An Alternative Fashion to Automate the Appropriateness of ALT-Text using Microsoft Computer Vision API

Abstract

Designing and releasing of software’s in production that contains images takes a lot of time due to the need of finding ALT-text attributes for the images embedded in the applications. This paper automates the task of writing ALT-text attributes in HTML, especially if image integration is large with the use of python PIP package and Microsoft Computer Vision API. This will save huge time and efforts of the developers by automating the task of captioning images manually up to a great extent. The challenge that confronts us is the quality of annotations generated by the machine with respect to the human generated annotations. To study the appropriateness of the captions delivered by APIs, a blend of human and machine assessment was used. We have noticed a high similarity in human and machine generated annotations as we obtained individual and cumulative BLEU score metric . Another metric is confidence score with a percentage mean of 0.5 .Also, we have calculated the time taken per caption which is 1.6 seconds per image which took 6.01 minutes to caption 200 images.