How to determine if image is something or not?
If you'd like to be able to predict if an image has a mouse, this is still a classification problem where you're classifying images into two classes -  Mouse and Not a Mouse. 
Any classifier you intend to use might need to learn a boundary to separate the mouse images from non mouse images in the n-dimensional input space. 
In case you employ a neural network, you could make do with just one output neuron that will ideally give high probability when the image is a mouse and low when there isn't a mouse in the image.
I have a trained model that determines if an image contains either cat or dog. I'm using SVM to classify. I want a new model that determines if an image is a mouse or not. It's different from the first model that classifies into 2 classes. This new model will return TRUE or FALSE only.
I don't think I can use a classifier model since I have only 1 class; the mouse. I don't intend to use the first model or anything related to it in the 2nd model.
What is the best way to approach this?