Function to calculate peak-signal-to-noise ratio.

peak_signal_to_noise_ratio(y_true, y_pred)

Arguments

y_true	True labels (Tensor)
y_pred	Predictions (Tensor of the same shape as `y_true`)

Value

PSNR value

Author

Tustison NJ

Examples


library( ANTsRNet )
library( keras )

model <- createUnetModel2D( c( 64, 64, 1 ) )
#> Error in py_discover_config(required_module, use_environment): Python specified in RETICULATE_PYTHON (/Users/ntustison/anaconda3/envs/antsx/bin/python3) does not exist

metric_peak_signal_to_noise_ratio <-
  custom_metric( "peak_signal_to_noise_ratio",
    peak_signal_to_noise_ratio )
#> Error in value[[3L]](cond): The R function's signature must not contains esoteric Python-incompatible constructs. Detailed traceback: 
#> Python specified in RETICULATE_PYTHON (/Users/ntustison/anaconda3/envs/antsx/bin/python3) does not exist

model %>% compile( loss = loss_categorical_crossentropy,
  optimizer = optimizer_adam( lr = 0.0001 ),
  metrics = c( metric_peak_signal_to_noise_ratio ) )
#> Error in compile(., loss = loss_categorical_crossentropy, optimizer = optimizer_adam(lr = 1e-04),     metrics = c(metric_peak_signal_to_noise_ratio)): object 'model' not found