tf.image.psnr
tf.image.psnr(a,b,max_val,name=None)
Defined in?tensorflow/python/ops/image_ops_impl.py.
Returns the Peak Signal-to-Noise Ratio between a and b.
This is intended to be used on signals (or images). Produces a PSNR value for each image in batch.
The last three dimensions of input are expected to be [height, width, depth].
Example:
? ? # Read images from file.
im1= tf.decode_png('path/to/im1.png')
im2= tf.decode_png('path/to/im2.png')# Compute PSNR over tf.uint8 Tensors.
psnr1= tf.image.psnr(im1, im2, max_val=255)
# Compute PSNR over tf.float32 Tensors.
im1= tf.image.convert_image_dtype(im1, tf.float32)
im2= tf.image.convert_image_dtype(im2, tf.float32)
psnr2= tf.image.psnr(im1, im2, max_val=1.0)# psnr1 and psnr2 both have type tf.float32 and are almost equal.
Arguments:
a: First set of images.
b: Second set of images.
max_val: The dynamic range of the images (i.e., the difference between the maximum the and minimum allowed values).
name: Namespace to embed the computation in.
Returns:
The scalar PSNR between a and b. The returned tensor has type?tf.float32?and shape [batch_size, 1].
https://tensorflow.google.cn/api_docs/python/tf/image/psnr?hl=zh-cn
