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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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--- |
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### Roboflow Dataset Page |
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[https://universe.roboflow.com/augmented-startups/football-player-detection-kucab](https://universe.roboflow.com/augmented-startups/football-player-detection-kucab?ref=roboflow2huggingface) |
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### Citation |
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``` |
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@misc{ football-player-detection-kucab_dataset, |
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title = { Football-Player-Detection Dataset }, |
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type = { Open Source Dataset }, |
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author = { Augmented Startups }, |
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howpublished = { \url{ https://universe.roboflow.com/augmented-startups/football-player-detection-kucab } }, |
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url = { https://universe.roboflow.com/augmented-startups/football-player-detection-kucab }, |
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journal = { Roboflow Universe }, |
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publisher = { Roboflow }, |
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year = { 2022 }, |
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month = { nov }, |
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note = { visited on 2022-12-29 }, |
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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 November 21, 2022 at 6:50 PM 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 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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It includes 1232 images. |
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Track-players-and-football 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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No image augmentation techniques were applied. |
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