Abstract: The invention relates to a computer-implemented method for providing training image data (TBD) for training a function, in particular an object recognition function (F0), the method comprising the following steps: S1 Providing at least one annotated image (AB), the annotated image (AB) having at least one object (01, 02, 031, 032, 041, 042, 043, 05) comprising an annotation (L1, L2) associated with the at least one object, the annotation describing an image region in which the at least one object (01, 02, 031, 032, 041, 042, 043, 05) is contained; S2 selecting an object (01, 02, 031, 032, 041, 042, 043, 05) in the annotated image (AB); S3 replacing the image region described by the annotation (L1, L2) with a region of another image in order to remove the selected object (01, 02, 031, 032, 041, 042, 043, 05) together with the annotation (L1, L2) associated with the selected object (01, 02, 031, 032, 041, 042, 043, 05) from the annotated image (AB) and produce a modified annotated image (MAB); S4 providing the

Abstract: A computer-implemented method and system provides a labelled training dataset. At least one sub-object or component is selected in a CAD model of an object comprising a plurality of sub-objects or components. A plurality of different render images is generated and the different render images contain the at least one selected sub-object or component. The different render images are labelled on the basis of the CAD model to provide a training dataset based on the labelled render images. Also, a computer-implemented method provides a trained function that is trained on the training dataset. A computer-implemented image recognition method uses such the trained function. An image recognition system comprising an image capture device and a data processing system carries out the image recognition method. A computer program comprises instructions that cause the system to carry out the methods.

Abstract: A computer-implemented method and system provides a labelled training dataset. At least one sub-object or component is selected in a CAD model of an object comprising a plurality of sub-objects or components. A plurality of different render images is generated and the different render images contain the at least one selected sub-object or component. The different render images are labelled on the basis of the CAD model to provide a training dataset based on the labelled render images. Also, a computer-implemented method provides a trained function that is trained on the training dataset. A computer-implemented image recognition method uses such the trained function. An image recognition system comprising an image capture device and a data processing system carries out the image recognition method. A computer program comprises instructions that cause the system to carry out the methods.