[pull] main from kornia:main

.github/workflows/pr_test_cpu.yml

@@ -25,24 +25,24 @@ jobs:
           - os: 'MacOS-latest'
             pytorch-dtype: 'float64'
 
-    uses: kornia/workflows/.github/workflows/tests.yml@v1.6.0
+    uses: kornia/workflows/.github/workflows/tests.yml@v1.8.1
     with:
       os: ${{ matrix.os }}
       python-version: '["3.8", "3.11"]'
-      pytorch-version: '["1.9.1", "2.2.0"]'
+      pytorch-version: '["1.9.1", "2.2.2"]'
       pytorch-dtype: ${{ matrix.pytorch-dtype }}
 
   coverage:
-    uses: kornia/workflows/.github/workflows/coverage.yml@v1.6.0
+    uses: kornia/workflows/.github/workflows/coverage.yml@v1.8.1
 
   typing:
-    uses: kornia/workflows/.github/workflows/mypy.yml@v1.6.0
+    uses: kornia/workflows/.github/workflows/mypy.yml@v1.8.1
 
   tutorials:
-    uses: kornia/workflows/.github/workflows/tutorials.yml@v1.6.0
+    uses: kornia/workflows/.github/workflows/tutorials.yml@v1.8.1
 
   docs:
-    uses: kornia/workflows/.github/workflows/docs.yml@v1.6.0
+    uses: kornia/workflows/.github/workflows/docs.yml@v1.8.1
 
   collector:
     needs: [coverage, tests-cpu, tutorials, typing, docs]
@@ -63,7 +63,7 @@ jobs:
         os: ['Ubuntu-latest', 'Windows-latest'] #, 'MacOS-latest'] add it when https://github.com/pytorch/pytorch/pull/89262 be merged
         pytorch-dtype: ['float32', 'float64']
 
-    uses: kornia/workflows/.github/workflows/tests.yml@v1.6.0
+    uses: kornia/workflows/.github/workflows/tests.yml@v1.8.1
     with:
       os: ${{ matrix.os }}
       pytorch-version: '["nightly"]'

.github/workflows/scheduled_test_cpu.yml

@@ -18,11 +18,11 @@ jobs:
         # os: ['Ubuntu-latest', 'Windows-latest', 'MacOS-latest']
         pytorch-dtype: ['float32', 'float64']
 
-    uses: kornia/workflows/.github/workflows/tests.yml@v1.6.0
+    uses: kornia/workflows/.github/workflows/tests.yml@v1.8.1
     with:
       os: 'Ubuntu-latest'
       python-version: '["3.8", "3.9", "3.10", "3.11"]'
-      pytorch-version: '["1.9.1", "1.10.2", "1.11.0", "1.12.1", "1.13.1", "2.0.1", "2.1.2", "2.2.0"]'
+      pytorch-version: '["1.9.1", "1.10.2", "1.11.0", "1.12.1", "1.13.1", "2.0.1", "2.1.2", "2.2.2"]'
       pytorch-dtype: ${{ matrix.pytorch-dtype }}
       pytest-extra: '--runslow'
 
@@ -34,11 +34,11 @@ jobs:
       matrix:
         pytorch-dtype: ['float32', 'float64']
 
-    uses: kornia/workflows/.github/workflows/tests.yml@v1.6.0
+    uses: kornia/workflows/.github/workflows/tests.yml@v1.8.1
     with:
       os: 'Windows-latest'
       python-version: '["3.11"]'
-      pytorch-version: '["1.9.1", "2.2.0"]'
+      pytorch-version: '["1.9.1", "2.2.2"]'
       pytorch-dtype: ${{ matrix.pytorch-dtype }}
 
   tests-cpu-mac:
@@ -47,19 +47,19 @@ jobs:
       matrix:
         pytorch-dtype: ['float32', 'float64']
 
-    uses: kornia/workflows/.github/workflows/tests.yml@v1.6.0
+    uses: kornia/workflows/.github/workflows/tests.yml@v1.8.1
     with:
       os: 'MacOS-latest'
       pytorch-dtype: ${{ matrix.pytorch-dtype }}
 
   coverage:
-    uses: kornia/workflows/.github/workflows/coverage.yml@v1.6.0
+    uses: kornia/workflows/.github/workflows/coverage.yml@v1.8.1
 
   typing:
-    uses: kornia/workflows/.github/workflows/mypy.yml@v1.6.0
+    uses: kornia/workflows/.github/workflows/mypy.yml@v1.8.1
 
   tutorials:
-    uses: kornia/workflows/.github/workflows/tutorials.yml@v1.6.0
+    uses: kornia/workflows/.github/workflows/tutorials.yml@v1.8.1
 
   docs:
-    uses: kornia/workflows/.github/workflows/docs.yml@v1.6.0
+    uses: kornia/workflows/.github/workflows/docs.yml@v1.8.1

.pre-commit-config.yaml

@@ -15,12 +15,12 @@ repos:
         exclude: ^$|.devcontainer
 
   - repo: https://github.com/tox-dev/pyproject-fmt
-    rev: "1.7.0"
+    rev: "1.8.0"
     hooks:
       - id: pyproject-fmt
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.3.7
+    rev: v0.4.1
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix]

docs/source/conf.py

@@ -2,6 +2,7 @@
 import inspect
 import os
 import sys
+from datetime import datetime, timezone
 
 # readthedocs generated the whole documentation in an isolated environment
 # by cloning the git repo. Thus, any on-the-fly operation will not effect
@@ -71,7 +72,7 @@
 # General information about the project.
 project = "Kornia"
 author = f"{project} developers"
-copyright = f"2019, {author}"
+copyright = f"{datetime.now(tz=timezone.utc).year}, {author}"
 
 # The version info for the project you're documenting, acts as replacement for
 # |version| and |release|, also used in various other places throughout the
@@ -168,7 +169,6 @@
 html_css_files = ["css/main.css"]
 html_js_files = ["js/custom.js"]
 
-
 # Configure viewcode extension.
 # based on https://github.com/readthedocs/sphinx-autoapi/issues/202
 code_url = "https://github.com/kornia/kornia/blob/main"
@@ -233,14 +233,12 @@ def linkcode_resolve(domain, info):
 #  author, documentclass [howto, manual, or own class]).
 latex_documents = [(master_doc, "kornia.tex", "Kornia", "manual")]
 
-
 # -- Options for manual page output ---------------------------------------
 
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
 man_pages = [(master_doc, "Kornia", "Kornia Documentation", [author], 1)]
 
-
 # -- Options for Texinfo output -------------------------------------------
 
 # Grouping the document tree into Texinfo files. List of tuples
@@ -258,7 +256,6 @@ def linkcode_resolve(domain, info):
     )
 ]
 
-
 # Example configuration for intersphinx: refer to the Python standard library.
 intersphinx_mapping = {
     "python": ("https://docs.python.org/3/", None),

kornia/feature/dedode/dedode.py

@@ -17,6 +17,7 @@
         "L-upright": "https://github.com/Parskatt/DeDoDe/releases/download/dedode_pretrained_models/dedode_detector_L.pth",
         "L-C4": "https://github.com/georg-bn/rotation-steerers/releases/download/release-2/dedode_detector_C4.pth",
         "L-SO2": "https://github.com/georg-bn/rotation-steerers/releases/download/release-2/dedode_detector_SO2.pth",
+        "L-C4-v2": "https://github.com/Parskatt/DeDoDe/releases/download/v2/dedode_detector_L_v2.pth",
     },
     "descriptor": {
         "B-upright": "https://github.com/Parskatt/DeDoDe/releases/download/dedode_pretrained_models/dedode_descriptor_B.pth",
@@ -41,7 +42,7 @@ class DeDoDe(Module):
         amp_dtype: The automatic mixed precision desired.
 
     Example:
-        >>> dedode = DeDoDe.from_pretrained(detector_weights="L-upright", descriptor_weights="B-upright")
+        >>> dedode = DeDoDe.from_pretrained(detector_weights="L-C4-v2", descriptor_weights="B-upright")
         >>> images = torch.randn(1, 3, 256, 256)
         >>> keypoints, scores = dedode.detect(images)
         >>> descriptions = dedode.describe(images, keypoints = keypoints)
@@ -168,22 +169,22 @@ def describe(
     @classmethod
     def from_pretrained(
         cls,
-        detector_weights: str = "L-upright",
+        detector_weights: str = "L-C4-v2",
         descriptor_weights: str = "G-upright",
         amp_dtype: torch.dtype = torch.float16,
     ) -> Module:
         r"""Loads a pretrained model.
 
-        Depth model was trained using depth map supervision and is slightly more precise but biased to detect keypoints
-        only where SfM depth is available. Epipolar model was trained using epipolar geometry supervision and
-        is less precise but detects keypoints everywhere where they are matchable. The difference is especially
-        pronounced on thin structures and on edges of objects.
-
         Args:
-            detector_weights: The weights to load for the detector. One of 'L-upright', 'L-C4', 'L-SO2'.
+            detector_weights: The weights to load for the detector.
+                One of 'L-upright' (original paper, https://arxiv.org/abs/2308.08479),
+                'L-C4', 'L-SO2' (from steerers, better for rotations, https://arxiv.org/abs/2312.02152),
+                'L-C4-v2' (from dedode v2, better at rotations, less clustering, https://arxiv.org/abs/2404.08928)
+                Default is 'L-C4-v2', but perhaps it should be 'L-C4-v2'?
             descriptor_weights: The weights to load for the descriptor.
-            One of 'B-upright', 'B-C4', 'B-SO2', 'G-upright', 'G-C4'.
-            checkpoint: The checkpoint to load. One of 'depth' or 'epipolar'.
+                One of 'B-upright','G-upright' (original paper, https://arxiv.org/abs/2308.08479),
+                'B-C4', 'B-SO2', 'G-C4' (from steerers, better for rotations, https://arxiv.org/abs/2312.02152).
+                Default is 'G-upright'.
             amp_dtype: the dtype to use for the model. One of torch.float16 or torch.float32.
             Default is torch.float16, suitable for CUDA. Use torch.float32 for CPU or MPS
 

tests/feature/test_dedode.py

@@ -42,7 +42,7 @@ def test_smoke_amp_fp16(self, dtype, device, descriptor_model, detector_model):
         assert descriptions.shape == (shape[0], n, 256)
 
     @pytest.mark.slow
-    @pytest.mark.parametrize("detector_weights", ["L-upright", "L-C4", "L-SO2"])
+    @pytest.mark.parametrize("detector_weights", ["L-upright", "L-C4", "L-SO2", "L-C4-v2"])
     @pytest.mark.parametrize("descriptor_weights", ["B-upright", "B-C4", "B-SO2", "G-upright", "G-C4"])
     def test_pretrained(self, dtype, device, descriptor_weights, detector_weights):
         if "G" in descriptor_weights and device.type != "cuda" and dtype == torch.float16: