--- task_categories: - object-detection tags: - roboflow - roboflow2huggingface - Volcanoes - Plumes - UAVs - Drone 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 num_examples: 294 - name: test num_bytes: 12048406 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-* license: mit language: - en ---
edouard-rolland/volcanic-plumes
### Dataset Description The dataset presents labelled pictures of plumes and of the Fuego Summit in Guatemala. The data was collected by the University of Bristol Flight Lab in Guatemala from March 22 to April 3, 2019. The drone used for this purpose was a Skywalker X8, equipped with a Pixhawk onboard computer running ArduPlane 3.7.1 and a Raspberry Pi 3B+ for mission management and communication with the ground station. The drone was also equipped of a GoPro Hero 9. ### Example of Application ### Citation ### Acknowledgement This work is supported by the WildDrone MSCA Doctoral Network funded by EU Horizon Europe under grant agreement no. 101071224, the Innovation Fund Denmark for the project DIREC (9142-00001B), and by the Engineering & Physical Sciences Research Council (UK) through the CASCADE (Complex Autonomous aircraft Systems Configuration, Analysis and Design Exploratory) programme grant (EP/R009953/1). ### 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] ``` ### Citation ``` @misc{ } ``` ### License MIT