def main():
print("Welcome to Organogenesis")
print("------------------")
#Keep a list of available structures for training/predicting
OARs = [
"Body", "Spinal Cord", "Oral Cavity", "Left Parotid", "Right Parotid"
] #Later will add an "all" option
#Need to get user input. Make a string to easily ask for a number corresponding to an OAR.
ChooseOAR_string = "Please enter the number for the organ you wish to contour / train a model for \n>>"
for i in range(len(OARs)):
ChooseOAR_string += str(
i + 1) + ": " + OARs[i] + "\n" #create list of options
while True: #wait for user input
try:
chosenOAR = int(input(ChooseOAR_string)) - 1
if chosenOAR < len(OARs):
break
except KeyboardInterrupt:
quit()
except:
pass
#Now determine if the goal is to train or to find contours, etc
chooseTask_string = "Please enter the number for the desired task\n"
chooseTask_string += "1. Train a UNet model for predicting " + str(
OARs[chosenOAR])
chooseTask_string += "\n2. Predict " + str(
OARs[chosenOAR]) + " contours using an existing model"
chooseTask_string += "\n3. Determine threshold accuracies for predictions of the " + str(
OARs[chosenOAR])
chooseTask_string += "\n4. Determine the evaulation data (F score and 95th percentile Haussdorf distance) for the validation set of the " + str(
OARs[chosenOAR])
chooseTask_string += "\n5. Plot predicted masks for the " + str(
OARs[chosenOAR])
chooseTask_string += "\n6. Export model to ONNX" #Not worrying about this anymore for now
chooseTask_string += "\n7. predict using ONNX model \n>>" #Not worrying about this anymore for now
while True: #get user input
try:
task = int(input(chooseTask_string))
if (task in range(0, 8)):
break
except KeyboardInterrupt:
quit()
except:
pass
if (task == 1):
Train.Train(OARs[chosenOAR],
7,
1e-3,
path=None,
processData=False,
loadModel=False,
preSorted=True)
Test.BestThreshold(OARs[chosenOAR], 400)
Test.TestPlot(OARs[chosenOAR], path=None, threshold=0.1)
elif task == 2:
contoursList, existingContoursList = Predict.GetContours(
OARs[chosenOAR],
"P85",
path=None,
threshold=0.72,
withReal=True,
tryLoad=False,
plot=False)
#print(contoursList)
#print(len(contoursList))
elif task == 3:
Test.BestThreshold(OARs[chosenOAR],
path=None,
testSize=500,
onlyMasks=False,
onlyBackground=False)
elif task == 4:
F_Score, recall, precision, accuracy, haussdorffDistance = Test.GetEvalData(
OARs[chosenOAR], path=None, threshold=0.7)
print([F_Score, recall, precision, accuracy, haussdorffDistance])
elif task == 5:
array, y = Test.GetMasks(OARs[chosenOAR],
"HN1046",
path="/media/calebsample/Data/temp",
threshold=0.1)
import numpy as np
print(np.amax(y))
print(np.amax(array))
Test.TestPlot(OARs[chosenOAR],
path="/media/calebsample/Data/temp",
threshold=0.1)
"\nPlease specify the number of epochs\n >")
numEpochs = int(numEpochs)
break
except KeyboardInterrupt:
quit()
except:
pass
processData = args.processData
loadModel = args.loadModel
dataPath = args.dataPath #If dataPath is None, then the program uses the data in the patient_files folder. If it is a path to a directory, data will be processed in this directory.
preSorted = args.preSorted
Train.Train(organ, numEpochs, lr, dataPath, processData, loadModel,
preSorted)
bestThreshold = Test.BestThreshold(organ, dataPath, 400)
Test.TestPlot(organ, dataPath, threshold=bestThreshold)
elif args.function == "GetContours":
patient = args.predictionPatientName
if (patient == None):
while True:
try:
patient = input(
"\nPlease specify the name of the patient folder that you are trying to get contours for\n >"
)
if patient != "":
break
except KeyboardInterrupt:
quit()
