# 比较与tf.image.central_crop的功能差异

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## tf.image.central_crop

```python
tf.image.central_crop(
    image,
    central_fraction
)
```

更多内容详见[tf.image.central_crop](https://www.tensorflow.org/versions/r2.6/api_docs/python/tf/image/central_crop)。

## mindspore.dataset.vision.CenterCrop

```python
class mindspore.dataset.vision.CenterCrop(
    size
)
```

更多内容详见[mindspore.dataset.vision.CenterCrop](https://mindspore.cn/docs/zh-CN/r2.0.0-alpha/api_python/dataset_vision/mindspore.dataset.vision.CenterCrop.html#mindspore.dataset.vision.CenterCrop)。

## 使用方式

TensorFlow：对图像进行中心裁剪，需要输入期望的裁切比例。

MindSpore：对图像进行中心裁剪，需要输入期望的裁切大小。

## 代码示例

```python
# The following implements CenterCrop with MindSpore.
import numpy as np
import mindspore.dataset as ds

image = np.random.random((28, 28, 3))
result = ds.vision.CenterCrop((14, 14))(image)
print(result.shape)
# (14, 14, 3)

# The following implements central_crop with TensorFlow.
import tensorflow as tf

image = tf.random.normal((28, 28, 3))
result = tf.image.central_crop(image, 0.5)
print(result.shape)
# (14, 14, 3)
```