def main():
print("Welcome to Organogenesis")
print("------------------")
#Keep a list of organs which can be contoured
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"
while True:
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
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 F-score for 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"
chooseTask_string += "\n7. predict using ONNX model \n>>"
while True:
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], 12, 1e-3, processData=False, loadModel=False)
Test.Best_Threshold(OARs[chosenOAR],400)
Test.TestPlot(OARs[chosenOAR], threshold=0.1)
elif task == 2:
Predict.GetContours(OARs[chosenOAR],"P86", threshold = 0.09, withReal=True, tryLoad=False)
elif task == 3:
Test.Best_Threshold(OARs[chosenOAR], testSize=500, onlyMasks=False,onlyBackground=False)
elif task == 4:
F_Score, recall, precision, accuracy = Test.FScore(OARs[chosenOAR], threshold=0.2)
print([F_Score, recall, precision, accuracy])
elif task == 5:
Test.TestPlot(OARs[chosenOAR], threshold=0.2)
elif task == 6:
PostProcessing.Export_To_ONNX(OARs[chosenOAR])
elif task == 7:
PostProcessing.Infer_From_ONNX(OARs[chosenOAR], 'P7')
