A computer-implemented method for constructing a model in a neural network for object detection in an unprocessed image , the construction being performed based on at least one image training batch , the method comprising acts of: - Providing a neural network configured with a set of specifications ; - Establishing at least one image training batch , which batch comprises at least one training image comprising one or more objects where an individual object is a member of an object class ; - Providing a graphical user interface (GUI) configured for displaying a training image from the image training batch ; and - Iteratively performing following acts: o Annotating object(s) in the training image by user interaction generating individually annotated object(s) ; o Associating an annotation with an object class for the annotated object in the training image by user interaction ; o Returning a user annotated image training dataset comprising the training image with annotated object(s) , each individual annotated object associated with an object class ; and o Constructing a model by training one or more collective model variables in the neural network to classify the individual annotated object(s) as a member of an object class , which model in combination with the set of specifications when implemented in a neural network is capable of object detection in an unprocessed image with a certain probability of object detection , characterised by the method comprising a further act of performing intelligent augmentation , said intelligent augmentation comprises acts of processing multiple annotated objects in a training image and awarding each resulting augmented annotated object a weighting for a certain probability of occurrence. - Providing a neural network configured with a set of specifications ; - Establishing at least one image training batch , which batch comprises at least one training image comprising one or more objects where an individual object is a member of an object class ; - Providing a graphical user interface (GUI) configured for displaying a training image from the image training batch ; and - Iteratively performing following acts: o Annotating object(s) in the training image by user interaction generating individually annotated object(s) ; o Associating an annotation with an object class for the annotated object in the training image by user interaction ; o Returning a user annotated image training dataset comprising the training image with annotated object(s) , each individual annotated object associated with an object class ; and o Constructing a model by training one or more collective model variables in the neural network to classify the individual annotated object(s) as a member of an object class , o Annotating object(s) in the training image by user interaction generating individually annotated object(s) ; o Associating an annotation with an object class for the annotated object in the training image by user interaction ; o Returning a user annotated image training dataset comprising the training image with annotated object(s) , each individual annotated object associated with an object class ; and o Constructing a model by training one or more collective model variables in the neural network to classify the individual annotated object(s) as a member of an object class , <EOS>