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)