This code line is here:
ssd_300_mobilenet0.25_coco
Firstly, the first scale feature map is drawn from relu22_fwd
from mobilenetv1
, however when input data is 300 * 300, this layer’s feature map is 19 * 19, or actually 18 * 18
using mobilenet.py
in model_zoo
folder, which means that the step is actually 16.
Then, the step parameter in function ssd_300_mobilenet0.25_coco
is started from 8, and remains are [8, 16, 32, 64, 100, 300]
. I noted that the steps are used within anchor generation, and I want to know the step settings here could impact the training accuracy (mAP)?
thank you.