🐾 Animal Detection System

An AI-powered Animal Detection System built with Flask, YOLOv11, OpenCV, and MySQL. The application detects people and supported animal classes from uploaded images or a live webcam feed, stores results in a relational database, generates reports, provides REST APIs with Swagger documentation, and visualizes detection statistics using NumPy and Matplotlib.

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Features

• User Registration & Login
• Secure Session Management
• Image Upload
• YOLOv11 Animal & Person Detection
• Live Webcam Detection
• Detection Results with Confidence Scores
• MySQL Database Integration
• CSV Report Generation
• PDF Report Generation
• Detection Analytics (Bar Graph)
• REST APIs
• Swagger API Documentation

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Technology Stack

Layer Technologies

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Frontend HTML, CSS, Jinja2 Backend Python, Flask AI Model YOLOv11 (Ultralytics) Database MySQL Computer Vision OpenCV Analytics NumPy, Matplotlib Documentation Swagger (Flasgger)

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System Architecture

             +----------------------+
             |      Web Browser     |
             +----------+-----------+
                        |
                        v
              Flask Web Application
                        |
      +-----------------+-----------------+
      |                 |                 |
      v                 v                 v
 Authentication   YOLOv11 Detector    REST APIs
      |                 |                 |
      +--------+--------+                 |
               |                          |
               v                          v
          MySQL Database          Swagger Documentation
               |
               v
      CSV / PDF Reports / Graph Analytics

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Screenshots

Create a folder named screenshots and place the following images inside it.

Login

Dashboard

Detection Results

Detection Analytics

Live Webcam Detection

PDF Report

CSV Export

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REST API Endpoints

Method Endpoint Description

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POST /api/register Register a user POST /api/login Login POST /api/logout Logout POST /api/upload Upload images GET /api/detect Run detection GET /api/history Upload history GET /api/results/<image_id> Detection results GET /api/profile User profile DELETE /api/image/<image_id> Delete image

Swagger UI:

http://127.0.0.1:5000/apidocs

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Skills Demonstrated

• Flask Development
• REST API Design
• Swagger Documentation
• MySQL Database Design
• SQL Relationships
• Session Authentication
• Computer Vision
• YOLOv11 Integration
• OpenCV
• NumPy
• Matplotlib
• PDF & CSV Report Generation
• Git & GitHub

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Future Improvements

• JWT Authentication
• Docker Support
• Cloud Deployment
• Object Tracking in Video
• React Frontend
• Email Notifications
• Admin Dashboard

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Installation

git clone <repository-url>
cd AnimalDetection

python -m venv .venv

# Windows
.venv\Scripts\activate

# macOS / Linux
source .venv/bin/activate

pip install -r requirements.txt

python app.py

Open:

http://127.0.0.1:5000

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Author

Divyam Choudhary

AI-powered Animal Detection System built as a portfolio project demonstrating Computer Vision, Flask backend development, REST APIs, MySQL integration, analytics, and reporting.