FastAPI Detection Results API

Overview

This project is a FastAPI-based web application for managing detection results. It provides RESTful API endpoints to create, retrieve, and delete detection results stored in a PostgreSQL database.

Features

• FastAPI framework for high-performance API development
• SQLAlchemy ORM for database interactions
• Pydantic for data validation and serialization
• PostgreSQL as the database backend
• Dependency injection for database sessions
• Exception handling for robustness

Project Structure

my_project/ ├── main.py # Entry point for FastAPI application ├── database.py # Database configuration and connection ├── models.py # SQLAlchemy database models ├── schemas.py # Pydantic schemas for request and response validation ├── crud.py # CRUD operations for database interactions ├── requirements.txt # Project dependencies └── README.md # Project documentation

Installation

Prerequisites

• Python 3.9+
• PostgreSQL installed and running

Step 1: Clone the Repository

sh git clone https://github.com/Azazh/Expose-the-Medical-Wearhouse-Data-Using-Fast-API.git cd Expose-the-Medical-Wearhouse-Data-Using-Fast-API

Step 2: Create a Virtual Environment

sh python -m venv venv source venv/bin/activate # On Windows use: venv\Scripts\activate

Step 3: Install Dependencies

sh pip install -r requirements.txt

Step 4: Configure Environment Variables

Create a .env file in the project root with the following content: ini DATABASE_URL=postgresql://postgres:yourpassword@localhost:5432/medical_dw

Step 5: Run Database Migrations (If Needed)

sh python -c 'from database import Base, engine; Base.metadata.create_all(bind=engine)'

Step 6: Start the FastAPI Application

sh uvicorn main:app --reload

The API will be accessible at: http://127.0.0.1:8000

API Endpoints

1. Create a Detection Result

http POST /detection_results/ Request Body: json { "image_path": "path/to/image.jpg", "class_label": "object", "confidence": 0.95, "x_min": 10, "y_min": 20, "x_max": 50, "y_max": 80 }

Response: json { "id": 1, "image_path": "path/to/image.jpg", "class_label": "object", "confidence": 0.95, "x_min": 10, "y_min": 20, "x_max": 50, "y_max": 80 }

2. Retrieve All Detection Results

http GET /detection_results/

3. Retrieve a Detection Result by ID

http GET /detection_results/{result_id}

4. Delete a Detection Result

http DELETE /detection_results/{result_id}

Testing the API

You can use tools like Postman or cURL to test API endpoints.

Example using cURL: sh curl -X GET http://127.0.0.1:8000/detection_results/

License

This project is licensed under the MIT License.

Author

azazh(https://github.com/azazh)