This tutorial shows, how to use the Image Analysis Software, Enterprise software to train your own image object detector, in particular for eyes detection. The object detector is trained on the positive (eyes) and negative (randomly choosen background images) training set. The detection process is performed mostly in real-time.
Please note that this is a tutorial, i.e. a simplified version of a previous real BurgSys's project. The objective is not to achieve the best possible accuracy but to provide easy to understand and easy to configure example. Accuracy of the process can be improved significantly by model optimization and more information you can also get at BurgSys training.
Loading input data sets. Since the training data set size is quite limited, an extended training set is generated in order to achieve better accuracy.
An object detector is trained and stored to disk.
Detection process - the stored detector is loaded from the disk and applied to a testing image.1)
When the model is trained and validated, the detection can run in real-time, 24 hours a day, 7 days a week and automatically analyse millions of images.1)
1) Acknowledgment: Image sources provided for free by FreeDigitalPhotos.net. See acknowledgement.This tutorial shows how to train an object detector to detect eyes from images in real-time.
Download Process
Download input data
According to the given positive and negative input training set (positive images - eyes, negative images other parts of a face or image background), the object detector is trained. There are several different types of image detectors (each of them is for diffirent types of data). After the training, the model is saved and then it is used for object detection in an input image.
Processing steps - training:
Processing steps - testing:
Try to generate a new image data or change the detector type or its parameters.
