🚨 Suspicious Activity Detection

This project is a Flask-based web application for detecting suspicious activities in videos using deep learning models.
It provides a simple web interface where users can upload a video and choose a detection model to analyze events like:

• 🚗 Accident Detection
• 🛒 Shoplifting Detection
• 🔫 Weapon Detection

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📌 Features

• 🌐 Web interface built with Flask\
• 🎥 Upload video and perform real-time activity detection\
• ⚡ Multiple detection models (Accident, Shoplifting, Weapon)\
• 📊 Results are displayed with processed video frames\
• 🧩 Modular design (easy to add more models in the future)

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🛠️ Tech Stack

• Frontend: HTML, CSS (Flask Templates)\
• Backend: Python, Flask\
• Deep Learning Models: Pretrained Suspicious Activity Detection models\
• Libraries: OpenCV, TensorFlow/PyTorch (based on models), Numpy

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📂 Project Structure

finalproject/
│── scripts/
│   ├── app.py                # Main Flask app
│   ├── detect_flask.py       # Video frame generator
│   ├── detect_multi.py       # Multi-activity detection script
│   ├── detect_single.py      # Single-activity detection script
│   ├── suspicious_activity.py# Core model functions
│
│── templates/
│   ├── index.html            # Upload & model selection page
│   ├── result.html           # Detection results page
│
│── static/
│   └── uploads/              # Uploaded videos
│
│── results/                  # Output videos
│
│── testing.mp4               # Sample input video
│── output.mp4                # Sample output video

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🚀 How to Run

1️⃣ Clone the Repository

git clone https://github.com/yourusername/suspicious-activity-detection.git
cd suspicious-activity-detection

2️⃣ Create a Virtual Environment

python -m venv venv
source venv/bin/activate   # On Mac/Linux
venv\Scripts�ctivate      # On Windows

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Run the Flask App

cd scripts
python app.py

5️⃣ Open in Browser

Go to:
👉 http://127.0.0.1:5000/

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🖥️ Demo

Accident Detection Example

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📹 [Watch Demo Video]

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📌 Future Improvements

• Add real-time camera stream detection\
• Extend models for more suspicious activities (fights, robbery, etc.)\
• Improve UI/UX design for better visualization

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🤝 Contributors

• Your Name -- Project Developer

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📜 License

This project is licensed under the MIT License -- feel free to use and modify.