Basic conv+ReLU+pooling layer extract the feature maps of an image.
Collects the input of the feature maps and proposals. Combines those messages and extract the proposal feature maps
Calculate the class of the proposal by the proposal feature maps, and use the bounding box regression again to get the final precise point.
The python version of the faster RCNN test's internet structure
Tensor board-Loss collections
Recognition Rate