Age and Gender Prediction Web Application using ResNet-50 Model
The Age and Gender Prediction Web Application is a user-friendly tool developed using the Flask framework and a trained ResNet-50 model. This web application allows users to upload photos or capture images using their webcam, providing real-time predictions of the age and gender of individuals depicted in the images. The application utilizes Python, Flask, OpenCV, Tensorflow, and Numpy to deliver accurate and convenient age and gender predictions.
This project focuses on the development of a web application that utilizes a trained ResNet-50 model for age and gender prediction. The application allows users to upload photos or use their webcam to capture images, and it provides real-time predictions of the age and gender of the individuals in the photos.
The Age and Gender Prediction Web Application using the ResNet-50 Model is designed to accurately predict the age and gender of individuals from photos. The application utilizes a ResNet-50 model that has been trained on a large dataset of facial images to learn patterns and features associated with age and gender attributes.
The Flask framework is employed to build the web application, providing a user-friendly interface for users to interact with. The application allows users to upload photos from their devices or use their webcam to capture images. Once an image is provided, the ResNet-50 model processes the image and makes predictions regarding the age and gender of the individuals depicted.
The application displays the predicted age and gender labels to the user, providing real-time results. Users can also download the processed images with the predicted labels for future reference or sharing. The application offers a seamless and convenient way to obtain insights into the age and gender characteristics of individuals based on facial images.
Flask, OpenCV, Tensorflow, Numpy