tensorrt, SSD, NMS with different width height feature maps

I have succesfully converted a custom tensorflow object detection ssd model to tensorrt 4.0.16.
I’m running an input with 1600x1600 and its output is as expected.
I want to change the input to 1920x1080 and have accordingly change config.py and the plugin code to support that.

Input = gs.create_node(
    # batch, channels, height, width
    shape=[1, 3, 1080, 1920])

PriorBox = gs.create_node(
    aspectRatios=[1.0, 2.0, 0.5, 3.0, 0.33],
    layerVariances=[0.1, 0.1, 0.2, 0.2],
    featureMapShapesWidth=[240, 120, 60, 30, 15, 7],
    featureMapShapesHeight=[135, 68, 34, 17, 9, 4])

The serialized engine is correctly created and loaded.
The problem is that i keep getting saturated x0,x1 values (y0,y1 is correct) to 1.

The question is NMS been tested with different feature map sizes for width and height ? Is this a known bug ?

why my posts are hidden ?

I have the similar issues. Have you solved this problem?

maybe feature maps are not correct

hey, were you able to address this problem? Can you provide more details of the model you were using and the sample code you based the config.py file from?