MrGiovanni / MrGiovanni/ModelsGenesis
Questions about data pre-processing.
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Description
This is a wonderful work, and there are some questions about data perocessing.
Question 1: When preparing our own image data, we always scale the data between -1 and 1. And I see the author process the data into 0 and 1. Is it necessary to scale the input data to 0 and 1?
Question 2: The author provide a UNet3D based model, and the number of the model class is 1. If we want use the author's pretrained model with 4 class (or other class), is it worked by loading the network layer without "module.out_tr.final_conv.weight", and just fine-tune the model? Do we need fixing the model layer and with a two stage training?
Thanks and looking forward your reply!
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First steps
- Read the whole issue, then the project's contributing guide.
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Research direction
No file, test, or entry point is identified; start by locating the preprocessing and UNet3D fine-tuning documentation or examples. Done means documenting the input scaling guidance and the supported procedure for adapting the one-class pretrained model to four or more classes.
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Assessment
- Tech stack
- jupyter-notebook, keras, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100