README.md

---
annotations_creators: []
language: en
size_categories:
- 10K<n<100K
task_categories:
- image-classification
task_ids: []
pretty_name: jaguars
tags:
- fiftyone
- image
- image-classification
license: cc-by-4.0
---

# Dataset Card for jaguars

<!-- Provide a quick summary of the dataset. -->

This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 12392 samples.



## Dataset Details

# Jaguar Re-identification Dataset

This dataset contains images of jaguars from the Porto Jofre region in the Pantanal National Park, Brazil. It was curated for the purpose of developing and evaluating deep learning models for individual jaguar identification for population tracking.

![](https://github.com/andandandand/practical-computer-vision/blob/main/images/jaguars_fo_2.png?raw=true)

## Dataset Description

The [Jaguar Identification Project](https://www.jaguaridproject.com/) aims to track jaguar movements, health, and demographics. This contributes valuable data to conservation strategies, especially considering jaguars are classified as Near Threatened by the [IUCN](https://iucn.org/) due to habitat loss, poaching, and human-wildlife conflict.

The core idea is to use photos taken by citizen scientists, to distinguish individual jaguars (e.g., identifying "Medrosa" vs. "Patricia").

**Origin of Data:**
The images are primarily sourced from Porto Jofre, a wildlife reserve located in the Pantanal National Park, which is home to one of the largest wild jaguar populations and is a popular destination for ecotourism and wildlife observation.

**Goal of the Dataset:**
The primary goal is to facilitate the development of models that can distinguish different individual jaguars from images. This supports:
*   Population tracking and demographic studies.
*   Citizen science efforts
*   Conservation strategies by providing data on jaguar movements and health.

## Dataset Details

**Data Collection and Preprocessing:**
The dataset was prepared through a pipeline involving:
*   Collection of raw images (initially around 40GB, ~4300 images).
*   **Cropping and Segmentation:**
    *   Cropped body images (using Grounding DINO).
    *   Cropped face images.
    *   Segmented body images (using SAM - Segment Anything Model).
    *   Segmented face images.

The dataset includes images of various individual jaguars, such as "Ousado," "Medrosa," and "Patricia."

## Motivation

Protecting endangered and near-threatened species like jaguars starts with understanding their populations and the threats they face, such as wildfires, deforestation, illegal trade, climate change, and human-wildlife conflicts. 

## Project Goals and Model Development

The dataset is used to:
*   Contribute to citizen science efforts at the Pantanal Jaguar ID Project.
*   Support research on re-identification models.

## Citation and License

All images were captured by Abigail Martin and contributors to the Jaguar ID Project https://www.jaguaridproject.com. The rights of ownership to these images remain to the Jaguar ID Project.  
We kindly ask you to keep all credits as shown on the original images. You will find these in the `raw_images` split.  

If you use this dataset in your research, please cite the following:

```bibtex
@misc{jaguar_identification_dataset_2025,
  author    = {Antonio Rueda-Toicen and Abigail Martin and Shahabeddin Dayani and Davide Panza and Aleksandra Kudaeva and Gerard de Melo},
  title     = {Jaguars of Pantanal Re-Identification Dataset},
  year      = {2025},
  publisher = {Hugging Face},
  journal   = {Hugging Face Hub},
  howpublished = {\url{https://huggingface.co/datasets/jaguaridentification/jaguars}} 
}
```

## Installation

If you haven't already, install FiftyOne:

```bash
pip install -U fiftyone
```

## Usage

```python
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub

# Load the dataset
# Note: other available arguments include 'max_samples', etc
# see https://docs.voxel51.com/api/fiftyone.utils.huggingface.html#fiftyone.utils.huggingface.load_from_hub
dataset = load_from_hub("andandandand/jaguars")

# Launch the App
session = fo.launch_app(dataset)
```