| | --- |
| | task_categories: |
| | - object-detection |
| | tags: |
| | - roboflow |
| | - roboflow2huggingface |
| | - Manufacturing |
| | --- |
| | |
| | <div align="center"> |
| | <img width="640" alt="keremberke/forklift-object-detection" src="https://huggingface.co/datasets/keremberke/forklift-object-detection/resolve/main/thumbnail.jpg"> |
| | </div> |
| |
|
| | ### Dataset Labels |
| |
|
| | ``` |
| | ['forklift', 'person'] |
| | ``` |
| |
|
| |
|
| | ### Number of Images |
| |
|
| | ```json |
| | {'test': 42, 'valid': 84, 'train': 295} |
| | ``` |
| |
|
| |
|
| | ### 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/forklift-object-detection", name="full") |
| | example = ds['train'][0] |
| | ``` |
| |
|
| | ### Roboflow Dataset Page |
| | [https://universe.roboflow.com/mohamed-traore-2ekkp/forklift-dsitv/dataset/1](https://universe.roboflow.com/mohamed-traore-2ekkp/forklift-dsitv/dataset/1?ref=roboflow2huggingface) |
| |
|
| | ### Citation |
| |
|
| | ``` |
| | @misc{ forklift-dsitv_dataset, |
| | title = { Forklift Dataset }, |
| | type = { Open Source Dataset }, |
| | author = { Mohamed Traore }, |
| | howpublished = { \\url{ https://universe.roboflow.com/mohamed-traore-2ekkp/forklift-dsitv } }, |
| | url = { https://universe.roboflow.com/mohamed-traore-2ekkp/forklift-dsitv }, |
| | journal = { Roboflow Universe }, |
| | publisher = { Roboflow }, |
| | year = { 2022 }, |
| | month = { mar }, |
| | note = { visited on 2023-01-15 }, |
| | } |
| | ``` |
| |
|
| | ### License |
| | CC BY 4.0 |
| |
|
| | ### Dataset Summary |
| | This dataset was exported via roboflow.ai on April 3, 2022 at 9:01 PM GMT |
| |
|
| | It includes 421 images. |
| | Forklift 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. |
| |
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| |
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| |
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