10.Jan.2024
This HTML code contains a simple web application that can perform image analysis and object recognition in the browser using TensorFlow.js. First, let's look at TensorFlow and model concepts.
What is TensorFlow?
TensorFlow is an open source library used to develop machine learning and deep learning projects. This library is specifically designed to model and optimize learning processes by performing complex mathematical calculations on large data sets. TensorFlow.js is the JavaScript version of TensorFlow and is used to run machine learning models in the browser.
What is a Model?
Models are algorithms that are trained to perform a specific task in machine learning and deep learning projects. For example, a model that analyzes images can recognize objects in an image. COCO-SSD (Common Objects in Context - Single Shot Multibox Detector) is one such model and can be used with TensorFlow.js. This model is capable of recognizing objects across a wide range of object classes.
Now, let's consider the JavaScript part on the HTML code:
handleImage function that fires when the user selects an image.
The resizeImage function resizes the selected image to a specific size.
The TensorFlow.js library and COCO-SSD model are loaded.
The model makes object predictions on the reduced image.
Predictions are marked visually and displayed in a list.
Advanced Feature: Sending Analysis Results to the Server
The resulting analysis results can, for example, be sent to a server and these results can then be used for processing. This can increase the potential for the user to integrate results obtained directly in the browser with other applications or systems. Adding an HTTP request to communicate with the server can be a step to implement this functionality.
This code provides a simple object recognition implementation using TensorFlow.js and the COCO-SSD model. It can be developed or customized according to your needs.
Site link for sample application and source code:https://ai.milivolt.news/imagesa.html
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