import pytest import torch from mmcls.core import average_performance, mAP def test_mAP(): target = torch.Tensor([[1, 1, 0, -1], [1, 1, 0, -1], [0, -1, 1, -1], [0, 1, 0, -1]]) pred = torch.Tensor([[0.9, 0.8, 0.3, 0.2], [0.1, 0.2, 0.2, 0.1], [0.7, 0.5, 0.9, 0.3], [0.8, 0.1, 0.1, 0.2]]) # target and pred should both be np.ndarray or torch.Tensor with pytest.raises(TypeError): target_list = target.tolist() _ = mAP(pred, target_list) # target and pred should be in the same shape with pytest.raises(AssertionError): target_shorter = target[:-1] _ = mAP(pred, target_shorter) assert mAP(pred, target) == pytest.approx(68.75, rel=1e-2) target_no_difficult = torch.Tensor([[1, 1, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0], [1, 0, 0, 0]]) assert mAP(pred, target_no_difficult) == pytest.approx(70.83, rel=1e-2) def test_average_performance(): target = torch.Tensor([[1, 1, 0, -1], [1, 1, 0, -1], [0, -1, 1, -1], [0, 1, 0, -1], [0, 1, 0, -1]]) pred = torch.Tensor([[0.9, 0.8, 0.3, 0.2], [0.1, 0.2, 0.2, 0.1], [0.7, 0.5, 0.9, 0.3], [0.8, 0.1, 0.1, 0.2], [0.8, 0.1, 0.1, 0.2]]) # target and pred should both be np.ndarray or torch.Tensor with pytest.raises(TypeError): target_list = target.tolist() _ = average_performance(pred, target_list) # target and pred should be in the same shape with pytest.raises(AssertionError): target_shorter = target[:-1] _ = average_performance(pred, target_shorter) assert average_performance(pred, target) == average_performance( pred, target, thr=0.5) assert average_performance(pred, target, thr=0.5, k=2) \ == average_performance(pred, target, thr=0.5) assert average_performance( pred, target, thr=0.3) == pytest.approx( (31.25, 43.75, 36.46, 33.33, 42.86, 37.50), rel=1e-2) assert average_performance( pred, target, k=2) == pytest.approx( (43.75, 50.00, 46.67, 40.00, 57.14, 47.06), rel=1e-2)