Deep learning bundle for object localization and identification
The Deep Learning library EasyLocate completes a range of image processing and analysis libraries that are in regular use with an extensive user base, mostly machine manufacturers who supply the semiconductor and electronics industries. It will be launched as part of the Open eVision 2.15 software of Euresys and can be used to locate and identify objects, products, or defects.
Image 1 | EasyLocate has the capability of distinguishing overlapping objects. It is suitable for counting the number of object instances. The users have time to evaluate the library, before they commit to a license payment. (Bild: Euresys SA)
Two main benefits have been identified for the new tool: Firstly, the library is very easy to use and fits seamlessly into a customer’s application. Secondly, with EasyLocate, the customer has time to evaluate the library, before they commit to a license payment. This is a major differentiating benefit to the customers, as with other products on the market, there is no opportunity to first evaluate them and see if they are appropriate for the machine considered. EasyLocate has the capability of distinguishing overlapping objects and is suitable for counting the number of object instances. It is based on Deep Learning algorithms and works by learning from examples. In practice, it predicts the bounding box surrounding each object, or defect, which was found in the image and assigns to each bounding box a class label. It must be trained with images where the objects or defects that must be found have been annotated with a bounding box and a class label. The deep learning network architecture was specifically designed for industrial machine vision applications. It is inspired from state-of-the-art architectures such as YOLO and RetinaNet.
Deep Learning Bundle
EasyLocate is part of the Deep Learning bundle of Open eVision. The Deep Learning bundle also includes EasyClassify, a library for the classification of images, that is used for defect detection and product recognition. The user of the Deep Learning bundle can also lean on the abilities offered by the EasySegment library, which is designed to ease the process of segmenting objects and defects. In the unsupervised mode, it is used for defect segmentation. It is trained with only good images and then segments the parts that differ from the standard model. In supervised mode, it can segment anything, including objects and defects. It requires a ground truth segmentation mask for each training image.
