y_true is one-hot, convert to sparse

aimodel/src/lib/ai/components/MetricMeanIoU.py

@@ -14,6 +14,7 @@ def one_hot_mean_iou(y_true, y_pred, classes=2):
 	"""
 	
 	y_pred = tf.math.argmax(y_pred, axis=-1)
+	y_true = tf.math.argmax(y_true, axis=-1)
 	y_true = tf.cast(y_true, dtype=tf.float32)
 	y_pred = tf.cast(y_pred, dtype=tf.float32)
 	

aimodel/src/lib/ai/components/MetricSensitivity.py

@@ -4,6 +4,7 @@ import tensorflow as tf
 
 def sensitivity(y_true, y_pred):
 	y_pred = tf.math.argmax(y_pred, axis=-1)
+	y_true = tf.math.argmax(y_true, axis=-1)
 	y_true = tf.cast(y_true, dtype=tf.float32)
 	y_pred = tf.cast(y_pred, dtype=tf.float32)
 	

aimodel/src/lib/ai/components/MetricSpecificity.py

@@ -14,6 +14,7 @@ def specificity(y_pred, y_true):
 	Specificity score
 	"""
 	y_pred = tf.math.argmax(y_pred, axis=-1)
+	y_true = tf.math.argmax(y_true, axis=-1)
 	y_true = tf.cast(y_true, dtype=tf.float32)
 	y_pred = tf.cast(y_pred, dtype=tf.float32)