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 += [image] * 10 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)