Comments (5)
Hi @manvirvirk
If you want to run training on your dataset, you should be able to do this by implementing pytorch Dataset interface and replace BrainSegmentationDataset with it.
from brain-segmentation-pytorch.
i want to run training on simple dataset of retina images. can you please elaborate in detail???
from brain-segmentation-pytorch.
from brain-segmentation-pytorch.
Here is a tutorial on how to implement custom dataset in pytorch: https://pytorch.org/tutorials/beginner/data_loading_tutorial.html
from brain-segmentation-pytorch.
i want to run on my database which contains 20 images and respective masks. What should be the dataset directory?
from brain-segmentation-pytorch.
Related Issues (20)
- Reproducibility issue HOT 5
- Training on a custom dataset HOT 1
- in_channels parameter change causes size mismatch HOT 5
- Retraining on own dataset HOT 1
- ValueError: Sample larger than population or is negative HOT 2
- Example on Colab not segmenting the tumor HOT 13
- A puzzle about the code HOT 1
- How can I run the docker container if my GPU isn't nvidia
- Very large images on my dataset
- Run on the test data HOT 3
- Can I run the code on test folder without the masks??
- google colab
- how can I apply other loss functions
- IoU of the model
- Negative loss value HOT 3
- After UNet Inference, how to overlay / superimpose the different size predicted masks to the original image size?
- dice
- Error
- manifest for nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04 not found: manifest unknown: manifest unknown
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from brain-segmentation-pytorch.