HALCON's Deep-Learning-Based Object Detection 1: Introduction and Preparation of the Dataset

In the first part of this tutorial series on HALCON's object detection, you will learn what object detection actually is, and what kinds of applications it can be used for. Then, we will have a look at the first program of an HDevelop example series on object detection. Within this program, we will have a look how to read in a dataset that you labeled, for example, with the MVTec Deep Learning Tool. Afterwards we will split this dataset, and preprocess the labeled data to be suitable for the deep learning model. Then, you will be ready for training, which we will learn about in the next video: https://youtu.be/9ux-eprJnBs 0:20 – Introduction of the technology 1:20 – Working with the HDevelop example detect_pills_deep_learning_1_prepare.hdev 1:48 – Read the dataset 2:00 – Split the dataset for training, validation, and testing 2:55 – Determine advanced parameters 3:35 – The available pretrained networks 4:00 – Preprocess the dataset In this video, HALCON 19.11 is used. www.mvtec.com www.halcon.com https://www.mvtec.com/products/deep-learning-tool/