
<div align="center">
  <img width="640" alt="keremberke/hard-hat-detection" src="https://huggingface.co/datasets/keremberke/hard-hat-detection/resolve/main/thumbnail.jpg">
</div>

### Dataset Labels

```
['hardhat', 'no-hardhat']
```


### Number of Images

```json
{'test': 2001, 'train': 13782, 'valid': 3962}
```


### 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/hard-hat-detection", name="full")
example = ds['train'][0]
```

### Roboflow Dataset Page
[https://universe.roboflow.com/roboflow-universe-projects/hard-hats-fhbh5/dataset/2](https://universe.roboflow.com/roboflow-universe-projects/hard-hats-fhbh5/dataset/2?ref=roboflow2huggingface)

### Citation

```
@misc{ hard-hats-fhbh5_dataset,
    title = { Hard Hats Dataset },
    type = { Open Source Dataset },
    author = { Roboflow Universe Projects },
    howpublished = { \\url{ https://universe.roboflow.com/roboflow-universe-projects/hard-hats-fhbh5 } },
    url = { https://universe.roboflow.com/roboflow-universe-projects/hard-hats-fhbh5 },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { dec },
    note = { visited on 2023-01-16 },
}
```

### License
CC BY 4.0

### Dataset Summary
This dataset was exported via roboflow.com on January 16, 2023 at 9:17 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 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 19745 images.
Hardhat-ppe 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:object-detection roboflow roboflow2huggingface Construction Utilities Manufacturing Logistics Ppe Assembly Line Warehouse Factory Damage Risk region:us
{"task_categories": ["object-detection"], "tags": ["roboflow", "roboflow2huggingface", "Construction", "Utilities", "Manufacturing", "Logistics", "Ppe", "Assembly Line", "Warehouse", "Factory", "Construction", "Logistics", "Utilities", "Damage Risk", "Ppe"]}
TAGS
#task_categories-object-detection #roboflow #roboflow2huggingface #Construction #Utilities #Manufacturing #Logistics #Ppe #Assembly Line #Warehouse #Factory #Damage Risk #region-us 


<div align="center">
  <img width="640" alt="keremberke/hard-hat-detection" src="URL
</div>

### Dataset Labels




### Number of Images




### How to Use

- Install datasets:



- Load the dataset:



### Roboflow Dataset Page
URL

### License
CC BY 4.0

### Dataset Summary
This dataset was exported via URL on January 16, 2023 at 9:17 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 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 URL

To find over 100k other datasets and pre-trained models, visit URL

The dataset includes 19745 images.
Hardhat-ppe 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.




### Dataset Labels ### Number of Images ### How to Use

- Install datasets:



- Load the dataset: ### Roboflow Dataset Page
URL ### License
CC BY 4.0 ### Dataset Summary
This dataset was exported via URL on January 16, 2023 at 9:17 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 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 URL

To find over 100k other datasets and pre-trained models, visit URL

The dataset includes 19745 images.
Hardhat-ppe 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.
TAGS
#task_categories-object-detection #roboflow #roboflow2huggingface #Construction #Utilities #Manufacturing #Logistics #Ppe #Assembly Line #Warehouse #Factory #Damage Risk #region-us 
 ### Dataset Labels ### Number of Images ### How to Use

- Install datasets:



- Load the dataset: ### Roboflow Dataset Page
URL ### License
CC BY 4.0 ### Dataset Summary
This dataset was exported via URL on January 16, 2023 at 9:17 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 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 URL

To find over 100k other datasets and pre-trained models, visit URL

The dataset includes 19745 images.
Hardhat-ppe 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.