Using Computer Vision to improve Health and Workplace safety

Recent developments in the field of training Neural Networks (Deep Learning) and advanced algorithm training platforms like Google’s TensorFlow and hardware accelerators from Intel (OpenVino), Nvidia (TensorRT) etc., have empowered developers to train and optimize complex Neural Networks in small edge devices like Smart Phones or Single Board Computers. This has led to a profusion of initiatives to use such trained models in the domain of Health and Safety (HSE) at workplace. Here is a summary of initiatives that Optisol Datalabs has been working on in the past year to improve safety and avoid accidents.Computer Vision Process Flow


Training a Computer vision model typically follows this process flow. The first step is to generate or collect training data. The training data can be generic images collected from google searches or propriety data collected in industrial premises. The training data is then labelled. This involves manually going over image by image and marking the objects (humans, trucks or other labels that need to be detected) with labels. The labeled dataset is converted into a format that the computer vision models needs to be trained. Typically training happens in a cloud ...


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