Synthesizing Realistic Wildlife Images for Conservation and Education

Overview

This project addresses the critical issue of data scarcity in wildlife conservation, particularly the lack of imagery for endangered species. By leveraging advanced generative AI techniques, we aim to create realistic wildlife images to support conservation efforts, scientific research, and public awareness.

Key Features

• Utilizes pre-trained generative models with fine-tuning
• Focuses on endangered African species: African Manatee, African Golden Cat, and White-backed Vulture
• Demonstrates potential for generating images of untrained species

Methodology

1. Data Collection: Images of target species collected from IUCN Red List
2. Preprocessing: Images resized to 512x512 pixels
3. Model: Fine-tuned runwayml/stable-diffusion-v1-5 using DreamBooth technique
4. Evaluation: Generated images compared with real wildlife photos

Results

• Successfully generated realistic images of trained species
• Demonstrated generalization to untrained species
• Potential applications in conservation education and research visualization
• Access the research work here

Future Work

• Expand model capabilities to cover more species
• Improve accuracy and consistency of generated images
• Explore integration with other conservation technologies
• Address ethical considerations of AI-generated imagery in scientific contexts

Contributors

Ridwan Ibidunni, Auwal Ibrahim, Obi Chinyere Mary, Samson Oguntuwase, Dominion Akinrotimi, Rishabh Shrivastava, Niket Kumar, Eguagie-Suyi Precious, Chinazom Enukoha, Adeleke Adekola Emmanuel, Akinwunmi Toluwani Adebayo, Benjamin Muoka, Ade Adesipo, Lolu Zaccheus, Muhammad Asif, Abdulkabir Badru

References

1. Berger-Wolf, T. Y., et al. (2017). Wildbook: Crowdsourcing, computer vision, and data science for conservation.
2. Chen, W., & Hays, J. (2018). Sketchygan: Towards diverse and realistic sketch to image synthesis.
3. Reed, S., et al. (2016). Generative adversarial text to image synthesis.
4. International Union for Conservation of Nature. (2024). The IUCN Red List of Threatened Species.
5. Hugging Face. (2024). DreamBooth Documentation.
6. Runway. (2022). Stable Diffusion v1.5.

Date

27/7/2024

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