Function Differences with tf.image.crop_to_bounding_box
tf.image.crop_to_bounding_box
tf.image.crop_to_bounding_box(
image,
offset_height,
offset_width,
target_height,
target_width
)
For more information, see tf.image.crop_to_bounding_box.
mindspore.dataset.vision.Crop
class mindspore.dataset.vision.Crop(
coordinates,
size
)
For more information, see mindspore.dataset.vision.Crop.
Differences
TensorFlow: Crop at the specified position of the image. Input parameters are the height and width coordinates of the position and the height and width of the cropped image.
MindSpore: Crop at the specified position of the image. Input parameters are the coordinates of the position and the size of the crop image.
Code Example
# The following implements Crop with MindSpore.
import numpy as np
import mindspore.dataset as ds
image = np.random.random((28, 28, 3))
result = ds.vision.Crop((0, 0), (14, 14))(image)
print(result.shape)
# (14, 14, 3)
# The following implements crop_to_bounding_box with TensorFlow.
import tensorflow as tf
image = tf.random.normal((28, 28, 3))
result = tf.image.crop_to_bounding_box(image, 0, 0, 14, 14)
print(result.shape)
# (14, 14, 3)