Scale Ratios

[ahkarami]

Dear @kuangliu,
Would you please explain how the scale_ratios in your code are defined?
I mean that, for example in the main paper of SSD, the scale ratios are between 0.2 up to 0.9; however as I saw in the script box_coder.py the scale_ratios are defined as below:
self.scale_ratios = (1., pow(2,1/3.), pow(2,2/3.))
I mean that all the values are greater than 1!!!

[ahkarami]

Hi @chenyuntc, @vaishnavm217, @Jumabek, @zmonoid, @nationalflag, @tfygg
I would appropriate, if one can answer my above question.

[vaishnavm217]

@ahkarami I am bit noob at this thing, although the box coder you are pointing at is of FPN, so check paper of that. SSD scales in repo seem right to me

[ahkarami]

@vaishnavm217,
Thank you for your answer. Would you please briefly explain the below parameters in the SSD script:

torchcv/torchcv/models/ssd/net.py

Lines 110 to 113 in 6291f3e

	steps = (8, 16, 32, 64, 100, 300)
	box_sizes = (30, 60, 111, 162, 213, 264, 315) # default bounding box sizes for each feature map.
	aspect_ratios = ((2,), (2,3), (2,3), (2,3), (2,), (2,))
	fm_sizes = (38, 19, 10, 5, 3, 1)

I mean the steps, box_sizes, aspect_ratios and fm_sizes.

[vaishnavm217]

steps are the space between each bounding box centers.
box_sizes are side of default bounding boxes.
Aspect ratios are self explainatory. There are used to change the size of the default bounding boxes
feature map sizes are the output dimension(wxh but as square sizes are used only one is mentioned) from the respective layers.
for more info look through net.py of SSD.
If it seems very confusing, try comparing it side by side with paper. helps a lot.
just see this too : http://jany.st/post/2017-11-05-single-shot-detector-ssd-from-scratch-in-tensorflow.html
Pretty good explaination

[ahkarami]

@vaishnavm217,
Thanks a lot for your help.