The main aim of this project is to to build a gender and age detector that can approximately guess the gender and age of the person (face) in a picture or through webcam.. The dataset is downloaded from Kaggle.
Age assessment involves classifying the years into several categories. It is challenging to put together the photographs because people of different ages have different face features.
Several techniques are used to determine the age and gender of various faces. The convolution network borrows features from the neural network. The image is transformed into one of the age groups in light of the ready models. The highlights are dealt with in further detail and sent to the preparatory frameworks.
In this Python project, I used deep learning to precisely determine a person's gender and age using just one photograph of their face.'Male' or 'Female' may be the expected gender, and '0 - 2', '4 - 6', '8 - 12', '15 - 20', '25 - 32', '38 - 43', '48 - 53', or '60 - 100' may be the predicted age, with 8 nodes in the final softmax layer. Due to elements like cosmetics, lighting, obstacles, and facial expressions, it is quite challenging to determine an exact age from a single image. I have decided to use classification for gender and regression for age.
To go about the python project, we’ll:
-Detect faces
-Classify into Male/Female
-Classify into one of the 8 age ranges
-Put the results on the image and display it