Tensorflow F-RCNN first stage input and output strides
Let me try to explain what exactly stride means generally, then you'll be able to address your specific problem.
Let's say we have an images of size 7x7. Let's take a kernel of size 3x3. When you slide the kernel over image with :
1. stride=1 


2. stride=2


Essentially stride means how much gap you should leave between two kernel position while applying convolution operation.
Now this concept is generic and applies to any operation where we need to slide a kernel over an input.

For Faster-RCNN model, features and anchors are two different things, so probably they're unrelated. Confirm this with official paper though.
For stride size, there is no restriction, you can take it whatever number you want, just make sure it should be less than or equal to half of the size of image(you can think why logically).