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Returns the Peak Signal-to-Noise Ratio between a and b.
tf.image.psnr( a, b, max_val, name=None )
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].
# 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 | |
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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 | |
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The scalar PSNR between a and b. The returned tensor has type tf.float32 and shape [batch_size, 1]. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/image/psnr