Won BuildDSM V1 Hackathon for Best Pitch/Demo
vetU is an AI/ML powered application for veterinary telehealth designed to assist pet owners in assessing their pets' health conditions remotely. The application utilizes image recognition technology, AI analysis, and access to veterinary resources to provide preliminary diagnoses and recommend appropriate actions.
Vet-U.Final.Demo.mp4
- Symptom Data Collection: Allows users to input various symptoms and characteristics of their pets to aid in the diagnostic process.
- AI Analysis: Utilizes machine learning models to analyze symptoms and provide preliminary diagnoses based on medical textbooks and data.
- Image Recognition: Enables users to capture images of their pets, which are then analyzed for visual symptoms such as runny nose or watery eyes.
- Vet Locator: Helps users find nearby veterinary clinics and hospitals based on their location, providing contact information and addresses.
- Report Generation: Generates reports with diagnostic information and recommended actions, which can be shared with veterinarians for further consultation.
- Clone the repository:
https://github.com/asrayg/vetU.git
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Install dependencies Requirement.txt coming soon
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Run the application:
bash main.py (Yep you need to have a linux shell for this project. Sorry windows users)
- Launch the application.
- Enter the relevant symptoms and characteristics of your pet.
- Capture an image of your pet for visual analysis (optional).
- View the preliminary diagnosis and recommended actions.
- Use the vet locator feature to find nearby veterinary clinics if further consultation is needed.
Contributions to vetU are welcome! If you'd like to contribute to the project, please follow these steps:
- Fork the repository.
- Create a new branch (
git checkout -b feature/your-feature). - Make your changes and commit them (
git commit -am 'Add new feature'). - Push to the branch (
git push origin feature/your-feature). - Create a new Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.
- This project utilizes the OpenAI API for AI analysis.
- Image recognition is powered by the Roboflow platform.
- Veterinary resources are obtained from publicly available sources and web scraping techniques.