Function Differences with tf.image.convert_image_dtype
tf.image.convert_image_dtype
tf.image.convert_image_dtype(
image,
dtype,
saturate=False,
name=None
)
For more information, see tf.image.convert_image_dtype.
mindspore.dataset.transforms.TypeCast
class mindspore.dataset.transforms.TypeCast(
output_type
)
For more information, see mindspore.dataset.transforms.TypeCast.
Differences
TensorFlow: Convert the data type of the Tensor image. It supports setting whether to perform clipping before casting to avoid overflow.
MindSpore: Convert the data type of the numpy.ndarray image.
Code Example
# The following implements TypeCast with MindSpore.
import numpy as np
import mindspore.dataset as ds
image = np.random.random((28, 28, 3))
result = ds.transforms.TypeCast(np.uint8)(image)
print(result.dtype)
# uint8
# The following implements convert_image_dtype with TensorFlow.
import tensorflow as tf
image = tf.random.normal((28, 28, 3), dtype=tf.float32)
result = tf.image.convert_image_dtype(image, tf.uint8)
print(result.dtype)
# uint8