Object Detection Using Tensor Flow In Shopping Malls

Object Detection Using Tensor flow in Shopping Malls

Abstract:-

Object Detection is the process of finding real-world object instances like car, bike, TV, flowers, and humans in still images or Videos. It allows for the recognition, localization, and detection of multiple objects within an image which provides us with a much better understanding of an image as a whole. It is commonly used in applications such as image retrieval, security, surveillance, and advanced driver assistance systems (ADAS). Creating accurate Machine Learning Models which are capable of identifying and localizing multiple objects in a single image remained a core challenge in computer vision. But, with recent advancements in Machine Learning and Deep Learning, Object Detection applications are easier to develop than ever before. Tensor Flow’s Object Detection API is an open source framework built on top of Tensor Flow that makes it easy to construct, train and deploy object detection models. Tensor flow is Google’s Open Source Machine Learning Framework for dataflow programming across a range of tasks. Nodes in the graph represent mathematical operations, while the graph edges represent the multi-dimensional data arrays (tensors) communicated between them.