---
license: mit
task_categories:
  - image-classification
tags:
  - biology
  - marine-life
  - biodiversity
pretty_name: 'Sea Shell Classification Dataset'
size_categories:
  - 1K<n<10K
---

# 🐚 De_vuelta_a_casa: Sea Shell Image Dataset

## 🌊 Dataset Description
The **De_vuelta_a_casa** dataset contains images of sea shells classified by species and divided into two geographic regions: **Caribbean** and **Pacific**. The dataset is organized into two main categories of mollusks:

- **Bivalves**: Mollusks with two shells (e.g., clams, oysters).
- **Gastropoda**: Mollusks with a single shell (e.g., snails).

Images were sourced from publicly available online resources and meticulously categorized by species within each geographic region. This dataset is ideal for:
- Image classification projects.
- Marine biodiversity research.
- Studies in marine biology.

## 📂 Dataset Structure
The dataset follows the folder structure below:

```plaintext
De_vuelta_a_casa/
├── Dataset/
    ├── Bivalves/
        ├── Caribbean/
            ├── species_1.jpg
            ├── species_2.jpg
            └── ...
        ├── Pacific/
            ├── species_1.jpg
            ├── species_2.jpg
            └── ...
    ├── Gastropoda/
        ├── Caribbean/
            ├── species_1.jpg
            ├── species_2.jpg
            └── ...
        ├── Pacific/
            ├── species_1.jpg
            ├── species_2.jpg
            └── ...
```

Each folder contains images organized by region and species.

## 🏷️Dataset Details
Total number of images: [Add the total number of images here]
Number of species: [Add the number of species here]
Geographic Regions: Caribbean and Pacific from Costa Rica
OverCategories:
  -Bivalves: Two-shelled mollusks (e.g., clams, oysters)
  -Gastropoda: Single-shelled mollusks (e.g., snails)
Image sources: Images collected from various public online sources.
Average resolution: [Add the average image resolution here, if relevant].
Labels: Each image is labeled with the species name it belongs to.
Sources: Publicly available images from the internet
Image Format: JPEG/PNG
Labels: Species name and geographic region

## 📊 Applications
This dataset can be used for:

**Marine Biodiversity Research:** Studying species distribution and diversity.
**Image Classification:** Training models to identify and classify mollusk species.
**Environmental Studies:** Understanding the impact of environmental factors on species distribution.
**Educational Purposes:** Teaching about marine ecosystems and mollusk species.

## 🚀 Getting Started
### 📥 Download the Dataset
You can download the dataset directly from Hugging Face using the following command:
```python
pip install datasets
```
```python
from datasets import load_dataset

dataset = load_dataset("De_vuelta_a_casa", split="train")
```
### 🔍 Access Specific Categories
To access images from specific categories:

**Bivalves (Caribbean):**
```python
dataset["Dataset/Bivalves/Caribbean/"]
```
**Bivalves (Pacific):**
```python
dataset["Dataset/Bivalves/Pacific/"]
```
**Gastropoda (Caribbean):**
```python
dataset["Dataset/Gastropoda/Caribbean/"]
```
**Gastropoda (Pacific):**
```python
dataset["Dataset/Gastropoda/Pacific/"]
```

## 📜 Licensing and Usage
License: MIT License
Usage:
This dataset is intended for educational and research purposes only.
Commercial use of the dataset requires prior verification of the original image sources.
Respect the copyright and intellectual property rights associated with the collected images.


## 🌟 Acknowledgments
Special thanks to:

All contributors who have made marine species documentation publicly available.
The creators of open-source tools that have enabled this project.
This dataset was created to promote awareness of marine biodiversity and support scientific research. We hope it helps researchers, educators, and enthusiasts understand and protect our oceans' ecosystems.

## 🔗 Citation
If you use this dataset in your research, please cite it as follows:

```bibtex
@dataset{de_vuelta_a_casa,
  title = {De_vuelta_a_casa: Sea Shell Image Dataset},
  author = {JoystickData Team},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/De_vuelta_a_casa}
}
```