https://github.com/bevinaa/paw-scan-mobile-application
Paw Scan is a mobile application designed to classify the breed of cats and dogs making the breed classification accessible to pet owners, vets, shelters, and animal enthusiasts, all from a mobile.
https://github.com/bevinaa/paw-scan-mobile-application
flask flutter python render
Last synced: about 2 months ago
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Paw Scan is a mobile application designed to classify the breed of cats and dogs making the breed classification accessible to pet owners, vets, shelters, and animal enthusiasts, all from a mobile.
- Host: GitHub
- URL: https://github.com/bevinaa/paw-scan-mobile-application
- Owner: Bevinaa
- Created: 2025-07-07T03:38:34.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2025-07-07T16:23:39.000Z (12 months ago)
- Last Synced: 2025-07-07T17:39:49.514Z (12 months ago)
- Topics: flask, flutter, python, render
- Language: Python
- Homepage:
- Size: 6.25 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 🐾 Paw Scan
**Paw Scan** is a Flutter-based mobile application that classifies cat and dog breeds using deep learning transformer models. It acts as the mobile frontend for the project [Breed-Classification-of-Cats-and-Dogs-Using-Transformer-Architecture](https://github.com/Bevinaa/Breed-Classification-of-Cats-and-Dogs-Using-Transformer-Architecture), where image classification is handled via a backend hosted on Render.
> ⚠️ This version requires an internet connection to send images to a web API. Hosted on Render's free tier - may trigger memory limits if usage is high.
---
## Features
- Capture or select an image of a cat or dog.
- Backend uses ViT, Swin, and DeiT transformer models for breed classification.
- Displays predicted breed name and confidence.
- Communicates with a hosted Python API for inference.
---
## Tech Stack
> ⚠️ Ensure that you have your two folders for flask and futter. After cloing the repository segregate the appropriate files to correct folders.
### Frontend
- **Flutter** (Dart)
- **Material Design UI**
- **HTTP** for backend communication
### Backend (Linked Project)
- **PyTorch** with `timm` transformer models
- **Residual MLP** for classification
- **Flask/FastAPI** for API endpoints
- **Hosted on**: [Render](https://render.com)
---
## Getting Started
> ⚠️ Ensure that you have your mobile phone connected as a emulator and test it by using 'flutter devices' in cmd.
1. **Clone the repository**:
```bash
git clone https://github.com/Bevinaa/Paw-Scan.git
cd Paw-Scan
```
2. **Install Flutter packages**:
```bash
flutter pub get
```
3. **Set your backend API URL from Render**:
```bash
'https://your-api-url.onrender.com/predict';
```
4. **Run the app**:
```bash
flutter run
flutter build apk
---
## Related Repository
[Breed-Classification-of-Cats-and-Dogs-Using-Transformer-Architecture](https://github.com/Bevinaa/Breed-Classification-of-Cats-and-Dogs-Using-Transformer-Architecture)
---
## Mobile Application - Overview
| UI of the App | Prediction |
|------------|--------------|
|  |  |
---
## Contributions
Contributions, feedback, and issues are welcome! Feel free to fork the repository and submit a pull request.
---
## Contact
For questions or further information, please contact:
- **Name:** Bevina R
- **Email:** bevina2110@gmail.com
- **GitHub:** [Bevinaa](https://github.com/Bevinaa)
---