How to train & test on big image

[Oktai15]

Hello, @argman and @zxytim !

Thank you for your job it's really cool. I need your advice.

I have a lot of image that have size about 4000x3000 and a lot of small text bbox's on each image.
What should I do on training? I see two ways:

1. directly pass this size and increase max_side_length & decrease text_scale;
2. cut big image into pieces (but text can be splitted)

And what should I do on testing? Again two ways:

1. directly pass this size and increase max_side_length & decrease text_scale;
2. cut big image into pieces (here I can use NMS)

What would you choose? Or maybe something else?

Btw, do you support multi-scale training?

Thanks in advance!

[argman]

I would choose the first one, if it cannot fit into gpu-memory ,then you can downsize a bit or train a smaller network

[Oktai15]

@argman, thanks for answer!
You skipped one question about multi-scale training)

[argman]

I have already cut pieces during training(but ensure text will not be splitted), tuning of parameters may help, it depends on your situation

[Oktai15]

@argman , okay, my last questions:
Could you point at code where you ensure that bounding boxes won’t be splitted?
Do you restore right coordinates on testing to use NMS and correct problem with splitted texts?