Training a model for object detection I am new to Machine Learning.  Need a little direction on how to proceed with training a model for object detection.  I have a complete training dataset and test dataset of cars with color images, annotations and bounding boxes.  This data set has 196 classes.

All google search mention use of pre-trained models.  However I want to train the model on this dataset to detect and predict bounding box values.  Did not find any on StackExchange either. 

Appreciate any pointers.

Thanks
You could try a "Mask R-CNN" The github page contains a keras model that could be trained by yourself. And there is also a link to an article how to train the model yourself step-by-step.