def preprocess_for_eval(image, output_height, output_width):
"""Preprocesses the given image for evaluation.
Args:
image: A `Tensor` representing an image of arbitrary size.
output_height: The height of the image after preprocessing.
output_width: The width of the image after preprocessing.
Returns:
A preprocessed image.
"""
tf.image_summary('image', tf.expand_dims(image, 0))
# Transform the image to floats.
image = tf.to_float(image)
# Resize and crop if needed.
resized_image = tf.image.resize_image_with_crop_or_pad(image,
output_width,
output_height)
tf.image_summary('resized_image', tf.expand_dims(resized_image, 0))
# Subtract off the mean and divide by the variance of the pixels.
return tf.image.per_image_whitening(resized_image)
cifarnet_preprocessing.py 文件源码
python
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