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Prasanna1991 committed May 22, 2020
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3 changes: 3 additions & 0 deletions README.md
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Expand Up @@ -4,12 +4,15 @@ The implementation of "Semi-supervised Medical Image Classification with Global
# How to run?
python latent-mixing.py

For detail, follow run_main.sh

# Requirements:
1. pyTorch
2. pickle
3. PIL
4. torchvision
5. sklearn

There might be more requirements but shouldn't be difficult to install them using conda.

# Credit:
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26 changes: 26 additions & 0 deletions run_main.sh
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# For the case: labeled = 300

# Input mixup
python latent-mixing.py --augu --out 'Final_models/ip1@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'input' --alpha 1.0 --manualSeed 1 --noSharp --gpu 0
python latent-mixing.py --augu --out 'Final_models/ip2@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'input' --alpha 1.0 --manualSeed 2 --noSharp --gpu 0
python latent-mixing.py --augu --out 'Final_models/ip3@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'input' --alpha 1.0 --manualSeed 3 --noSharp --gpu 0
python latent-mixing.py --augu --out 'Final_models/ip4@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'input' --alpha 1.0 --manualSeed 4 --noSharp --gpu 0
python latent-mixing.py --augu --out 'Final_models/ip5@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'input' --alpha 1.0 --manualSeed 5 --noSharp --gpu 0

# Input + Latent mixup
python latent-mixing.py --augu --out 'Final_models/mn1@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'mixup_hidden' --alpha 2.0 --manualSeed 1 --noSharp --gpu 0
python latent-mixing.py --augu --out 'Final_models/mn2@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'mixup_hidden' --alpha 2.0 --manualSeed 2 --noSharp --gpu 0
python latent-mixing.py --augu --out 'Final_models/mn3@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'mixup_hidden' --alpha 2.0 --manualSeed 3 --noSharp --gpu 0
python latent-mixing.py --augu --out 'Final_models/mn4@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'mixup_hidden' --alpha 2.0 --manualSeed 4 --noSharp --gpu 0
python latent-mixing.py --augu --out 'Final_models/mn5@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'mixup_hidden' --alpha 2.0 --manualSeed 5 --noSharp --gpu 0

# Only Latent mixup
python latent-mixing.py --augu --out 'Final_models/oh1@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'only_hidden' --alpha 2.0 --manualSeed 1 --noSharp --gpu 0
python latent-mixing.py --augu --out 'Final_models/oh2@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'only_hidden' --alpha 2.0 --manualSeed 2 --noSharp --gpu 0
python latent-mixing.py --augu --out 'Final_models/oh3@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'only_hidden' --alpha 2.0 --manualSeed 3 --noSharp --gpu 0
python latent-mixing.py --augu --out 'Final_models/oh4@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'only_hidden' --alpha 2.0 --manualSeed 4 --noSharp --gpu 0
python latent-mixing.py --augu --out 'Final_models/oh5@300' --epochs 256 --batch-size 128 --lr 0.0001 --schedule 50 125 --howManyLabelled 300 --mixup 'only_hidden' --alpha 2.0 --manualSeed 5 --noSharp --gpu 0



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