In image recognition, the issue of object detection is considered to be challenging, mainly because of many PC vision programs depend on it, it is a crucial component of PC vision. Numerous identifying terms and frameworks have been explored for a long time as a solution to this problem. This paper's goal is to provide a concise overview of a number of object recognition and computer vision platforms. This paper primarily discusses AWS Image Rekognition, it's an AWS service that is reasonably sophisticated and simple to integrate with services like Lambda and offers a substantial amount of details in its analysis. The report includes a variety of perspectives that have been applied by diverse analysts to the identification and spotting of objects. AWS Image Rekognition can identify situations and items in the images used in this article, producing a confidence score for each label that ranges from 0% to 100%. Boto3, a Python client for AWS, and the detect labels method are used to do this. To do this, you need to provide a picture, a boundary on the amount of labels to return, a level of confidence for eliminating uncertain findings.