def main():
output_dir = os.path.abspath("workspace")
dataset_manager = DatasetManager()
model = MaskRCNN(output_dir)
ratio = 0.2
datasetA, datasetB = dataset_manager.split_dataset('ade20k_train',
ratio=ratio)
weights = model.train(datasetA, weights=None, epochs=10)
while True:
small_datasetB = dataset_manager.random_subset(datasetB, 100)
predictions = model.predict(small_datasetB, weights)
annotations = annotator.filter(predictions)
new_dataset = dataset_manager.create_dataset_with_new_annotations(
datasetB, annotations)
weights = model.train(new_dataset, weights, epochs=1)
