{"id":24324112,"url":"https://github.com/alihassanml/lums-ai-hackthon","last_synced_at":"2025-03-11T03:36:19.290Z","repository":{"id":270612742,"uuid":"910428109","full_name":"alihassanml/LUMS-AI-Hackthon","owner":"alihassanml","description":"LUMS AI Hackthon","archived":false,"fork":false,"pushed_at":"2025-01-01T20:13:23.000Z","size":25273,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-17T19:16:55.250Z","etag":null,"topics":["deep-learning","gru","lsm","magic","opencv","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/alihassanml.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-12-31T08:44:15.000Z","updated_at":"2025-01-06T15:39:47.000Z","dependencies_parsed_at":"2025-01-01T20:38:35.720Z","dependency_job_id":null,"html_url":"https://github.com/alihassanml/LUMS-AI-Hackthon","commit_stats":null,"previous_names":["alihassanml/lums-ai-hackthon"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alihassanml%2FLUMS-AI-Hackthon","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alihassanml%2FLUMS-AI-Hackthon/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alihassanml%2FLUMS-AI-Hackthon/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alihassanml%2FLUMS-AI-Hackthon/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/alihassanml","download_url":"https://codeload.github.com/alihassanml/LUMS-AI-Hackthon/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":242967686,"owners_count":20214280,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["deep-learning","gru","lsm","magic","opencv","tensorflow"],"created_at":"2025-01-17T19:17:09.685Z","updated_at":"2025-03-11T03:36:19.266Z","avatar_url":"https://github.com/alihassanml.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# LUMS AI Hackathon: Magic Wand Project 🪄\n\nWelcome to the **Magic Wand Project**, developed as part of the **LUMS AI Hackathon**! 🚀 Our innovative solution bridges the gap between gesture recognition and real-time AI-powered interaction, delivering a unique and engaging user experience.\n\n---\n\n## 🎯 Project Overview\n\nThe Magic Wand project leverages **Streamlit** and **Groq API** to create an intuitive and interactive application for gesture-based controls. This AI-driven system can detect and classify hand gestures in real time, enabling seamless integration with various applications.\n\n### Key Highlights:\n- Utilized **LSTMs** and **GRUs** for handling sequential data and long-term dependencies.\n- Achieved **89% accuracy** on Kaggle, securing **3rd place** on the leaderboard.\n- Designed with an easy-to-use interface powered by **Streamlit** for rapid deployment.\n- Integrated **Groq API** for high-performance model inference.\n\n---\n\n## 🚀 Features\n- **Real-Time Gesture Recognition**: Classify hand gestures with precision.\n- **Streamlined UI**: User-friendly interface for interaction and visualization.\n- **Robust Model**: Trained on 100-frame sequences using advanced deep learning techniques.\n- **Scalable Design**: Built for adaptability across various use cases.\n\n---\n\n## 🛠️ Tech Stack\n- **Frontend**: [Streamlit](https://streamlit.io/) for a responsive and interactive UI.\n- **Backend**: Python with integration of the **Groq API** for high-performance model serving.\n- **Deep Learning Framework**: TensorFlow/Keras for gesture recognition models.\n- **Deployment**: Scalable architecture ready for deployment in production.\n\n---\n\n## 📈 Model Performance\nOur gesture recognition model achieved the following:\n- **Accuracy**: 89% on test data.\n- **Leaderboard**: Secured **3rd place** on Kaggle during the LUMS AI Hackathon.\n\n---\n\n## 🏗️ Installation\n\n### Prerequisites\n- Python 3.8 or higher\n- Virtual Environment (optional but recommended)\n\n### Steps\n1. **Clone the Repository**:\n   ```bash\n   git clone https://github.com/alihassanml/LUMS-AI-Hackthon.git\n   cd LUMS-AI-Hackthon\n   ```\n\n2. **Install Dependencies**:\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n3. **Run the Application**:\n   ```bash\n   streamlit run app.py\n   ```\n\n4. **Access the Application**:\n   - Open your browser and navigate to `http://localhost:8501`.\n\n---\n\n## 🧠 How It Works\n1. **Data Collection**: Captures a sequence of 100 frames for each gesture.\n2. **Model Training**: Utilizes LSTM and GRU networks to handle sequential data and classify gestures.\n3. **Real-Time Prediction**: Inference pipeline powered by Groq API ensures fast and accurate predictions.\n\n---\n\n## 🤝 Contributions\nWe welcome contributions! If you'd like to improve this project, feel free to:\n1. Fork the repository.\n2. Make your changes.\n3. Submit a pull request.\n\n---\n\n## 📜 License\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.\n\n---\n\n## 🌟 Acknowledgments\nSpecial thanks to the **LUMS AI Hackathon** organizers and my incredible team for their collaborative efforts.\n\nFor more details, contact [Ali Hassan](https://github.com/alihassanml).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falihassanml%2Flums-ai-hackthon","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falihassanml%2Flums-ai-hackthon","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falihassanml%2Flums-ai-hackthon/lists"}