README.md

---
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
---

<div align="center">
  <img width=100% alt="edouard-rolland/volcanic-plumes" src="https://huggingface.co/datasets/edouard-rolland/volcanic-plumes/resolve/main/thumbnail.png">
</div>

### 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.

### Citation

```
@misc{
}
```

### 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']
```

### Example of Labelled Images

<div align="center">
  <<img width=50% alt="edouard-rolland/volcanic-plumes" src="https://huggingface.co/datasets/edouard-rolland/volcanic-plumes/resolve/main/val_batch0_labels.jpg">
</div>

### Number of Images

```json
{'valid': 294, 'test': 456, 'train': 1211}
```
### Example of Application

The dataset was used to train a YOLOv8 neural network. More details can be found in the paper mentioned in the citation section. The following video presents the model output for an entire flight.

[![YOLOv8](https://huggingface.co/datasets/edouard-rolland/volcanic-plumes/resolve/main/youtube_t.png)](https://www.youtube.com/watch?v=pSGYUPancfA)


### 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]
```

### License
MIT