About Project
It is challenging to tag multiple images in one go during image recognition; it becomes a persistent issue for our client. To solve this problem, we developed an application that utilizes artificial intelligence and machine learning technology to simultaneously identify and tag multiple images. The application recognizes objects in an image and then assigns appropriate tags to them. We have configured the application to learn from its mistakes and improve its accuracy over time. Additionally, it can recognize different types of images and assign separate tags to them. Through the classification, we have ensured that the tagging process is accurate and efficient.
What we did
Brainvire developed an application called “Tagger” using the latest technologies. This application allows users to tag several photos in a single go, quickly. It also uses face detection and recognition techniques to conduct an image search through thousands of images and detect a person the user intends to locate.
- Platform/OSWeb
- CategoryMedia & Entertainment
- Case StudyView Now >
Tech Stack
- .Net core
- Azure cloud
- jQuery
- Microsoft Cognitive Services
- Microsoft SQL Server
- Python
Features
Highlights
This app is compatible with Microsoft desktops and can handle large amounts of data at once. This app makes the end-users job more accessible and allows the management of metadata related to the images. It also allows users to create tags and organize data into different categories. It also provides a feature of auto-tagging, which can save time and effort for the users. The app allows users to access and manage the images' metadata and make necessary changes. This app is simple and easy to use, making it an excellent option for managing and organizing data.