A gender Detection and age prediction web application developed using Flask, Open CV, HTML & CSS
- The frontend of the application is built using HTML & CSS
- The backend is built using Flask and Open CV
First introducing you with the terminologies used in this advanced python project of gender and age detection –
Computer Vision is the field of study that enables computers to see and identify digital images and videos as a human would. The challenges it faces largely follow from the limited understanding of biological vision. Computer Vision involves acquiring, processing, analyzing, and understanding digital images to extract high-dimensional data from the real world in order to generate symbolic or numerical information which can then be used to make decisions. The process often includes practices like object recognition, video tracking, motion estimation, and image restoration.
OpenCV is short for Open Source Computer Vision. Intuitively by the name, it is an open-source Computer Vision and Machine Learning library. This library is capable of processing real-time image and video while also boasting analytical capabilities. It supports the Deep Learning frameworks TensorFlow, Caffe, and PyTorch.
A Convolutional Neural Network is a deep neural network (DNN) widely used for the purposes of image recognition and processing and NLP. Also known as a ConvNet, a CNN has input and output layers, and multiple hidden layers, many of which are convolutional. In a way, CNNs are regularized multilayer perceptrons.
To build a gender and age detector that can approximately guess the gender and age of the person (face) in a picture using Deep Learning on the Adience dataset.
Hello Guys,Let’s see an interesting application of Deep Learning applied to faces. We will estimate the age and figure out the gender of the person by live detecting or from a single image, Hereby I'm sharing a python web app project “ Age-Prediction-and-Gender-Detection ” . I have used the models trained by Tal Hassner and Gil Levi. The predicted gender may be one of ‘Male’ and ‘Female’, and the predicted age may be one of the following ranges- (0 – 2), (4 – 6), (8 – 12), (15 – 20), (25 – 32), (38 – 43), (48 – 53), (60 – 100). The front-end of the application is built using HTML, CSS and JavaScript The back-end is built using Flask and Open CV. It is very difficult to accurately guess an exact age from a single image because of factors like makeup, lighting, obstructions, and facial expressions. And so, we make this a classification problem instead of making it one of regression.
Ref: https://data-flair.training/ and Umang Tiwari
Make sure you have Python, OpenCV, Flask and PIL installed on your system to run this project.
- Download the contents of the repository
- Install the necessary prerequisites are by following command:-
pip3 install -r requirements.txt
- Type the following command inside the directory on your terminal
python3 app.py
- Click http://127.0.0.1:5000/ (Press CTRL+C to quit)
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