keremberke/construction-safety-object-detection
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--- task_categories: - object-detection tags: - roboflow - roboflow2huggingface - Construction - Logistics - Utilities - Damage Risk - Ppe - Construction - Utilities - Manufacturing - Logistics - Ppe - Assembly Line - Warehouse - Factory --- <div align="center"> <img width="640" alt="keremberke/construction-safety-object-detection" src="https://huggingface.co/datasets/keremberke/construction-safety-object-detection/resolve/main/thumbnail.jpg"> </div> ### Dataset Labels ``` ['barricade', 'dumpster', 'excavators', 'gloves', 'hardhat', 'mask', 'no-hardhat', 'no-mask', 'no-safety vest', 'person', 'safety net', 'safety shoes', 'safety vest', 'dump truck', 'mini-van', 'truck', 'wheel loader'] ``` ### Number of Images ```json {'train': 307, 'valid': 57, 'test': 34} ``` ### 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/construction-safety-object-detection", name="full") example = ds['train'][0] ``` ### Roboflow Dataset Page [https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety/dataset/1](https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety/dataset/1?ref=roboflow2huggingface) ### Citation ``` @misc{ construction-site-safety_dataset, title = { Construction Site Safety Dataset }, type = { Open Source Dataset }, author = { Roboflow Universe Projects }, howpublished = { \\url{ https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety } }, url = { https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety }, journal = { Roboflow Universe }, publisher = { Roboflow }, year = { 2023 }, month = { jan }, note = { visited on 2023-01-26 }, } ``` ### License CC BY 4.0 ### Dataset Summary This dataset was exported via roboflow.com on December 29, 2022 at 11:22 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 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 398 images. Construction are annotated in COCO format. The following pre-processing was applied to each image: * Auto-orientation of pixel data (with EXIF-orientation stripping) No image augmentation techniques were applied.
### 任务类别 - 目标检测（object-detection） ### 标签 - Roboflow - roboflow2huggingface - 建筑工程（Construction） - 物流（Logistics） - 公用事业（Utilities） - 损坏风险（Damage Risk） - 个人防护装备（PPE） - 建筑工程（Construction） - 公用事业（Utilities） - 制造业（Manufacturing） - 物流（Logistics） - 个人防护装备（PPE） - 装配线（Assembly Line） - 仓库（Warehouse） - 工厂（Factory） <div align="center"> <img width="640" alt="keremberke/建筑安全目标检测" src="https://huggingface.co/datasets/keremberke/construction-safety-object-detection/resolve/main/thumbnail.jpg"> </div> ### 数据集标签 ['路障（barricade）', '自卸垃圾箱（dumpster）', '挖掘机（excavators）', '手套（gloves）', '安全帽（hardhat）', '口罩（mask）', '未佩戴安全帽（no-hardhat）', '未佩戴口罩（no-mask）', '未穿戴安全背心（no-safety vest）', '人员（person）', '安全网（safety net）', '安全鞋（safety shoes）', '安全背心（safety vest）', '自卸卡车（dump truck）', '小型货车（mini-van）', '卡车（truck）', '轮式装载机（wheel loader）'] ### 图像数量 json {"训练集": 307, "验证集": 57, "测试集": 34} ### 使用方法 - 安装[datasets](https://pypi.org/project/datasets/)库： bash pip install datasets - 加载数据集： python from datasets import load_dataset ds = load_dataset("keremberke/construction-safety-object-detection", name="full") example = ds['train'][0] ### Roboflow 数据集页面 [https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety/dataset/1](https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety/dataset/1?ref=roboflow2huggingface) ### 引用 @misc{ construction-site-safety_dataset, title = { 建筑工地安全数据集 }, type = { 开源数据集 }, author = { Roboflow 宇宙项目团队 }, howpublished = { \url{ https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety } }, url = { https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety }, journal = { Roboflow 宇宙 }, publisher = { Roboflow }, year = { 2023 }, month = { jan }, note = { 访问于 2023-01-26 }, } ### 许可证 CC BY 4.0 ### 数据集概述 本数据集于2022年12月29日格林尼治标准时间上午11:22通过roboflow.com导出。 Roboflow是一款端到端的计算机视觉平台，可助力您完成以下工作： * 与团队协作开展计算机视觉项目 * 收集并整理图像数据 * 解析非结构化图像数据 * 进行标注并构建数据集 * 导出、训练并部署计算机视觉模型 * 运用主动学习技术，持续优化数据集 本数据集共包含398张图像，建筑相关目标采用COCO格式进行标注。 已对每张图像执行以下预处理操作： * 像素数据自动校正（附带EXIF方向信息剥离） 未使用任何图像增强技术。
数据集概述
任务类别
- 目标检测
标签
- barricade
- dumpster
- excavators
- gloves
- hardhat
- mask
- no-hardhat
- no-mask
- no-safety vest
- person
- safety net
- safety shoes
- safety vest
- dump truck
- mini-van
- truck
- wheel loader
图像数量
json { "train": 307, "valid": 57, "test": 34 }
使用方法
-
安装
datasets库： bash pip install datasets -
加载数据集： python from datasets import load_dataset ds = load_dataset("keremberke/construction-safety-object-detection", name="full") example = ds[train][0]
许可证
- CC BY 4.0
数据集处理
- 应用了自动像素数据方向调整（包含EXIF方向剥离）
- 未应用图像增强技术
