def __init__(self):
classifier = Classifier()
classifier.Build()
# Trainer, Evaluator
print("Reading Training set...")
# self.setdata('something')
self.trainer = Trainer(classifier)
self.trainEvaluator = Evaluator("train",
dataSettings.PATH_TO_TRAIN_SET_CATELOG,
classifier)
print("\t Done.\n")
print("Reading Validation set...")
self.validationEvaluator = Evaluator(
"validation", dataSettings.PATH_TO_VAL_SET_CATELOG, classifier)
print("\t Done.\n")
print("Reading Test set...")
self.testEvaluator = Evaluator("test",
dataSettings.PATH_TO_TEST_SET_CATELOG,
classifier)
print("\t Done.\n")
# Summary
summaryOp = tf.summary.merge_all()
self.trainer.SetMergedSummaryOp(summaryOp)
self.trainEvaluator.SetMergedSummaryOp(summaryOp)
self.validationEvaluator.SetMergedSummaryOp(summaryOp)
self.bestThreshold = None
self.testEvaluator.SetMergedSummaryOp(summaryOp)
# Time
self._startTrainEpochTime = time.time()
self._trainCountInOneEpoch = 0
# Saver
self.modelSaver = tf.train.Saver(
max_to_keep=trainSettings.MAX_TRAINING_SAVE_MODEL)
# Session
self.session = tf.Session()
init = tf.global_variables_initializer()
self.session.run(init)
self.trainer.SetGraph(self.session.graph)
self.validationEvaluator.SetGraph(self.session.graph)
"{0:.2f}".format(duration_) + "(s)\n")
else:
print("\t loss:", floatPrecision.format(loss_),
" frame accuracy:", floatPrecision.format(frameAccuracy_),
" given frame threshold:",
threshold_, " video accuracy:",
floatPrecision.format(videoAccuracy_), " duration:",
"{0:.2f}".format(duration_) + "(s)\n")
if __name__ == '__main__':
numberOfArguments = len(sys.argv)
if (numberOfArguments == 2) or (numberOfArguments == 3):
PATH_TO_DATA_SET_CATELOG = sys.argv[1]
classifier = Classifier()
classifier.Build()
evaluator = Evaluator("evaluate", PATH_TO_DATA_SET_CATELOG, classifier)
with tf.Session() as session:
init = tf.global_variables_initializer()
session.run(init)
print("Load Model from: ", evalSettings.PATH_TO_MODEL_CHECKPOINTS)
modelLoader = tf.train.Saver()
modelLoader.restore(session,
evalSettings.PATH_TO_MODEL_CHECKPOINTS)
startEvaluateTime = time.time()
if numberOfArguments == 2:
print("Start evaluate: ", PATH_TO_DATA_SET_CATELOG,
", and find the best threshold...")