Comments (3)
WillBrennan
commented on June 30, 2024
Can you list the categories you've got in your validation set and in your training set and how many images are in each? Likewise the parameters you launched training with?
This error often occurs if you decrease the batch-size to 1.
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SaharGezer
commented on June 30, 2024
I have only one category:
INFO:root:categories: ['rail']
Training Set : 6800 Images
Val Set: 1700 Images
The net: BiSeNetV2
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WillBrennan
commented on June 30, 2024
My mistake; forgot those are in the logs above! This error is caused by batchnorm having a small batch. If you increase the batch-size this'll fix it. Its failing a check in batch-norm where it requires more than one sample per a channel to calculate the sample standard deviation per a channel.
Call train will giving --batch-size 8 should fix it.
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Related Issues (20)
- Assertion Error when replicating this code with Google Colab HOT 2
- pickle.UnpicklingError: invalid load key, 'v'. HOT 2
- Semantic Segmentation Tool HOT 1
- real time HOT 4
- CPU HOT 4
- CUDA error: no kernel image HOT 3
- Cannot launch "labelme" HOT 1
- Input Shape HOT 2
- coremltools conversion from pytorch to coreml HOT 1
- coreml conversion error HOT 1
- segmented images HOT 1
- Training error HOT 4
- Skin segmentation dataset HOT 1
- How did I get SS to show black and white skin mask HOT 1
- Tranfer learning HOT 1
- Understanding the terminal output during training HOT 4
- Multiple Classes
- Running out of memory HOT 2
- Unable to find fcn_resnet101_coco, and BiSeNetV2 HOT 1
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