Metadata-Version: 2.1
Name: gvision
Version: 0.8a1
Summary: End-to-end automation platform for computer vision projects.
Home-page: https://github.com/gaurang157/gvision
Author: Gaurang Ingle
Author-email: gaurang.ingle@gmail.com
Maintainer: Gaurang Ingle
Maintainer-email: gaurang.ingle@gmail.com
License: MIT
Project-URL: Bug Reports, https://github.com/gaurang157/gvision/issues
Project-URL: Source, https://github.com/gaurang157/gvision
Project-URL: Documentation, https://github.com/gaurang157/gvision/blob/main/README.md
Project-URL: Say Thanks!, https://github.com/gaurang157/gvision/issues/new?assignees=&labels=&template=thanks.yml
Keywords: computer vision,automation,model training,model deployment,object detection,segmentation,classification,pose estimation,deep learning,machine learning,Roboflow,Ultralytics,TensorFlow,TensorBoard,Streamlit,CLI interface,UI interface
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Natural Language :: English
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Application Frameworks
Classifier: Topic :: Software Development :: User Interfaces
Classifier: Topic :: Utilities
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: av ==11.0.0
Requires-Dist: numpy ==1.24.4
Requires-Dist: opencv-python ==4.9.0.80
Requires-Dist: opencv-python-headless ==4.8.0.74
Requires-Dist: pandas ==2.0.3
Requires-Dist: Pillow ==10.2.0
Requires-Dist: PyYAML ==6.0.1
Requires-Dist: Requests ==2.31.0
Requires-Dist: roboflow ==1.1.1
Requires-Dist: streamlit ==1.31.1
Requires-Dist: streamlit-ace ==0.1.1
Requires-Dist: streamlit-webrtc ==0.47.1
Requires-Dist: supervision ==0.18.0
Requires-Dist: torch ==2.2.0
Requires-Dist: ultralytics ==8.1.10
Requires-Dist: YAML2ST ==1.0.20
Requires-Dist: tensorboard >=2.10.0


![logo](https://raw.githubusercontent.com/gaurang157/gvision/main/logo.png)
# GVISION 🚀
GVISION is an end-to-end automation platform for computer vision projects, providing seamless integration from data collection to model training and deployment. Whether you're a beginner or an expert, GVISION simplifies the entire process, allowing you to focus on building and deploying powerful models.

## Features ✨

- **Easy-to-Use Interface:** Intuitive UI design for effortless project management and model development.
- **No Coding Required:** Build and train models without writing any code.
- **Roboflow Integration:** Easily download datasets from Roboflow for your computer vision projects.
- **Multiple Tasks Supported:** Develop models for object detection, segmentation, classification, and pose estimation.
- **Ultralytics Model Training:** Train your custom models using Ultralytics YOLOv8.
- **Live Monitoring with TensorBoard:** Monitor model training and performance in real-time using TensorFlow's TensorBoard integration.
- **Performance Monitoring:** View model performance and visualize results.
- **Quick Deployment:** Deploy trained models seamlessly for various applications.
- **Streamlit Deployment Demo:** Quickly deploy your trained models with Streamlit for interactive demos and visualization.

## Getting Started 🌟
1. **Note: Before Installation**
It's recommended to create a new Python environment or Conda environment before installing GVISION. This will prevent potential conflicts with your existing dependencies and ensure a smooth installation process.

2. **Installation**
You can install GVISION using pip:
```bash
pip install gvision
```
# Global CLI
3. **Run GVISION**: Launch the GVISION application directly in the Command Line Interface (CLI).
```bash
gvision
```
![Global cli](https://raw.githubusercontent.com/gaurang157/gvision/main/image.png)

# #UI:
![GVISION-AUTOMATION](https://raw.githubusercontent.com/gaurang157/gvision/main/assets/ss.png)

4. Import Your Data: Use the Roboflow integration to import datasets and preprocess your data.

5. Train Your Model: Utilize Ultralytics for training your custom models with ease.

6. Deploy Your Model: Showcase your trained models with Streamlit deployment for interactive visualization.

## Documentation 📚
For detailed instructions on how to use GVISION, check out the [Documentation](https://github.com/gaurang157/gvision#).

## License 📝
GVISION is licensed under the [MIT License](https://opensource.org/licenses/MIT).

## Contributing 🤝
We welcome contributions from the community! If you have any feature requests, bug reports, or ideas for improvement, please [open an issue](https://github.com/gaurang157/gvision/issues) or submit a [pull request](https://github.com/gaurang157/gvision/pulls).

## Upcoming Features 🚀
- **Video Support:** Upload video datasets and train models for video analysis.
- **Predicted Video Generation:** Generate predicted videos based on model inference results.

Version 0.9 of GVISION will introduce exciting new features, including video support and predicted video generation capabilities. Stay tuned for updates!


## Support 💌
For any questions, feedback, or support requests, please contact us at gaurang.ingle@gmail.com.




