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AARunBatch.py
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AARunBatch.py
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######################################################################################
# Floris Fok
# Final bacherlor project
#
# 2019 febuari
# Transfer learning from medical and non medical data sets to medical target data
#
# ENJOY
######################################################################################
# Helper file for running experiments
# TIP: USE batch scripts
######################################################################################
import sys
#checks correct usage
if len(sys.argv) != 3:
print("\nUSAGE: python run_batch.py iiii(i) 'run_style'")
quit()
from AARunTarget import run_target
from AARunSource import run_source
#difine number string
arg = sys.argv[1]
#translate numbers to settings
model = ["imagenet","Chest","CatDog","KaggleDR","Nat",'None']
data = ['two','three','two_combined']#data[y]
style = ['FT', 'SVM']
#define argument numbers, just short to write
data_num = int(arg[0])
model_num = int(arg[1])
style_num = int(arg[2])
random_num = int(arg[3])
#if a fifth argument is given, define it
try:
sub_data_num = int(arg[4])
except:
if data_num == 0:
print("You need a fifth argument to run ISIC")
run_style = sys.argv[2]
# select paramset
if data_num ==0:
params = {"Data":'ISIC',
"data_name":data[sub_data_num],
"style":style[style_num],
"model":model[model_num],
"file_path":r"C:\ISIC",
"pickle_path":r"C:\pickles\save_melanoom_color_",
"model_path":{'Nat':r"C:\models\Epochs_50_Nat.json","KaggleDR":r"C:\models\Epochs_50_kaggleDR.json","Chest":r"C:\models\Epochs_50_Chest.json", "CatDog":r"C:\models\Epochs_40_CatDog.json" },
"RandomSeed":random_num,
"doc_path":r"C:\Users\Flori\Documents\GitHub\t",
'img_size_x':224,
'img_size_y':224,
'norm':False,
'color':True,
'pretrain':None,
"equal_data":False,
"shuffle":True,
"epochs":50,
"val_size":200,
"test_size":400,
"Batch_size":32,
"stop":'yes'
}
elif data_num == 1:
params = {"Data":'Nat',
"style":'none',
"model":'None',
'file_path':r"C:\natural_images",
'pickle_path':r"C:\pickles\Nat",
'model_path':r"C:\models\Epochs_50_Nat.json",
"RandomSeed":random_num,
"doc_path":r"C:\Users\Flori\Documents\GitHub\t",
'img_size_x':224,
'img_size_y':224,
'norm':False,
'color':True,
'pretrain':None,
"equal_data":False,
"shuffle":True,
"epochs":50,
"val_size":500,
"test_size":1000,
"Batch_size":32,
"stop":'yes'
}
elif data_num == 2:
params = {"Data":'Blood',
"data_name":None,
"style":style[style_num],
"model":model[model_num],
"file_path":r"C:\blood-cells",
"pickle_path":r"C:\pickles\Blood",
"model_path":{"Nat":r"C:\models\Epochs_50_Nat.json","KaggleDR":r"C:\models\Epochs_50_kaggleDR.json","Chest":r"C:\models\Epochs_50_Chest.json", "CatDog":r"C:\models\Epochs_40_CatDog.json" },
"RandomSeed":random_num,
"doc_path":r"C:\Users\Flori\Documents\GitHub\t",
'img_size_x':224,
'img_size_y':224,
'norm':False,
'color':True,
'pretrain':None,
"equal_data":False,
"shuffle":True,
"epochs":50,
"val_size":1500,
"test_size":2000,
"Batch_size":32,
"stop":'yes'
}
elif data_num == 3:
params = {"Data":'Chest',
"data_name":None,
"style":style[style_num],
"model":model[model_num],
"file_path":r"C:\chest_xray",
"pickle_path":r"C:\pickles\Chest_int",
"model_path":{"Nat":r"C:\models\Epochs_50_Nat.json","KaggleDR":r"C:\models\Epochs_50_kaggleDR.json","Chest":r"C:\models\Epochs_50_Chest.json", "CatDog":r"C:\models\Epochs_40_CatDog.json" },
"RandomSeed":random_num,
"doc_path":r"C:\Users\Flori\Documents\GitHub\t",
'img_size_x':224,
'img_size_y':224,
'norm':False,
'color':True,
'pretrain':None,
"equal_data":False,
"shuffle":True,
"epochs":50 ,
"val_size":600,
"test_size":900,
"Batch_size":32,
"stop":'yes'
}
elif data_num == 4:
params = {"Data":'KaggleDR',
"data_name":None,
"style":style[style_num],
"model":model[model_num],
"file_path":r"C:\KaggleDR",
"pickle_path":r"C:\pickles\KaggleDR",
"model_path":{"Nat":r"C:\models\Epochs_50_Nat.json","KaggleDR":r"C:\models\Epochs_50_kaggleDR.json","Chest":r"C:\models\Epochs_50_Chest.json", "CatDog":r"C:\models\Epochs_40_CatDog.json" },
"RandomSeed":random_num,
"doc_path":r"C:\Users\Flori\Documents\GitHub\t",
'img_size_x':224,
'img_size_y':224,
'norm':False,
'color':True,
'pretrain':None,
"equal_data":False,
"shuffle":True,
"epochs":50 ,
"val_size":5000,
"test_size":5000,
"Batch_size":32,
"stop":'yes'
}
elif data_num == 5:
params = {"Data":'CatDog',
"data_name":None,
'file_path':r"C:\PetImages",
"style":style[style_num],
"model":model[model_num],
'pickle_path':r"C:\pickles\CatDog",
'model_path':r"C:\models\Epochs_",
'doc_path':r"C:\Users\Flori\Documents\GitHub\t",
"RandomSeed":random_num,
'img_size_x':224,
'img_size_y':224,
'norm':True,
'color':True,
'pretrain':None,
"equal_data":False,
"shuffle": True,
"epochs": 50 ,
"val_size":3000,
"test_size":5000,
"Batch_size": 32,
"stop":'yes'
}
#run program
if run_style == 'source':
run(params)
elif run_style == 'target':
run_target(params)
else:
print('Run Style Unknown')