[2019.3.1 16:44] uploading mask file

• python==3.6
• torch==0.4.1
• torchvision==0.2.1

https://www.kaggle.com/c/humpback-whale-identification/discussion/82366

trainset -> ./input/train
testset -> ./input/test

cd input
unzip mask.zip
download model_50A_slim_ensemble.csv(https://drive.google.com/file/d/1hfOu3_JR0vWJkNlRhKwhqJDaF3ID2vRs/view?usp=sharing) into ./input

download playground data, then put them into input/train
https://www.kaggle.com/c/whale-categorization-playground/data

line 301 in train.py
step 1.
       freeze = False
       model_name = 'senet154'
       min_num_class = 10
       checkPoint_start = 0
       lr = 3e-4
       #until train map5 >= 0.98

step 2.
       freeze = True
       model_name = 'senet154'
       min_num_class = 0
       checkPoint_start = best checkPoint of step 1
       lr = 3e-4

step 3.
       freeze = True
       model_name = 'senet154'
       min_num_class = 0
       checkPoint_start = best checkPoint of step 2
       lr = 3e-5

line 99 in test.py
       checkPoint_start = best checkPoint of step 3