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14f6839 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 | import tensorflow as tf
from data.image_classification import ImageClassificationDirectoryDataset
def _write_classification_data(tmp_path):
image = tf.zeros((8, 10, 3), dtype=tf.uint8)
encoded_image = tf.io.encode_jpeg(image)
for split in ["train", "val", "test"]:
for class_name in ["cat", "dog"]:
class_dir = tmp_path / split / class_name
class_dir.mkdir(parents=True)
tf.io.write_file(str(class_dir / f"{class_name}_1.jpg"), encoded_image)
tf.io.write_file(str(class_dir / f"{class_name}_2.jpg"), encoded_image)
return tmp_path / "train", tmp_path / "val", tmp_path / "test"
def test_training_ds_builds_binary_classification_images_and_labels(tmp_path):
"""验证目录分类训练数据集会输出调整尺寸后的图片和二分类标签。"""
train_dir, validation_dir, test_dir = _write_classification_data(tmp_path)
dataset = ImageClassificationDirectoryDataset(
train_path=train_dir,
validation_path=validation_dir,
test_path=test_dir,
image_size=(6, 6)
)
images, labels = next(iter(dataset.training_ds(batch_size=2)))
assert images.shape == (2, 6, 6, 3)
assert labels.shape == (2, 1)
assert images.dtype == tf.float32
assert labels.dtype == tf.float32
def test_class_names_returns_directory_class_names(tmp_path):
"""验证目录分类数据集会按目录名返回类别名称。"""
train_dir, validation_dir, test_dir = _write_classification_data(tmp_path)
dataset = ImageClassificationDirectoryDataset(
train_path=train_dir,
validation_path=validation_dir,
test_path=test_dir,
image_size=(6, 6)
)
assert dataset.class_names() == ["cat", "dog"]
def test_validation_and_test_ds_read_their_own_directories(tmp_path):
"""验证验证集和测试集会分别从对应目录读取图片。"""
train_dir, validation_dir, test_dir = _write_classification_data(tmp_path)
dataset = ImageClassificationDirectoryDataset(
train_path=train_dir,
validation_path=validation_dir,
test_path=test_dir,
image_size=(6, 6)
)
validation_images, validation_labels = next(iter(dataset.validation_ds(batch_size=2)))
test_images, test_labels = next(iter(dataset.test_ds(batch_size=2)))
assert validation_images.shape == (2, 6, 6, 3)
assert validation_labels.shape == (2, 1)
assert test_images.shape == (2, 6, 6, 3)
assert test_labels.shape == (2, 1)
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