Using Object Detection Model YOLOV7 with Tensorflow.Js

1. Introduction A few weeks ago, I was assigned a task at work involving object detection. As someone who primarily works on the frontend, I became curious was it possible to implement an object detection model directly in a browser based React app, without relying on a backend or Python-based inference? This blog post is a continuation of that research. It documents the step-by-step process I took to run a YOLOv7 model using TensorFlow.js within a React project. Along the way, I encountered several technical challenges particularly around model conversion and client-side rendering —that I believe are worth sharing. My goal is to make this post useful for fellow developers who are exploring the same idea or simply want to integrate machine learning into their frontend applications. I’ll walk you through everything from model conversion, preprocessing, inference, to displaying the results in a browser. Let’s get started. 2. What is YOLO and Why TensorFlow.js?

Apr 21, 2025 - 05:01

Using Object Detection Model YOLOV7 with Tensorflow.Js

1. Introduction

A few weeks ago, I was assigned a task at work involving object detection. As someone who primarily works on the frontend, I became curious was it possible to implement an object detection model directly in a browser based React app, without relying on a backend or Python-based inference?

This blog post is a continuation of that research. It documents the step-by-step process I took to run a YOLOv7 model using TensorFlow.js within a React project. Along the way, I encountered several technical challenges particularly around model conversion and client-side rendering —that I believe are worth sharing.

My goal is to make this post useful for fellow developers who are exploring the same idea or simply want to integrate machine learning into their frontend applications. I’ll walk you through everything from model conversion, preprocessing, inference, to displaying the results in a browser.

Let’s get started.