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--- |
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task_categories: |
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- object-detection |
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tags: |
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- roboflow |
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- roboflow2huggingface |
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--- |
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<div align="center"> |
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<img width="640" alt="neogpx/constructionxc7c" src="https://huggingface.co/datasets/neogpx/constructionxc7c/resolve/main/thumbnail.jpg"> |
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</div> |
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### Dataset Labels |
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``` |
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['bulldozer', 'dump truck', 'excavator', 'grader', 'loader', 'mixer truck', 'mobile crane', 'roller'] |
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``` |
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### Number of Images |
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```json |
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{'valid': 1524, 'test': 757, 'train': 16002} |
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``` |
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### How to Use |
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- Install [datasets](https://pypi.org/project/datasets/): |
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```bash |
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pip install datasets |
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``` |
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- Load the dataset: |
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```python |
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from datasets import load_dataset |
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ds = load_dataset("neogpx/constructionxc7c", name="full") |
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example = ds['train'][0] |
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``` |
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### Roboflow Dataset Page |
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[https://universe.roboflow.com/capstone-lkzgq/construction-vehicle-detection-pxc7c/dataset/2 |
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](https://universe.roboflow.com/capstone-lkzgq/construction-vehicle-detection-pxc7c/dataset/2 |
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?ref=roboflow2huggingface) |
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### Citation |
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``` |
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@misc{ |
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construction-vehicle-detection-pxc7c_dataset, |
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title = { Construction Vehicle Detection Dataset }, |
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type = { Open Source Dataset }, |
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author = { Capstone }, |
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howpublished = { \\url{ https://universe.roboflow.com/capstone-lkzgq/construction-vehicle-detection-pxc7c } }, |
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url = { https://universe.roboflow.com/capstone-lkzgq/construction-vehicle-detection-pxc7c }, |
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journal = { Roboflow Universe }, |
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publisher = { Roboflow }, |
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year = { 2023 }, |
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month = { aug }, |
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note = { visited on 2025-02-11 }, |
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} |
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``` |
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### License |
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CC BY 4.0 |
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### Dataset Summary |
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This dataset was exported via roboflow.com on July 17, 2023 at 7:32 AM GMT |
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Roboflow is an end-to-end computer vision platform that helps you |
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* collaborate with your team on computer vision projects |
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* collect & organize images |
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* understand and search unstructured image data |
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* annotate, and create datasets |
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* export, train, and deploy computer vision models |
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* use active learning to improve your dataset over time |
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For state of the art Computer Vision training notebooks you can use with this dataset, |
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visit https://github.com/roboflow/notebooks |
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To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com |
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The dataset includes 18283 images. |
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Construction-utility-vechicles are annotated in COCO format. |
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The following pre-processing was applied to each image: |
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* Auto-orientation of pixel data (with EXIF-orientation stripping) |
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* Resize to 640x640 (Stretch) |
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The following augmentation was applied to create 3 versions of each source image: |
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* Randomly crop between 0 and 20 percent of the image |
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* Random rotation of between -20 and +20 degrees |
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* Salt and pepper noise was applied to 5 percent of pixels |
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