023-06-12 }, }
许可证
MIT
数据集概述
该数据集通过 roboflow.com 于 2023 年 6 月 12 日 10:10 AM GMT 导出。
数据集包括 206 张图片。球员标注采用 COCO 格式。
以下预处理应用于每张图片：
- 自动调整像素数据方向（去除 EXIF 方向信息）
- 调整大小至 640x640（拉伸）
未应用任何图像增强技术。
