def get_data():
images, labels = load_data()
Xtest, Ytest = get_test_data()
Xtrain, Ytrain = get_train_data()
data = Data(Xtrain, Ytrain)
data = ElasticAugment(num_maps=6, std=7, border_mode='reflect_101', keep_old_data=True)(data)
Xtrain, Ytrain = data.get_data()
print(len(Xtrain), len(Ytrain))
num_pos = calc_num_pos(Ytrain)
Xtrain, Ytrain, Xtest, Ytest = normalize_data(Xtrain, Ytrain, Xtest, Ytest)
return Xtrain, Ytrain, num_pos, Xtest, Ytest
Xtrain, Ytrain, _ = ImageCutter.image_and_mask_cutter(Xtrain, Ytrain, 256, 256, 128, 128, 0.05)
Xtest, Ytest, _ = ImageCutter.image_and_mask_cutter(Xtest, Ytest, 256, 256, 128, 128, 0.05)
Xtrain = np.asarray(Xtrain).astype(np.float32) / 255
Xtrain = [i for i in Xtrain]
Ytrain = np.asarray(Ytrain).astype(np.uint8) // 10
Ytrain = [i for i in Ytrain]
Xtest = np.asarray(Xtest).astype(np.float32) / 255
Xtest = [i for i in Xtest]
Ytest = np.asarray(Ytest).astype(np.uint8) // 10
Ytest = [i for i in Ytest]
data = Data(Xtrain, Ytrain)
data = AffineAugment(num_matrices=1, noise_type='gaussian', keep_old_data=True)(data)
data = ElasticAugment(num_maps=1, border_mode='reflect_101', keep_old_data=True)(data)
aug_images, aug_labels = data.get_data()
print(len(aug_images))
aug_labels = [cv2.cvtColor(item, cv2.COLOR_BGR2GRAY) for item in aug_labels]
Ytest = [cv2.cvtColor(item, cv2.COLOR_BGR2GRAY) for item in Ytest]
num_pos = calc_num_pos(aug_labels)
assert(sum([i > 0 for i in num_pos]) == len(num_pos))
# Start test
mf.set_main_gpu(1)
trainer = SegmentatorTrainer('experiment.json', 'resnet50')
trainer.set_test_data(Xtest, Ytest)