--- task_categories: - object-detection tags: - roboflow - roboflow2huggingface - Construction - Logistics - Utilities - Damage Risk - Ppe - Construction - Utilities - Manufacturing - Logistics - Ppe - Assembly Line - Warehouse - Factory ---
keremberke/construction-safety-object-detection
### 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.