Built a Computer Vision-Powered App Using Gemini in Under 15 Minutes — No Training Required

Author(s): Areeb Adnan Khan

Originally published on Towards AI.

This member-only story is on us. Upgrade to access all of Medium.

Machine Learning Algorithm Illustration: Source Getty Images

Computer Vision is booming, and with the rise of multi modal AI models, it’s easier than ever to leverage its power. From industrial security checks to image classification and identification, the applications are rapidly expanding.

But if you’re just getting started and feeling overwhelmed by the sheer amount of information out there — don’t worry! This guide will walk you through performing image classification with almost 98% accuracy using zero-shot learning — no prior training required.

Zero-shot learning (ZSL) is a machine learning technique that allows models to classify images without having seen examples during training. This is incredibly powerful because:

It eliminates the need for large, labeled datasets.It enables models to generalize across categories.It saves time and computational resources.

By leveraging Pre-trained AI models, we can classify images on the fly using text-based descriptions — a game-changer for those who want fast, accurate results without deep AI expertise.

To get started, you need to install the genai library [1]. This is a generative AI library designed for IPython environments, making it an excellent tool for both learning and interacting with AI models.

Run the following command to install… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI