def test_dice_coef_max(self):
"""Test the upper-bound of the dice coefficient."""
y_true = np.ones((2, 1, 200, 200))
y_pred = np.ones((2, 1, 200, 200))
var_y_true = K.variable(y_true)
var_y_pred = K.variable(y_pred)
out_loss = gm_model.dice_coef(var_y_true, var_y_pred)
res = K.eval(out_loss)
assert res == 1.0
def test_dice_coef_max(self):
"""Test the upper-bound of the dice coefficient."""
y_true = np.ones((2, 1, 200, 200))
y_pred = np.ones((2, 1, 200, 200))
var_y_true = K.variable(y_true)
var_y_pred = K.variable(y_pred)
out_loss = gm_model.dice_coef(var_y_true, var_y_pred)
res = K.eval(out_loss)
assert res == 1.0
def test_dice_coef_min(self):
"""Test the lower-bound of the dice coefficient."""
y_true = np.ones((2, 1, 200, 200))
y_pred = np.zeros((2, 1, 200, 200))
var_y_true = K.variable(y_true)
var_y_pred = K.variable(y_pred)
out_loss = gm_model.dice_coef(var_y_true, var_y_pred)
res = K.eval(out_loss)
# Smoothing term makes it never reach zero
assert res == pytest.approx(0.0, 0.001)
def test_dice_coef_min(self):
"""Test the lower-bound of the dice coefficient."""
y_true = np.ones((2, 1, 200, 200))
y_pred = np.zeros((2, 1, 200, 200))
var_y_true = K.variable(y_true)
var_y_pred = K.variable(y_pred)
out_loss = gm_model.dice_coef(var_y_true, var_y_pred)
res = K.eval(out_loss)
# Smoothing term makes it never reach zero
assert res == pytest.approx(0.0, abs=0.001)