Fix the dependencies of LPIPS metric

requirements/image.txt

@@ -4,4 +4,3 @@
 scipy >1.0.0, <1.11.0
 torchvision >=0.8, <0.17.0
 torch-fidelity <=0.4.0  # bumping to allow install version from master, now used in testing
-lpips <=0.1.4

src/torchmetrics/image/lpip.py

@@ -47,8 +47,8 @@ class LearnedPerceptualImagePatchSimilarity(Metric):
     Both input image patches are expected to have shape ``(N, 3, H, W)``. The minimum size of `H, W` depends on the
     chosen backbone (see `net_type` arg).
 
-    .. note:: using this metrics requires you to have ``lpips`` package installed. Either install
-        as ``pip install torchmetrics[image]`` or ``pip install lpips``
+    .. note:: using this metrics requires you to have ``torchvision`` package installed. Either install as
+        ``pip install torchmetrics[image]`` or ``pip install torchvision``.
 
     .. note:: this metric is not scriptable when using ``torch<1.8``. Please update your pytorch installation
         if this is a issue.
@@ -71,7 +71,7 @@ class LearnedPerceptualImagePatchSimilarity(Metric):
 
     Raises:
         ModuleNotFoundError:
-            If ``lpips`` package is not installed
+            If ``torchvision`` package is not installed
         ValueError:
             If ``net_type`` is not one of ``"vgg"``, ``"alex"`` or ``"squeeze"``
         ValueError:

src/torchmetrics/utilities/imports.py

@@ -36,7 +36,6 @@
 _SCIPY_AVAILABLE: bool = package_available("scipy")
 _SCIPY_GREATER_EQUAL_1_8 = compare_version("scipy", operator.ge, "1.8.0")
 _TORCH_FIDELITY_AVAILABLE: bool = package_available("torch_fidelity")
-_LPIPS_AVAILABLE: bool = package_available("lpips")
 _PYCOCOTOOLS_AVAILABLE: bool = package_available("pycocotools")
 _TORCHVISION_AVAILABLE: bool = package_available("torchvision")
 _TORCHVISION_GREATER_EQUAL_0_8: Optional[bool] = compare_version("torchvision", operator.ge, "0.8.0")

tests/unittests/image/test_lpips.py

@@ -19,7 +19,7 @@
 from lpips import LPIPS as LPIPS_reference  # noqa: N811
 from torch import Tensor
 from torchmetrics.image.lpip import LearnedPerceptualImagePatchSimilarity
-from torchmetrics.utilities.imports import _LPIPS_AVAILABLE
+from torchmetrics.utilities.imports import _TORCHVISION_AVAILABLE
 
 from unittests.helpers import seed_all
 from unittests.helpers.testers import MetricTester
@@ -47,7 +47,7 @@ def _compare_fn(img1: Tensor, img2: Tensor, net_type: str, normalize: bool = Fal
     return res.sum()
 
 
-@pytest.mark.skipif(not _LPIPS_AVAILABLE, reason="test requires that lpips is installed")
+@pytest.mark.skipif(not _TORCHVISION_AVAILABLE, reason="test requires that lpips is installed")
 class TestLPIPS(MetricTester):
     """Test class for `LearnedPerceptualImagePatchSimilarity` metric."""
 
@@ -94,7 +94,7 @@ def test_normalize_arg(normalize):
     assert res == res2
 
 
-@pytest.mark.skipif(not _LPIPS_AVAILABLE, reason="test requires that lpips is installed")
+@pytest.mark.skipif(not _TORCHVISION_AVAILABLE, reason="test requires that torchvision is installed")
 def test_error_on_wrong_init():
     """Test class raises the expected errors."""
     with pytest.raises(ValueError, match="Argument `net_type` must be one .*"):
@@ -104,7 +104,7 @@ def test_error_on_wrong_init():
         LearnedPerceptualImagePatchSimilarity(net_type="squeeze", reduction=None)
 
 
-@pytest.mark.skipif(not _LPIPS_AVAILABLE, reason="test requires that lpips is installed")
+@pytest.mark.skipif(not _TORCHVISION_AVAILABLE, reason="test requires that lpips is installed")
 @pytest.mark.parametrize(
     ("inp1", "inp2"),
     [