https://github.com/dinithmaleesha/flutter-image-classification
ClassiFy is a Flutter-based image classification app that uses machine learning to identify objects in images with confidence scores.
https://github.com/dinithmaleesha/flutter-image-classification
ai computer flutter-image-classification flutter-image-processing image-classification image-processing machine-learning
Last synced: 4 months ago
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ClassiFy is a Flutter-based image classification app that uses machine learning to identify objects in images with confidence scores.
- Host: GitHub
- URL: https://github.com/dinithmaleesha/flutter-image-classification
- Owner: dinithmaleesha
- Created: 2024-12-16T03:38:20.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2024-12-17T07:46:11.000Z (over 1 year ago)
- Last Synced: 2025-02-10T00:38:09.590Z (over 1 year ago)
- Topics: ai, computer, flutter-image-classification, flutter-image-processing, image-classification, image-processing, machine-learning
- Language: Dart
- Homepage:
- Size: 24.5 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ClassiFy 🔍
ClassiFy is a Flutter-based image classification app that uses machine learning to identify objects in images with confidence scores. This is a personal project I developed to bring an idea I had in mind for a few months to life.
## Features 🌟
- Classifies images using a TensorFlow Lite pre-trained MobileNet model.
- Displays the top three predictions with confidence scores.
- Simple and intuitive UI.
- Provides details about the app functionality via an info icon.
- Added some fake latency to enhance the user experience.
## How It Works 🔬
1. Pick an image from your device.
2. The app processes the image using the MobileNet model.
3. Get results showing the most probable classification along with confidence percentages.
## Technologies Used 🤖
- **Flutter**: To build the app.
- **TensorFlow Lite**: For on-device machine learning.
## Model Details 🔸
The app uses the MobileNet v1 model:
- Model: [MobileNet v1 1.0 224](https://github.com/emgucv/models/blob/master/mobilenet_v1_1.0_224_float_2017_11_08/mobilenet_v1_1.0_224.tflite)
> **Note:** I couldn't find the first source of the model. If I locate it, I will update this information.
## Getting Started 🚀
### Prerequisites
- Flutter SDK installed on your machine.
- An emulator or physical device to run the app.
### Installation
1. Clone the repository:
```bash
git clone https://github.com/dinithmaleesha/flutter-image-classification.git
cd flutter-image-classification
```
2. Install dependencies:
```bash
flutter pub get
```
3. Run the app:
```bash
flutter run
```
### Building the APK
To build the APK:
```bash
flutter build apk --release
```
The generated APK will be available in the `build/app/outputs/flutter-apk/` directory.
## Credits 🌟
- **Model**: MobileNet v1 from TensorFlow Lite.
- **Icons**: [Flaticon](https://www.flaticon.com).
## Future Improvements 🚒
- Enhance the UI with more interactive elements.
- Add support for additional models and image processing features.
- Improve result explanations for better user understanding.
## Contributions 🤝
Contributions are welcome! Feel free to fork this repository, make changes, and submit a pull request.
---
Developed with ❤️ by Dinith Maleesha.