https://github.com/protheeuz/yolov11-flask
Object Detection Web App using YOLOv11 and Flask. Supports RTSP Streams and Video Uploads. A study case for a Fall Detection System for the Elderly.
https://github.com/protheeuz/yolov11-flask
cctv-detection cctv-monitoring cctv-surveillance flask object-detection realtime rtsp yolov10 yolov8
Last synced: 7 months ago
JSON representation
Object Detection Web App using YOLOv11 and Flask. Supports RTSP Streams and Video Uploads. A study case for a Fall Detection System for the Elderly.
- Host: GitHub
- URL: https://github.com/protheeuz/yolov11-flask
- Owner: protheeuz
- Created: 2024-07-12T15:43:40.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-19T12:42:22.000Z (8 months ago)
- Last Synced: 2025-02-19T13:39:07.916Z (8 months ago)
- Topics: cctv-detection, cctv-monitoring, cctv-surveillance, flask, object-detection, realtime, rtsp, yolov10, yolov8
- Language: CSS
- Homepage:
- Size: 62.1 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
## YOLOv11 - Flask
Object Detection Web App using YOLOv11 and Flask. Supports RTSP Streams and Video Uploads. A study case for a Fall Detection System for the Elderly.
----------------------------------------------------------------
## Features
**1. User Authentication:**
+ Secure login and registration functionality using Flask-Login.
+ Supports session management for user access.
**2. Object Detection:**
+ Utilitizes YOLOv11 for *real-time object detection*.
+ Allows video uploads for processing
+ Provides RTSP stream integration for live detection
**3. File Management:**
+ Uploaded videos and detected frames are stored in a structured directory.
+ Automatically cleanup of old detection files to maintain storage efficiency.
**4. Real-Time Notifications:**
+ Displays the count of new logins since the current day for authenticated users.
**5. Cross-Origin Resource Sharing (CORS):**
+ Configured to allow specific resources to be accessed from external domains.
## Installation
**1. Clone the repository:**
```git clone https://github.com/protheeuz/YOLOv11-Flask.git```
**2. Install dependencies:**
```pip install -r requirements.txt```
**3. Create and configure a .env file:**
+ Define environment variables such as database credentials, Flask secret key, and other required settings.
**4. Initialize the database:**
+ Execute the necessary SQL scripts or ORM migrations to set up the database schema.
**5. Run the application:**
```python app.py```
**6. Access the web app:**
+ Open your browser and navigate to ``http://localhost:PORT``.
----------------------------------------------------------------
## Directory Structure
```
.
├── config.py # Configuration for Flask and other services
├── database.py # Database connection and teardown handlers
├── detection.py # Cleanup and detection-specific logic
├── models.py # Database models and user-related operations
├── views/
│ ├── auth.py # Routes for authentication
│ ├── main.py # Main application routes
├── static/
│ ├── uploads/ # Uploaded videos and detection files
├── templates/ # HTML templates for the Flask app
├── main.py # Entry point for the Flask app
├── requirements.txt # Python dependencies
├── auth_bp.py # Authentication logic and routes
├── additional_logic.py # Auxiliary functions and custom features
└── rtsp_handler.py # RTSP streaming and fall detection logic
```
----------------------------------------------------------------
## Configuration
+ UPLOAD_FOLDER: Path to the directory where uloaded files are stored.
+ DETECTION_IMAGES_FOLDER: Path to the directory for detection result images.
+ PUBLIC_URL: Publicly accessible URL for the application.
+ ALLOWED_EXTENSIONS: Set of allowed file extensions for upload.
+ CONFIDENCE_THRESHOLD: Confidence threshold for object detection labels.
----------------------------------------------------------------
## Cleanup Task
A background thread is implemented to periodically clean up old detection files. The task runs every 30 seconds to ensure storage is managed efficiently.
----------------------------------------------------------------
## Usage
**1. Login:**
+ Create an account or log in using your credentials.
**2. Upload Video:**
+ Navigate to the upload page and upload a video file.
**3. Real-Time Detection:**
+ Monitor object detection output directly on the application.
**4. RTSP Stream Monitoring:**
+ Add RTSP stream URLs for live monitoring and fall detection.