Lizard_new Object Detection Dataset and Pre-Trained Model by ana.leonor.a@hotmail.com

Images

5853 images

Explore Dataset

Here are a few use cases for this project:

Biological Research: This model can be used in ecological studies to identify and classify different parts of a lizard's body. It can assist with tracking and monitoring lizard populations and understanding their behavior, shift in their body structures or any changes in their population dynamics.
Wildlife Conservation: It could be used in biodiversity hotspots where lizards are prevalent. By identifying different lizards and their body parts, this model can help in assessing their health status and population size, which is vital for implementing effective conservation strategies.
Pet Trade Monitoring: The model can help pet trade organizations and authorities by identifying lizards and different parts of their body, to ensure the healthy sourcing of pet lizards. Any abnormalities or changes in physical characteristics can be flagged for potential illness or mistreatment.
Educational Purpose: This model can be used as a part of interactive learning tools in zoology classes to educate students about lizards' anatomy and diversity. It can boost engagement by providing automatic lizard body part recognition.
Wildlife Photography Editing: The model could help wildlife photographers identifying and classifying parts of the lizard body during their editing process. This could help in ensuring accurate depictions and highlight specific features, enhancing the educational value of the photographs.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            lizard_new_dataset,
                            title = { Lizard_new Dataset },
                            type = { Open Source Dataset },
                            author = { ana.leonor.a@hotmail.com },
                            howpublished = { \url{ https://universe.roboflow.com/ana-leonor-a-hotmail-com/lizard_new } },
                            url = { https://universe.roboflow.com/ana-leonor-a-hotmail-com/lizard_new },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jul },
                            note = { visited on 2024-06-01 },
                            }