Efficient automation and accurate object detection have been an important advancement of computer vision systems.
With the increase in demand for deep learning techniques, the accuracy for object detection has increased periodically. Our
project aims to incorporate the existing technique for object detection to achieve library automation with high accuracy with
real-time performance and also interfacing it with the application of IoT. A major challenge in our project is computational
hardware, which leads to slow and nonoptimal performance. In this project, we use a completely deep learning-based approach
to solve the problem of object detection in an end-to-end fashion and as a result, we can automate the library using the following
technique with the help of solid-state relay. The network is trained on 500 images to generate its custom weights using darknet
config file.
