Mask is an array full of 0, leads to Nan for logits

[gabrielvannier]

Thanks for this project !
This project is awesome. However I have an issue that occur really often and I can not figure out how to solve it :/

I am testing the repository in multi_frame using your script test.py. When starting the test, everything works fine and the predict fonction yields features correctly except for one thing : For almost half of the features the mask is an array full of 0 for the first two dimensions.

This imply that the new depth map (calculated on line 151 of test.py will be an array full of 0 :
depth_map = depth_map[..., 0]*masks[..., 0]

and the depth_mean will be an Nan value (because of division by 0) :
depth_mean = np.sum(depth_map) / np.sum(masks[..., 0])

And logits as well...
cla_ratio = flags.paras.cla_ratio depth_ratio = 1 - cla_ratio logits[0] = depth_ratio * depth_mean + cla_ratio * logits[0] logits[1] = 1.0 - depth_mean

So I need to figure out why the mask is an array full of 0, and how to fix the it to get the output I want !
If anybody could help me I would be very thankful !

PS : If you need any additional information let me know, I am 100% available

[gabrielvannier]

Also, what does the masks is supposed to represent ? what is its meaning ?

[nguyennhatkhoa99]

How do you calculate the depth map for input to the network. My image prediction always return to 0.