how to pretrain my image using resnet50 in mask-rcnn

Question

I am researching about mask r-cnn. I want to know how to pretrain my image(knife,sofa,baby,.....) using resnet50 in mask-rcnn. I struggle to find that in github, but I can't. Please help me anybody who know how to handle it.

Answer 1

Try this implementation of Mask RCNN on github here.

Answer 2

You can follow Mask_RCNN github repo. It has both resnet50 and resnet100 (might be wrong here). It is a beautiful implementation I would say. The base model is from FAIR (Facebook AI Research). There is a demo file which you can check before starting your work.

If it works well, you can see my answer, it will help you to train the model with your custom data. The answer is a bit long, but it lists all the steps.

Something which I personally like about this implementation is:

• It is easy to setup. Won't bother you much about the dependencies. Having a python virtual environment does the wonders.
• It falls back automatically from a CPU version to GPU and vice versa.
• It is having good support from its developers. It is getting commits frequently.
• The code is very customisable. So If you want to do some changes, it's pretty easy. Some booleans and numbers changes up and down and you are done...!!!