https://github.com/octonawish-akcodes/facialtraitanalyzer
Containerized Django web application that performs age and gender detection on uploaded images using OpenCV and ML.
https://github.com/octonawish-akcodes/facialtraitanalyzer
age-detection containerization django-project docker docker-compose face-detection gender-detection opencv-python
Last synced: about 2 months ago
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Containerized Django web application that performs age and gender detection on uploaded images using OpenCV and ML.
- Host: GitHub
- URL: https://github.com/octonawish-akcodes/facialtraitanalyzer
- Owner: octonawish-akcodes
- Created: 2023-12-30T08:12:31.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-01-11T17:14:35.000Z (over 1 year ago)
- Last Synced: 2025-02-04T03:02:03.152Z (3 months ago)
- Topics: age-detection, containerization, django-project, docker, docker-compose, face-detection, gender-detection, opencv-python
- Language: Python
- Homepage:
- Size: 82.6 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# FacialTraitAnalyzer (Age and Gender Detection Web App) 👦👩🔍
## Overview:
FaceTraitsAnalyzer is a Django web application designed for age and gender detection in images. Leveraging the power of OpenCV and pre-trained models, this application allows users to upload images and receive real-time analysis of facial features. This is a Django web application that performs age and gender detection on uploaded images using OpenCV and pre-trained models.
## Key Features:
- **Age Detection:** Accurately estimates the age range of individuals in uploaded images. 🎂
- **Gender Detection:** Identifies the gender of faces with high precision. ♂️♀️
- **User-Friendly Interface:** Intuitive web interface for seamless image upload and result presentation. 🌐
- **Visual Insights:** Presents detection results overlaid on the uploaded images for a comprehensive analysis. 📊
## Project Structure 📂
```plaintext
.
├── Dockerfile
├── README.md
├── age_gender_detection_app
│ ├── __init__.py
│ ├── __pycache__
│ │ ├── __init__.cpython-310.pyc
│ │ ├── admin.cpython-310.pyc
│ │ ├── apps.cpython-310.pyc
│ │ ├── forms.cpython-310.pyc
│ │ ├── models.cpython-310.pyc
│ │ ├── urls.cpython-310.pyc
│ │ └── views.cpython-310.pyc
│ ├── admin.py
│ ├── age_deploy.prototxt
│ ├── age_net.caffemodel
│ ├── apps.py
│ ├── forms.py
│ ├── gender_deploy.prototxt
│ ├── gender_net.caffemodel
│ ├── migrations
│ │ ├── 0001_initial.py
│ │ ├── __init__.py
│ │ └── __pycache__
│ │ ├── 0001_initial.cpython-310.pyc
│ │ └── __init__.cpython-310.pyc
│ ├── models.py
│ ├── opencv_face_detector.pbtxt
│ ├── opencv_face_detector_uint8.pb
│ ├── templates
│ │ ├── result.html
│ │ └── upload_image.html
│ ├── tests.py
│ ├── urls.py
│ └── views.py
├── age_gender_detection_project
│ ├── __init__.py
│ ├── __pycache__
│ │ ├── __init__.cpython-310.pyc
│ │ ├── settings.cpython-310.pyc
│ │ ├── urls.cpython-310.pyc
│ │ └── wsgi.cpython-310.pyc
│ ├── asgi.py
│ ├── settings.py
│ ├── urls.py
│ └── wsgi.py
├── compose.yaml
├── db.sqlite3
├── manage.py
├── media
│ └── uploads
│ ├── 1487718277-screen-shot-2017-02-21-at-60424-pm.png
│ ├── Screenshot_2023-12-26_204504.png
│ ├── istockphoto-1147066751-612x612_h4qn96t.jpg
│ └── result.png
└── requirements.txt
```
## Prerequisites 🛠️
- Python 3
- Django
- OpenCV
## Getting Started 🚀
1. **Clone the repository:**
```bash
git clone https://github.com/octonawish-akcodes/FacialTraitAnalyzer.git
```
2. **Install the required dependencies:**
```bash
pip install -r requirements.txt
```
3. **Apply migrations:**
```bash
python manage.py migrate
```
4. **Run the development server:**
```bash
python manage.py runserver
```
The app should be accessible at [http://127.0.0.1:8000/age_gender/](http://127.0.0.1:8000/age_gender/).
> My 8000 port was busy so I used 8001.
## Docker Usage Section 🐳
1. **Pull the Docker image from Docker Hub:**
```bash
docker pull abhidocker12/age_gender_detection:latest
```
2. **Run the Docker container:**
```bash
docker run -p 8000:8000 abhidocker12/age_gender_detection:latest
```
Access the Django application in your web browser at http://localhost:8000/age_gender/upload/.
## Usage 🖼️
1. **Visit [http://127.0.0.1:8000/age_gender/upload/](http://127.0.0.1:8000/age_gender/upload/) in your web browser.**
2. **Upload an image using the provided form.**
3. **Click "Submit" to perform age and gender detection.**
4. **View the detection result, including the detected image, gender, and age.**