I need to detect a chair, but only when it's in center
So, I captured a video such that the chair covers all parts of the image in every frame
I need to classify between two classes - chair is in center AND chair is not in center
So, I am not getting how to tag each image?
As seen in the below image, should the tag region cover the entire frame?
You might want to think about the formulation of your problem. If you want to classify the entire image frame as to whether there is a chair in the center or not, you might want to cast it as an image classification problem rather than an object detection problem. Essentially you want to do a binary classification of the entire image as to whether there is a chair in the middle or not. So you would have a two class classification problem.
This would be simpler to train, because you would not have to supply bounding boxes, and result in a simpler and more portable model.
To build classification models easily in Watson Studio, you could check out https://cloud.ibm.com/docs/visual-recognition?topic=visual-recognition-tutorial-custom-classifier (programmatically) or https://dzone.com/articles/build-custom-visual-recognition-model-using-watson (with Watson Studio GUI)
If you would like to continue with object detection check out https://medium.com/@vincent.perrin/watson-visual-recognition-object-detection-in-action-in-5-minutes-8f97c4b613c3
Once you know where the chair is using object detection, you can do simple math to tell whether it is in the center or not.
