Auto sort imports (#6)

* Add isort, merge check runs into one

* Run isort

* Ignor build in flake8 config

* Remove jupyter as dev dependency

.flake8

@@ -1,3 +1,4 @@
 [flake8]
 max-line-length = 88
 extend-ignore = E203
+exclude = .git,__pycache__,build,.venv/

.github/workflows/code-quality.yml

@@ -8,24 +8,17 @@ on:
   pull_request:
     types: [ assigned, opened, synchronize, reopened ]
 jobs:
-  formatting-check:
+  check:
-    name: Formatting Check
+    name: Format and Lint Checks
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v3
-      - uses: psf/black@stable
-        with:
-          jupyter: true
-  linting-check:
-    name: Linting Check
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v3
       - uses: actions/setup-python@v4
         with:
-          python-version: "3.10"
+          python-version: '3.10'
           cache: 'pip'
       - run: python -m pip install --upgrade pip
-      - run: python -m pip install .
+      - run: python -m pip install .[dev]
-      - run: python -m pip install --upgrade flake8
+      - run: python -m flake8 .
-      - run: python -m flake8 . --exclude build/
+      - run: python -m isort . --check-only --diff
+      - run: python -m black . --check --diff

format.sh

@@ -0,0 +1,3 @@
+python -m flake8 .
+python -m isort .
+python -m black .

gluefactory/__init__.py

@@ -1,4 +1,5 @@
 import logging
+
 from .utils.experiments import load_experiment  # noqa: F401
 
 formatter = logging.Formatter(

gluefactory/datasets/__init__.py

@@ -1,6 +1,7 @@
 import importlib.util
-from .base_dataset import BaseDataset
+
 from ..utils.tools import get_class
+from .base_dataset import BaseDataset
 
 
 def get_dataset(name):

gluefactory/datasets/augmentations.py

@@ -1,11 +1,11 @@
 from typing import Union
 
 import albumentations as A
+import cv2
 import numpy as np
 import torch
 from albumentations.pytorch.transforms import ToTensorV2
 from omegaconf import OmegaConf
-import cv2
 
 
 class IdentityTransform(A.ImageOnlyTransform):

gluefactory/datasets/base_dataset.py

@@ -3,12 +3,13 @@ Base class for dataset.
 See mnist.py for an example of dataset.
 """
 
-from abc import ABCMeta, abstractmethod
 import collections
 import logging
-from omegaconf import OmegaConf
+from abc import ABCMeta, abstractmethod
+
 import omegaconf
 import torch
+from omegaconf import OmegaConf
 from torch.utils.data import DataLoader, Sampler, get_worker_info
 from torch.utils.data._utils.collate import (
     default_collate_err_msg_format,

gluefactory/datasets/eth3d.py

@@ -4,18 +4,18 @@ ETH3D multi-view benchmark, used for line matching evaluation.
 import logging
 import os
 import shutil
-
-import numpy as np
-import cv2
-import torch
-from pathlib import Path
 import zipfile
+from pathlib import Path
+
+import cv2
+import numpy as np
+import torch
 
-from .base_dataset import BaseDataset
-from .utils import scale_intrinsics
 from ..geometry.wrappers import Camera, Pose
 from ..settings import DATA_PATH
 from ..utils.image import ImagePreprocessor, load_image
+from .base_dataset import BaseDataset
+from .utils import scale_intrinsics
 
 logger = logging.getLogger(__name__)
 

gluefactory/datasets/homographies.py

@@ -11,25 +11,25 @@ import tarfile
 from pathlib import Path
 
 import cv2
+import matplotlib.pyplot as plt
 import numpy as np
 import omegaconf
 import torch
-import matplotlib.pyplot as plt
 from omegaconf import OmegaConf
 from tqdm import tqdm
 
-from .augmentations import IdentityAugmentation, augmentations
-from .base_dataset import BaseDataset
-from ..settings import DATA_PATH
-from ..models.cache_loader import CacheLoader, pad_local_features
-from ..utils.image import read_image
 from ..geometry.homography import (
-    sample_homography_corners,
     compute_homography,
+    sample_homography_corners,
     warp_points,
 )
+from ..models.cache_loader import CacheLoader, pad_local_features
+from ..settings import DATA_PATH
+from ..utils.image import read_image
 from ..utils.tools import fork_rng
 from ..visualization.viz2d import plot_image_grid
+from .augmentations import IdentityAugmentation, augmentations
+from .base_dataset import BaseDataset
 
 logger = logging.getLogger(__name__)
 

gluefactory/datasets/hpatches.py

@@ -4,16 +4,17 @@ Simply load images from a folder or nested folders (does not have any split).
 import argparse
 import logging
 import tarfile
+
 import matplotlib.pyplot as plt
 import numpy as np
 import torch
 from omegaconf import OmegaConf
 
-from .base_dataset import BaseDataset
 from ..settings import DATA_PATH
-from ..utils.image import load_image, ImagePreprocessor
+from ..utils.image import ImagePreprocessor, load_image
 from ..utils.tools import fork_rng
 from ..visualization.viz2d import plot_image_grid
+from .base_dataset import BaseDataset
 
 logger = logging.getLogger(__name__)
 

gluefactory/datasets/image_folder.py

@@ -2,13 +2,14 @@
 Simply load images from a folder or nested folders (does not have any split).
 """
 
-from pathlib import Path
-import torch
 import logging
-import omegaconf
+from pathlib import Path
 
+import omegaconf
+import torch
+
+from ..utils.image import ImagePreprocessor, load_image
 from .base_dataset import BaseDataset
-from ..utils.image import load_image, ImagePreprocessor
 
 
 class ImageFolder(BaseDataset, torch.utils.data.Dataset):

gluefactory/datasets/image_pairs.py

@@ -3,13 +3,14 @@ Simply load images from a folder or nested folders (does not have any split).
 """
 
 from pathlib import Path
-import torch
-import numpy as np
-from .base_dataset import BaseDataset
-from ..utils.image import load_image, ImagePreprocessor
 
-from ..settings import DATA_PATH
+import numpy as np
+import torch
+
 from ..geometry.wrappers import Camera, Pose
+from ..settings import DATA_PATH
+from ..utils.image import ImagePreprocessor, load_image
+from .base_dataset import BaseDataset
 
 
 def names_to_pair(name0, name1, separator="/"):

gluefactory/datasets/megadepth.py

@@ -1,9 +1,9 @@
 import argparse
 import logging
-from pathlib import Path
-from collections.abc import Iterable
-import tarfile
 import shutil
+import tarfile
+from collections.abc import Iterable
+from pathlib import Path
 
 import h5py
 import matplotlib.pyplot as plt
@@ -12,18 +12,14 @@ import PIL.Image
 import torch
 from omegaconf import OmegaConf
 
-from .base_dataset import BaseDataset
-from .utils import (
-    scale_intrinsics,
-    rotate_intrinsics,
-    rotate_pose_inplane,
-)
 from ..geometry.wrappers import Camera, Pose
 from ..models.cache_loader import CacheLoader
-from ..utils.tools import fork_rng
-from ..utils.image import load_image, ImagePreprocessor
 from ..settings import DATA_PATH
-from ..visualization.viz2d import plot_image_grid, plot_heatmaps
+from ..utils.image import ImagePreprocessor, load_image
+from ..utils.tools import fork_rng
+from ..visualization.viz2d import plot_heatmaps, plot_image_grid
+from .base_dataset import BaseDataset
+from .utils import rotate_intrinsics, rotate_pose_inplane, scale_intrinsics
 
 logger = logging.getLogger(__name__)
 scene_lists_path = Path(__file__).parent / "megadepth_scene_lists"

gluefactory/eval/__init__.py

@@ -1,4 +1,5 @@
 import torch
+
 from ..utils.tools import get_class
 from .eval_pipeline import EvalPipeline
 

gluefactory/eval/eth3d.py

@@ -1,23 +1,18 @@
-from pathlib import Path
-from omegaconf import OmegaConf
-import matplotlib.pyplot as plt
 from collections import defaultdict
-from tqdm import tqdm
+from pathlib import Path
+
+import matplotlib.pyplot as plt
 import numpy as np
+from omegaconf import OmegaConf
+from tqdm import tqdm
 
-from .io import (
-    parse_eval_args,
-    load_model,
-    get_eval_parser,
-)
-
-from .eval_pipeline import EvalPipeline, load_eval
-
-from ..utils.export_predictions import export_predictions
-from .utils import get_tp_fp_pts, aggregate_pr_results
-from ..settings import EVAL_PATH
-from ..models.cache_loader import CacheLoader
 from ..datasets import get_dataset
+from ..models.cache_loader import CacheLoader
+from ..settings import EVAL_PATH
+from ..utils.export_predictions import export_predictions
+from .eval_pipeline import EvalPipeline, load_eval
+from .io import get_eval_parser, load_model, parse_eval_args
+from .utils import aggregate_pr_results, get_tp_fp_pts
 
 
 def eval_dataset(loader, pred_file, suffix=""):

gluefactory/eval/eval_pipeline.py

@@ -1,7 +1,8 @@
-from omegaconf import OmegaConf
-import numpy as np
 import json
+
 import h5py
+import numpy as np
+from omegaconf import OmegaConf
 
 
 def load_eval(dir):

gluefactory/eval/hpatches.py

@@ -1,31 +1,27 @@
-from pathlib import Path
-from omegaconf import OmegaConf
-from pprint import pprint
-import matplotlib.pyplot as plt
 from collections import defaultdict
 from collections.abc import Iterable
-from tqdm import tqdm
+from pathlib import Path
+from pprint import pprint
+
+import matplotlib.pyplot as plt
 import numpy as np
-from ..visualization.viz2d import plot_cumulative
+from omegaconf import OmegaConf
+from tqdm import tqdm
 
-from .io import (
-    parse_eval_args,
-    load_model,
-    get_eval_parser,
-)
-from ..utils.export_predictions import export_predictions
-from ..settings import EVAL_PATH
-from ..models.cache_loader import CacheLoader
 from ..datasets import get_dataset
-from .utils import (
+from ..models.cache_loader import CacheLoader
-    eval_homography_robust,
+from ..settings import EVAL_PATH
-    eval_poses,
+from ..utils.export_predictions import export_predictions
-    eval_matches_homography,
-    eval_homography_dlt,
-)
 from ..utils.tools import AUCMetric
-
+from ..visualization.viz2d import plot_cumulative
 from .eval_pipeline import EvalPipeline
+from .io import get_eval_parser, load_model, parse_eval_args
+from .utils import (
+    eval_homography_dlt,
+    eval_homography_robust,
+    eval_matches_homography,
+    eval_poses,
+)
 
 
 class HPatchesPipeline(EvalPipeline):

gluefactory/eval/inspect.py

@@ -1,9 +1,10 @@
 import argparse
-from pathlib import Path
-import matplotlib.pyplot as plt
-import matplotlib
-from pprint import pprint
 from collections import defaultdict
+from pathlib import Path
+from pprint import pprint
+
+import matplotlib
+import matplotlib.pyplot as plt
 
 from ..settings import EVAL_PATH
 from ..visualization.global_frame import GlobalFrame
@@ -11,7 +12,6 @@ from ..visualization.two_view_frame import TwoViewFrame
 from . import get_benchmark
 from .eval_pipeline import load_eval
 
-
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()
     parser.add_argument("benchmark", type=str)

gluefactory/eval/io.py

@@ -1,13 +1,14 @@
-import pkg_resources
-from pathlib import Path
-from typing import Optional
-from omegaconf import OmegaConf
 import argparse
+from pathlib import Path
 from pprint import pprint
+from typing import Optional
+
+import pkg_resources
+from omegaconf import OmegaConf
 
 from ..models import get_model
-from ..utils.experiments import load_experiment
 from ..settings import TRAINING_PATH
+from ..utils.experiments import load_experiment
 
 
 def parse_config_path(name_or_path: Optional[str], defaults: str) -> Path:

gluefactory/eval/megadepth1500.py

@@ -1,26 +1,23 @@
-import torch
+import zipfile
-from pathlib import Path
-from omegaconf import OmegaConf
-from pprint import pprint
-import matplotlib.pyplot as plt
 from collections import defaultdict
 from collections.abc import Iterable
-from tqdm import tqdm
+from pathlib import Path
-import zipfile
+from pprint import pprint
-import numpy as np
-from ..visualization.viz2d import plot_cumulative
-from .io import (
-    parse_eval_args,
-    load_model,
-    get_eval_parser,
-)
-from ..utils.export_predictions import export_predictions
-from ..settings import EVAL_PATH, DATA_PATH
-from ..models.cache_loader import CacheLoader
-from ..datasets import get_dataset
-from .eval_pipeline import EvalPipeline
 
-from .utils import eval_relative_pose_robust, eval_poses, eval_matches_epipolar
+import matplotlib.pyplot as plt
+import numpy as np
+import torch
+from omegaconf import OmegaConf
+from tqdm import tqdm
+
+from ..datasets import get_dataset
+from ..models.cache_loader import CacheLoader
+from ..settings import DATA_PATH, EVAL_PATH
+from ..utils.export_predictions import export_predictions
+from ..visualization.viz2d import plot_cumulative
+from .eval_pipeline import EvalPipeline
+from .io import get_eval_parser, load_model, parse_eval_args
+from .utils import eval_matches_epipolar, eval_poses, eval_relative_pose_robust
 
 
 class MegaDepth1500Pipeline(EvalPipeline):

gluefactory/eval/utils.py

@@ -1,11 +1,12 @@
+import kornia
 import numpy as np
 import torch
-import kornia
+
-from ..geometry.epipolar import relative_pose_error, generalized_epi_dist
+from ..geometry.epipolar import generalized_epi_dist, relative_pose_error
-from ..geometry.homography import sym_homography_error, homography_corner_error
 from ..geometry.gt_generation import IGNORE_FEATURE
-from ..utils.tools import AUCMetric
+from ..geometry.homography import homography_corner_error, sym_homography_error
 from ..robust_estimators import load_estimator
+from ..utils.tools import AUCMetric
 
 
 def check_keys_recursive(d, pattern):

gluefactory/geometry/depth.py

@@ -1,5 +1,5 @@
-import torch
 import kornia
+import torch
 
 from .utils import get_image_coords
 from .wrappers import Camera

gluefactory/geometry/epipolar.py

@@ -1,7 +1,8 @@
-import torch
-from .utils import skew_symmetric, to_homogeneous
-from .wrappers import Pose, Camera
 import numpy as np
+import torch
+
+from .utils import skew_symmetric, to_homogeneous
+from .wrappers import Camera, Pose
 
 
 def T_to_E(T: Pose):

gluefactory/geometry/gt_generation.py

@@ -2,9 +2,9 @@ import numpy as np
 import torch
 from scipy.optimize import linear_sum_assignment
 
-from .homography import warp_points_torch
+from .depth import project, sample_depth
 from .epipolar import T_to_E, sym_epipolar_distance_all
-from .depth import sample_depth, project
+from .homography import warp_points_torch
 
 IGNORE_FEATURE = -2
 UNMATCHED_FEATURE = -1

gluefactory/geometry/homography.py

@@ -1,9 +1,10 @@
-from typing import Tuple
 import math
+from typing import Tuple
+
 import numpy as np
 import torch
 
-from .utils import to_homogeneous, from_homogeneous
+from .utils import from_homogeneous, to_homogeneous
 
 
 def flat2mat(H):

gluefactory/geometry/wrappers.py

@@ -6,13 +6,14 @@ Based on PyTorch tensors: differentiable, batched, with GPU support.
 import functools
 import inspect
 import math
-from typing import Union, Tuple, List, Dict, NamedTuple, Optional
+from typing import Dict, List, NamedTuple, Optional, Tuple, Union
-import torch
+
 import numpy as np
+import torch
 
 from .utils import (
-    distort_points,
     J_distort_points,
+    distort_points,
     skew_symmetric,
     so3exp_map,
     to_homogeneous,

gluefactory/models/__init__.py

@@ -1,6 +1,7 @@
 import importlib.util
-from .base_model import BaseModel
+
 from ..utils.tools import get_class
+from .base_model import BaseModel
 
 
 def get_model(name):

gluefactory/models/base_model.py

@@ -3,10 +3,11 @@ Base class for trainable models.
 """
 
 from abc import ABCMeta, abstractmethod
+from copy import copy
+
 import omegaconf
 from omegaconf import OmegaConf
 from torch import nn
-from copy import copy
 
 
 class MetaModel(ABCMeta):

gluefactory/models/cache_loader.py

@@ -1,11 +1,12 @@
-import torch
 import string
-import h5py
 
-from .base_model import BaseModel
+import h5py
-from ..settings import DATA_PATH
+import torch
+
 from ..datasets.base_dataset import collate
+from ..settings import DATA_PATH
 from ..utils.tensor import batch_to_device
+from .base_model import BaseModel
 from .utils.misc import pad_to_length
 
 

gluefactory/models/extractors/aliked.py

@@ -1,10 +1,11 @@
+from typing import Callable, Optional
+
 import torch
-from torch import nn
 import torch.nn.functional as F
-from torchvision.models import resnet
-from typing import Optional, Callable
-from torch.nn.modules.utils import _pair
 import torchvision
+from torch import nn
+from torch.nn.modules.utils import _pair
+from torchvision.models import resnet
 
 from gluefactory.models.base_model import BaseModel
 

gluefactory/models/extractors/disk_kornia.py

@@ -1,5 +1,5 @@
-import torch
 import kornia
+import torch
 
 from ..base_model import BaseModel
 from ..utils.misc import pad_and_stack

gluefactory/models/extractors/grid_extractor.py

@@ -1,6 +1,7 @@
-import torch
 import math
 
+import torch
+
 from ..base_model import BaseModel
 
 

gluefactory/models/extractors/keynet_affnet_hardnet.py

@@ -1,5 +1,5 @@
-import torch
 import kornia
+import torch
 
 from ..base_model import BaseModel
 from ..utils.misc import pad_to_length

gluefactory/models/extractors/mixed.py

@@ -1,10 +1,8 @@
-from omegaconf import OmegaConf
 import torch.nn.functional as F
+from omegaconf import OmegaConf
 
-from ..base_model import BaseModel
 from .. import get_model
-
+from ..base_model import BaseModel
-# from ...geometry.depth import sample_fmap
 
 to_ctr = OmegaConf.to_container  # convert DictConfig to dict
 

gluefactory/models/extractors/sift.py

@@ -1,12 +1,11 @@
-import numpy as np
-import torch
-import pycolmap
-from scipy.spatial import KDTree
-from omegaconf import OmegaConf
 import cv2
+import numpy as np
+import pycolmap
+import torch
+from omegaconf import OmegaConf
+from scipy.spatial import KDTree
 
 from ..base_model import BaseModel
-
 from ..utils.misc import pad_to_length
 
 EPS = 1e-6

gluefactory/models/extractors/superpoint_open.py

@@ -5,11 +5,12 @@
    The implementation of this model and its trained weights are made
    available under the MIT license.
 """
-import torch.nn as nn
-import torch
 from collections import OrderedDict
 from types import SimpleNamespace
 
+import torch
+import torch.nn as nn
+
 from ..base_model import BaseModel
 from ..utils.misc import pad_and_stack
 

gluefactory/models/lines/deeplsd.py

@@ -1,9 +1,9 @@
+import deeplsd.models.deeplsd_inference as deeplsd_inference
 import numpy as np
 import torch
-import deeplsd.models.deeplsd_inference as deeplsd_inference
 
-from ..base_model import BaseModel
 from ...settings import DATA_PATH
+from ..base_model import BaseModel
 
 
 class DeepLSD(BaseModel):

gluefactory/models/lines/wireframe.py

@@ -1,8 +1,8 @@
 import torch
 from sklearn.cluster import DBSCAN
 
-from ..base_model import BaseModel
 from .. import get_model
+from ..base_model import BaseModel
 
 
 def sample_descriptors_corner_conv(keypoints, descriptors, s: int = 8):

gluefactory/models/matchers/depth_matcher.py

@@ -1,10 +1,11 @@
-from ..base_model import BaseModel
-from ...geometry.gt_generation import (
-    gt_matches_from_pose_depth,
-    gt_line_matches_from_pose_depth,
-)
 import torch
 
+from ...geometry.gt_generation import (
+    gt_line_matches_from_pose_depth,
+    gt_matches_from_pose_depth,
+)
+from ..base_model import BaseModel
+
 
 class DepthMatcher(BaseModel):
     default_conf = {

gluefactory/models/matchers/gluestick.py

@@ -7,9 +7,9 @@ import torch
 import torch.utils.checkpoint
 from torch import nn
 
+from ...settings import DATA_PATH
 from ..base_model import BaseModel
 from ..utils.metrics import matcher_metrics
-from ...settings import DATA_PATH
 
 warnings.filterwarnings("ignore", category=UserWarning)
 ETH_EPS = 1e-8

gluefactory/models/matchers/homography_matcher.py

@@ -1,8 +1,8 @@
-from ..base_model import BaseModel
 from ...geometry.gt_generation import (
-    gt_matches_from_homography,
     gt_line_matches_from_homography,
+    gt_matches_from_homography,
 )
+from ..base_model import BaseModel
 
 
 class HomographyMatcher(BaseModel):

gluefactory/models/matchers/lightglue.py

@@ -1,15 +1,17 @@
 import warnings
+from pathlib import Path
+from typing import Callable, List, Optional
+
 import numpy as np
 import torch
-from torch import nn
 import torch.nn.functional as F
-from typing import Optional, List, Callable
-from torch.utils.checkpoint import checkpoint
 from omegaconf import OmegaConf
+from torch import nn
+from torch.utils.checkpoint import checkpoint
+
 from ...settings import DATA_PATH
 from ..utils.losses import NLLLoss
 from ..utils.metrics import matcher_metrics
-from pathlib import Path
 
 FLASH_AVAILABLE = hasattr(F, "scaled_dot_product_attention")
 

gluefactory/models/matchers/lightglue_pretrained.py

@@ -1,7 +1,8 @@
-from ..base_model import BaseModel
 from lightglue import LightGlue as LightGlue_
 from omegaconf import OmegaConf
 
+from ..base_model import BaseModel
+
 
 class LightGlue(BaseModel):
     default_conf = {"features": "superpoint", **LightGlue_.default_conf}

gluefactory/models/matchers/nearest_neighbor_matcher.py

@@ -3,8 +3,9 @@ Nearest neighbor matcher for normalized descriptors.
 Optionally apply the mutual check and threshold the distance or ratio.
 """
 
-import torch
 import logging
+
+import torch
 import torch.nn.functional as F
 
 from ..base_model import BaseModel

gluefactory/models/triplet_pipeline.py

@@ -9,9 +9,10 @@ Losses and metrics get accumulated accordingly.
 If no triplet is found, this falls back to two_view_pipeline.py
 """
 
-from .two_view_pipeline import TwoViewPipeline
 import torch
+
 from ..utils.misc import get_twoview, stack_twoviews, unstack_twoviews
+from .two_view_pipeline import TwoViewPipeline
 
 
 def has_triplet(data):

gluefactory/models/two_view_pipeline.py

@@ -11,9 +11,9 @@ that corresponds to the keypoint i in image 0. m0[i] = -1 if i is unmatched.
 """
 
 from omegaconf import OmegaConf
-from .base_model import BaseModel
-from . import get_model
 
+from . import get_model
+from .base_model import BaseModel
 
 to_ctr = OmegaConf.to_container  # convert DictConfig to dict
 

gluefactory/models/utils/misc.py

@@ -1,5 +1,6 @@
 import math
 from typing import List, Optional, Tuple
+
 import torch
 
 

gluefactory/robust_estimators/__init__.py

@@ -1,4 +1,5 @@
 import inspect
+
 from .base_estimator import BaseEstimator
 
 

gluefactory/robust_estimators/base_estimator.py

@@ -1,6 +1,7 @@
-from omegaconf import OmegaConf
 from copy import copy
 
+from omegaconf import OmegaConf
+
 
 class BaseEstimator:
     base_default_conf = {

gluefactory/robust_estimators/homography/poselib.py

@@ -1,6 +1,6 @@
 import poselib
-from omegaconf import OmegaConf
 import torch
+from omegaconf import OmegaConf
 
 from ..base_estimator import BaseEstimator
 

gluefactory/robust_estimators/relative_pose/opencv.py

@@ -1,9 +1,9 @@
 import cv2
 import numpy as np
 import torch
-from ...geometry.wrappers import Pose
-from ...geometry.utils import from_homogeneous
 
+from ...geometry.utils import from_homogeneous
+from ...geometry.wrappers import Pose
 from ..base_estimator import BaseEstimator
 
 

gluefactory/robust_estimators/relative_pose/poselib.py

@@ -1,8 +1,8 @@
 import poselib
-from omegaconf import OmegaConf
 import torch
-from ...geometry.wrappers import Pose
+from omegaconf import OmegaConf
 
+from ...geometry.wrappers import Pose
 from ..base_estimator import BaseEstimator
 
 

gluefactory/robust_estimators/relative_pose/pycolmap.py

@@ -1,8 +1,8 @@
 import pycolmap
-from omegaconf import OmegaConf
 import torch
-from ...geometry.wrappers import Pose
+from omegaconf import OmegaConf
 
+from ...geometry.wrappers import Pose
 from ..base_estimator import BaseEstimator
 
 

gluefactory/scripts/export_local_features.py

@@ -1,14 +1,14 @@
+import argparse
 import logging
 from pathlib import Path
-import argparse
+
 import torch
 from omegaconf import OmegaConf
 
+from ..datasets import get_dataset
+from ..models import get_model
 from ..settings import DATA_PATH
 from ..utils.export_predictions import export_predictions
-from ..models import get_model
-from ..datasets import get_dataset
-
 
 resize = 1600
 

gluefactory/scripts/export_megadepth.py

@@ -1,14 +1,15 @@
+import argparse
 import logging
 from pathlib import Path
-import argparse
+
 import torch
 from omegaconf import OmegaConf
 
-from ..settings import DATA_PATH
-from ..utils.export_predictions import export_predictions
-from ..models import get_model
 from ..datasets import get_dataset
 from ..geometry.depth import sample_depth
+from ..models import get_model
+from ..settings import DATA_PATH
+from ..utils.export_predictions import export_predictions
 
 resize = 1024
 n_kpts = 2048

gluefactory/train.py

@@ -5,37 +5,37 @@ Author: Paul-Edouard Sarlin (skydes)
 """
 
 import argparse
-from pathlib import Path
-import signal
-import re
 import copy
-from collections import defaultdict
+import re
 import shutil
-import numpy as np
+import signal
-
+from collections import defaultdict
-from omegaconf import OmegaConf
+from pathlib import Path
-from tqdm import tqdm
-import torch
-from torch.utils.tensorboard import SummaryWriter
-from torch.cuda.amp import GradScaler, autocast
 from pydoc import locate
 
-from .models import get_model
+import numpy as np
+import torch
+from omegaconf import OmegaConf
+from torch.cuda.amp import GradScaler, autocast
+from torch.utils.tensorboard import SummaryWriter
+from tqdm import tqdm
+
+from . import __module_name__, logger
 from .datasets import get_dataset
+from .eval import run_benchmark
+from .models import get_model
+from .settings import EVAL_PATH, TRAINING_PATH
+from .utils.experiments import get_best_checkpoint, get_last_checkpoint, save_experiment
 from .utils.stdout_capturing import capture_outputs
+from .utils.tensor import batch_to_device
 from .utils.tools import (
     AverageMetric,
     MedianMetric,
-    RecallMetric,
     PRMetric,
-    set_seed,
+    RecallMetric,
     fork_rng,
+    set_seed,
 )
-from .utils.tensor import batch_to_device
-from .utils.experiments import get_last_checkpoint, get_best_checkpoint, save_experiment
-from .eval import run_benchmark
-from .settings import TRAINING_PATH, EVAL_PATH
-from . import __module_name__, logger
 
 # @TODO: Fix pbar pollution in logs
 # @TODO: add plotting during evaluation

gluefactory/utils/benchmark.py

@@ -1,7 +1,8 @@
-import torch
-import numpy as np
 import time
 
+import numpy as np
+import torch
+
 
 def benchmark(model, data, device, r=100):
     timings = np.zeros((r, 1))

gluefactory/utils/experiments.py

@@ -4,16 +4,17 @@ A set of utilities to manage and load checkpoints of training experiments.
 Author: Paul-Edouard Sarlin (skydes)
 """
 
-from pathlib import Path
 import logging
+import os
 import re
 import shutil
-from omegaconf import OmegaConf
+from pathlib import Path
-import torch
+
-import os
+import torch
+from omegaconf import OmegaConf
 
-from ..settings import TRAINING_PATH
 from ..models import get_model
+from ..settings import TRAINING_PATH
 
 logger = logging.getLogger(__name__)
 

gluefactory/utils/export_predictions.py

@@ -4,11 +4,12 @@ Use a standalone script with `python3 -m dsfm.scipts.export_predictions dir`
 or call from another script.
 """
 
-import torch
-import numpy as np
 from pathlib import Path
-from tqdm import tqdm
+
 import h5py
+import numpy as np
+import torch
+from tqdm import tqdm
 
 from .tensor import batch_to_device
 

gluefactory/utils/image.py

@@ -1,10 +1,11 @@
-from pathlib import Path
-import torch
-import kornia
-import cv2
-import numpy as np
-from typing import Tuple, Optional
 import collections.abc as collections
+from pathlib import Path
+from typing import Optional, Tuple
+
+import cv2
+import kornia
+import numpy as np
+import torch
 from omegaconf import OmegaConf
 
 

gluefactory/utils/stdout_capturing.py

@@ -6,11 +6,12 @@ Author: Paul-Edouard Sarlin (skydes)
 """
 
 from __future__ import division, print_function, unicode_literals
+
 import os
-import sys
 import subprocess
-from threading import Timer
+import sys
 from contextlib import contextmanager
+from threading import Timer
 
 
 def apply_backspaces_and_linefeeds(text):

gluefactory/utils/tensor.py

@@ -3,8 +3,9 @@ Author: Paul-Edouard Sarlin (skydes)
 """
 
 import collections.abc as collections
-import torch
+
 import numpy as np
+import torch
 
 string_classes = (str, bytes)
 

gluefactory/utils/tools.py

@@ -4,13 +4,14 @@ Various handy Python and PyTorch utils.
 Author: Paul-Edouard Sarlin (skydes)
 """
 
-import time
-import numpy as np
 import os
-import torch
 import random
-from contextlib import contextmanager
+import time
 from collections.abc import Iterable
+from contextlib import contextmanager
+
+import numpy as np
+import torch
 
 
 class AverageMetric:

gluefactory/visualization/global_frame.py

@@ -1,14 +1,16 @@
-import traceback
-import numpy as np
-import matplotlib.pyplot as plt
-from omegaconf import OmegaConf
-from matplotlib.widgets import Button
-from copy import deepcopy
 import functools
+import traceback
+from copy import deepcopy
+
+import matplotlib.pyplot as plt
+import numpy as np
+from matplotlib.widgets import Button
+from omegaconf import OmegaConf
+
+from ..datasets.base_dataset import collate
 
 # from ..eval.export_predictions import load_predictions
 from ..models.cache_loader import CacheLoader
-from ..datasets.base_dataset import collate
 from .tools import RadioHideTool
 
 

gluefactory/visualization/tools.py

@@ -1,25 +1,25 @@
+import inspect
+import sys
+import warnings
+
 import matplotlib.pyplot as plt
+import torch
 from matplotlib.backend_tools import ToolToggleBase
 from matplotlib.widgets import RadioButtons, Slider
-import warnings
-import torch
 
+from ..geometry.epipolar import T_to_F, generalized_epi_dist
+from ..geometry.homography import sym_homography_error
 from ..visualization.viz2d import (
+    cm_ranking,
+    cm_RdGn,
+    draw_epipolar_line,
+    get_line,
+    plot_color_line_matches,
     plot_heatmaps,
     plot_keypoints,
     plot_lines,
     plot_matches,
-    plot_color_line_matches,
-    cm_RdGn,
-    cm_ranking,
-    get_line,
-    draw_epipolar_line,
 )
-from ..geometry.homography import sym_homography_error
-from ..geometry.epipolar import generalized_epi_dist, T_to_F
-
-import inspect
-import sys
 
 with warnings.catch_warnings():
     warnings.simplefilter("ignore")

gluefactory/visualization/two_view_frame.py

@@ -1,10 +1,9 @@
-import numpy as np
 import pprint
+
+import numpy as np
+
 from . import viz2d
-
+from .tools import RadioHideTool, ToggleTool, __plot_dict__
-from .tools import __plot_dict__
-
-from .tools import RadioHideTool, ToggleTool
 
 
 class FormatPrinter(pprint.PrettyPrinter):

gluefactory/visualization/visualize_batch.py

@@ -1,13 +1,7 @@
 import torch
 
 from ..utils.tensor import batch_to_device
-from .viz2d import (
+from .viz2d import cm_RdGn, plot_heatmaps, plot_image_grid, plot_keypoints, plot_matches
-    plot_image_grid,
-    plot_keypoints,
-    plot_matches,
-    cm_RdGn,
-    plot_heatmaps,
-)
 
 
 def make_match_figures(pred_, data_, n_pairs=2):

gluefactory/visualization/viz2d.py

@@ -6,8 +6,8 @@
 """
 
 import matplotlib
-import matplotlib.pyplot as plt
 import matplotlib.patheffects as path_effects
+import matplotlib.pyplot as plt
 import numpy as np
 import seaborn as sns
 

pyproject.toml

@@ -43,10 +43,14 @@ extra = [
     "deeplsd @ git+https://github.com/cvg/DeepLSD.git",
     "homography_est @ git+https://github.com/rpautrat/homography_est.git",
 ]
-dev = ["black", "flake8", "jupyter"]
+dev = ["black", "flake8", "isort"]
 
 [tool.setuptools.packages.find]
 include = ["gluefactory*"]
 
 [tool.setuptools.package-data]
 gluefactory = ["datasets/megadepth_scene_lists/*.txt", "configs/*.yaml"]
+
+[tool.isort]
+profile = "black"
+extend_skip = ["gluefactory_nonfree/"]