def main():
args = parseArgs()
function = args.function
input_file = args.input
output_file = args.output
true_file = args.trueout
result_file = args.result
method = args.method
if function == ("Pred" or "Predict"):
if input_file == "":
print("Error - Read inputs")
elif output_file == "":
print("Error - Write output")
else:
prediction(input_file, output_file, method)
elif function == ("Eval" or "Evaluate"):
if input_file == "" or true_file == "":
print("Error - Read inputs")
elif output_file == "":
print("Error - Write output")
else:
evaluate(input_file, output_file, true_file, result_file)
else:
print("Please choose 'Pred' function or 'Eval' function")
else:
saver.restore(sess, config.weightsFile(epoch))
evalRes = runEvaluation(sess,
model,
data["main"],
epoch,
evalTest=True,
raw=config.raw_image)
extraEvalRes = runEvaluation(sess,
model,
data["extra"],
epoch,
evalTrain=not config.extraVal,
evalTest=True,
raw=config.raw_image)
print("took {:.2f} seconds".format(time.time() - start))
printDatasetResults(None, evalRes, extraEvalRes)
print("Writing predictions...")
writePreds(preprocessor, evalRes, extraEvalRes)
print(bcolored("Done!", "white"))
if __name__ == '__main__':
parseArgs()
loadDatasetConfig[config.dataset]()
main()