ds_task_recycling_project/docs/API_Documentation.md

Memory Module Detection System

A computer vision system for detecting memory modules in images and videos using YOLO object detection.

Features

• Image Detection: Upload images to detect memory modules
• Video Processing: Process video files frame-by-frame
• Bounding Box Visualization: See detected objects with confidence scores
• Detailed Analytics: Get detection statistics and metrics
• REST API: Fully documented API endpoints
• Web Interface: User-friendly browser interface

Requirements

• Python 3.8+
• CUDA-enabled GPU (recommended for best performance)
• Docker (optional)

Installation

1. Clone the repository

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

2. Set up Python environment

python -m venv venv
source venv/bin/activate  # Linux/MacOS
venv\Scripts\activate    # Windows

3. Install dependencies

pip install -r requirements.txt

4. Download YOLO model

Place your .pt model file in the models/ directory and update config.py with the correct path.

Configuration

Edit config.py to customize:

• Model paths
• Confidence thresholds
• File size limits
• Server host/port settings

Running the Application

Development Mode

python backend/app.py

Production Mode (with Gunicorn)

gunicorn --bind 0.0.0.0:5000 backend.app:app

Docker

docker build -t memory-detection .
docker run -p 5000:5000 memory-detection

API Documentation

Endpoints

Endpoint	Method	Description
/	GET	Web interface
/api/health	GET	Service health check
/api/v1/detect	POST	Detect memory modules in image
/api/v1/detect/video	POST	Process video for detections
/api/v1/results/<filename>	GET	Retrieve result images

Example Requests

Image Detection:

curl -X POST -F "image=@test.jpg" http://localhost:5000/api/v1/detect

Video Processing:

curl -X POST -F "video=@test.mp4" -F "fps=2" -F "max_frames=100" http://localhost:5000/api/v1/detect/video

Web Interface

Access the web interface at http://localhost:5000:

1. Upload Images:

   • Supported formats: JPG, PNG
   • Max file size: 10MB (configurable)

2. Process Videos:

   • Supported formats: MP4, AVI, MOV
   • Adjustable FPS and frame limits
   • Detailed frame-by-frame results

Project Structure

memory-detection/
├── backend/               # Core application
│   ├── app.py             # Flask application
│   ├── config.py          # Configuration
│   ├── detector.py        # YOLO detection logic
│   ├── exceptions.py      # Custom exceptions
│   ├── utils.py           # Helper functions
│   ├── video_processor.py # Video handling
│   └── templates/         # Frontend templates
│       └── index.html     # Web interface
├── models/                # YOLO model files
├── uploads/               # Temporary upload storage
├── results/               # Detection result images
├── tests/                 # Unit tests
├── requirements.txt       # Python dependencies
└── README.md              

Troubleshooting

Common Issues:

1. Model not loading:

   • Verify model path in config.py
   • Check file permissions

2. CUDA errors:

   • Ensure compatible CUDA version is installed
   • Try CPU-only mode by modifying detector.py

3. File upload issues:

   • Check MAX_FILE_SIZE in config
   • Verify file extensions are allowed