--- task_categories: - object-detection tags: - roboflow - roboflow2huggingface ---
keremberke/csgo-object-detection
### Dataset Labels ``` ['ct', 'cthead', 't', 'thead'] ``` ### Number of Images ```json {'train': 3879, 'valid': 383, 'test': 192} ``` ### 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/csgo-object-detection", name="full") example = ds['train'][0] ``` ### Roboflow Dataset Page [https://universe.roboflow.com/asd-culfr/wlots/dataset/1](https://universe.roboflow.com/asd-culfr/wlots/dataset/1?ref=roboflow2huggingface) ### Citation ``` @misc{ wlots_dataset, title = { wlots Dataset }, type = { Open Source Dataset }, author = { asd }, howpublished = { \\url{ https://universe.roboflow.com/asd-culfr/wlots } }, url = { https://universe.roboflow.com/asd-culfr/wlots }, journal = { Roboflow Universe }, publisher = { Roboflow }, year = { 2022 }, month = { may }, note = { visited on 2023-01-27 }, } ``` ### License CC BY 4.0 ### Dataset Summary This dataset was exported via roboflow.com on December 28, 2022 at 8:08 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 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 4454 images. Ct-cthead-t-thead 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 416x416 (Fill (with center crop)) The following augmentation was applied to create 3 versions of each source image: * Random brigthness adjustment of between -15 and +15 percent