--- task_categories: - object-detection tags: - roboflow - roboflow2huggingface dataset_info: features: - name: image_id dtype: int64 - name: image dtype: image - name: width dtype: int32 - name: height dtype: int32 - name: objects sequence: - name: id dtype: int64 - name: area dtype: int64 - name: bbox sequence: float32 length: 4 - name: category dtype: class_label: names: '0': plume '1': summit splits: - name: train num_bytes: 29846342.127 num_examples: 1211 - name: validation num_bytes: 7311174.0 num_examples: 294 - name: test num_bytes: 12048406.0 num_examples: 456 download_size: 49324639 dataset_size: 49205922.127000004 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
edouard-rolland/volcanic-plumes
### Dataset Labels ``` ['plume', 'summit'] ``` ### Number of Images ```json {'valid': 294, 'test': 456, 'train': 1211} ``` ### 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("edouard-rolland/volcanic-plumes", name="full") example = ds['train'][0] ``` ### Roboflow Dataset Page [https://universe.roboflow.com/edouardrolland/hiddenproject-wndzs/dataset/1](https://universe.roboflow.com/edouardrolland/hiddenproject-wndzs/dataset/1?ref=roboflow2huggingface) ### Citation ``` @misc{ hiddenproject-wndzs_dataset, title = { HiddenProject Dataset }, type = { Open Source Dataset }, author = { EdouardRolland }, howpublished = { \\url{ https://universe.roboflow.com/edouardrolland/hiddenproject-wndzs } }, url = { https://universe.roboflow.com/edouardrolland/hiddenproject-wndzs }, journal = { Roboflow Universe }, publisher = { Roboflow }, year = { 2024 }, month = { feb }, note = { visited on 2024-02-01 }, } ``` ### License CC BY 4.0 ### Dataset Summary This dataset was exported via roboflow.com on February 1, 2024 at 9:57 AM 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 1961 images. Plume are annotated in COCO format. The following pre-processing was applied to each image: No image augmentation techniques were applied.