[英]How to prepare PIL Image.Image for tf.image.decode_image
For a file read with:对于文件读取:
import PIL
import tensorflow as tf
from keras_preprocessing.image import array_to_img
path_image = "path/cat_960_720.jpg"
read_image = PIL.Image.open(path_image)
# read_image.show()
image_decode = tf.image.decode_image(read_image)
print("This is the size of the Sample image:", image_decode.shape, "\n")
print("This is the array for Sample image:", image_decode)
resize_image = tf.image.resize(image_decode, (32, 32))
print("This is the Shape of resized image", resize_image.shape)
print("This is the array for resize image:", resize_image)
to_img = array_to_img(resize_image)
to_img.show()
I keep getting error for this line tf.image.decode_image(read_image)
:我不断收到此行
tf.image.decode_image(read_image)
的错误:
ValueError: Attempt to convert a value (<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=960x586 at 0x11AA49F40>) with an unsupported type (<class 'PIL.JpegImagePlugin.JpegImageFile'>) to a Tensor.
ValueError:尝试将具有不受支持的类型 (<class 'PIL.JpegImagePlugin.JpegImageFile'>) 的值 (<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=960x586 at 0x11AA49F40>) 转换为 Tensor。
How can I pass imae read with PIL to tensorflow so that I could decode and resize, so that I could resize this big picture to 32x32x3
?如何将使用 PIL 读取的 imae 传递给 tensorflow 以便我可以解码和调整大小,以便我可以将这张大图片调整为
32x32x3
?
A few options, here is 1 if you have to use PIL
:几个选项,如果您必须使用
PIL
,这里是 1:
import PIL
import tensorflow as tf
from keras_preprocessing.image import array_to_img
import numpy as np
path_image = "/content/cat.jpg"
read_image = np.asarray(PIL.Image.open(path_image))
resize_image = tf.image.resize(read_image, (32, 32))
print("This is the Shape of resized image", resize_image.shape)
print("This is the array for resize image:", resize_image)
to_img = array_to_img(resize_image)
Here is an option with TF
only:这是一个只有
TF
的选项:
import tensorflow as tf
from keras_preprocessing.image import array_to_img
path_image = "/content/cat.jpg"
read_image = tf.io.read_file(path_image)
read_image = tf.image.decode_image(read_image)
resize_image = tf.image.resize(read_image, (32, 32))
print("This is the Shape of resized image", resize_image.shape)
print("This is the array for resize image:", resize_image)
to_img = array_to_img(resize_image)
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