Code formatting (#47)

* Add formatting CI
* Apply black and isort
* Fix flake8 errors
* Add bash script

.github/workflows/code-quality.yml

@@ -0,0 +1,25 @@
+name: Format and Lint
+on:
+  push:
+    branches:
+      - master
+    paths:
+      - '*.py'
+      - '*.ipynb'
+  pull_request:
+    types: [ assigned, opened, synchronize, reopened ]
+jobs:
+  check:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: '3.10'
+          cache: 'pip'
+          cache-dependency-path: 'requirements/dev.txt'
+      - run: python -m pip install --upgrade pip
+      - run: python -m pip install -r requirements/dev.txt
+      - run: python -m flake8 maploc
+      - run: python -m isort maploc *.ipynb --check-only --diff
+      - run: python -m black maploc *.ipynb --check --diff

.isort.cfg

@@ -0,0 +1,2 @@
+[settings]
+profile=black

demo.ipynb

@@ -14,7 +14,7 @@
     "# The highest accuracy is achieved with num_rotations=360\n",
     "# but num_rotations=64~128 is often sufficient.\n",
     "# To reduce the memory usage, we can reduce the tile size in the next cell.\n",
-    "demo = Demo(num_rotations=256, device='cpu')"
+    "demo = Demo(num_rotations=256, device=\"cpu\")"
    ]
   },
   {
@@ -135,6 +135,7 @@
     "\n",
     "# Show the query area in an interactive map\n",
     "from maploc.osm.viz import GeoPlotter\n",
+    "\n",
     "plot = GeoPlotter(zoom=16)\n",
     "plot.points(prior_latlon[:2], \"red\", name=\"location prior\", size=10)\n",
     "plot.bbox(proj.unproject(bbox), \"blue\", name=\"map tile\")\n",
@@ -142,12 +143,14 @@
     "\n",
     "# Query OpenStreetMap for this area\n",
     "from maploc.osm.tiling import TileManager\n",
+    "\n",
     "tiler = TileManager.from_bbox(proj, bbox + 10, demo.config.data.pixel_per_meter)\n",
     "canvas = tiler.query(bbox)\n",
     "\n",
     "# Show the inputs to the model: image and raster map\n",
     "from maploc.osm.viz import Colormap, plot_nodes\n",
     "from maploc.utils.viz_2d import plot_images\n",
+    "\n",
     "map_viz = Colormap.apply(canvas.raster)\n",
     "plot_images([image, map_viz], titles=[\"input image\", \"OpenStreetMap raster\"])\n",
     "plot_nodes(1, canvas.raster[2], fontsize=6, size=10)"
@@ -1186,7 +1189,8 @@
     "\n",
     "# Run the inference\n",
     "uv, yaw, prob, neural_map, image_rectified = demo.localize(\n",
-    "    image, camera, canvas, roll_pitch=gravity)\n",
+    "    image, camera, canvas, roll_pitch=gravity\n",
+    ")\n",
     "\n",
     "# Visualize the predictions\n",
     "overlay = likelihood_overlay(prob.numpy().max(-1), map_viz.mean(-1, keepdims=True))\n",
@@ -1194,7 +1198,7 @@
     "plot_images([overlay, neural_map_rgb], titles=[\"prediction\", \"neural map\"])\n",
     "ax = plt.gcf().axes[0]\n",
     "ax.scatter(*canvas.to_uv(bbox.center), s=5, c=\"red\")\n",
-    "plot_dense_rotations(ax, prob, w=0.005, s=1/25)\n",
+    "plot_dense_rotations(ax, prob, w=0.005, s=1 / 25)\n",
     "add_circle_inset(ax, uv)\n",
     "plt.show(\"notebook\")\n",
     "\n",

format.sh

@@ -0,0 +1,6 @@
+all_files=$(git ls-tree --full-tree -r --name-only HEAD .)
+py_files=$(echo "$all_files" | grep ".*\.py$")
+nb_files=$(echo "$all_files" | grep ".*\.ipynb$" | grep -v "^notebooks")
+python -m black $py_files $nb_files
+python -m isort $py_files $nb_files
+python -m flake8 $py_files

maploc/__init__.py

@@ -1,11 +1,10 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 
-from pathlib import Path
 import logging
+from pathlib import Path
 
 import pytorch_lightning  # noqa: F401
 
-
 formatter = logging.Formatter(
     fmt="[%(asctime)s %(name)s %(levelname)s] %(message)s",
     datefmt="%Y-%m-%d %H:%M:%S",

maploc/data/image.py

@@ -1,11 +1,11 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 
-from typing import Callable, Optional, Union, Sequence
+import collections
+from typing import Callable, Optional, Sequence, Union
 
 import numpy as np
 import torch
 import torchvision.transforms.functional as tvf
-import collections
 from scipy.spatial.transform import Rotation
 
 from ..utils.geometry import from_homogeneous, to_homogeneous

maploc/data/kitti/dataset.py

@@ -13,12 +13,12 @@ import torch.utils.data as torchdata
 from omegaconf import OmegaConf
 from scipy.spatial.transform import Rotation
 
-from ... import logger, DATASETS_PATH
+from ... import DATASETS_PATH, logger
 from ...osm.tiling import TileManager
 from ..dataset import MapLocDataset
 from ..sequential import chunk_sequence
 from ..torch import collate, worker_init_fn
-from .utils import parse_split_file, parse_gps_file, get_camera_calibration
+from .utils import get_camera_calibration, parse_gps_file, parse_split_file
 
 
 class KittiDataModule(pl.LightningDataModule):

maploc/data/kitti/prepare.py

@@ -1,9 +1,9 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 
 import argparse
-from pathlib import Path
 import shutil
 import zipfile
+from pathlib import Path
 
 import numpy as np
 from tqdm.auto import tqdm
@@ -12,9 +12,9 @@ from ... import logger
 from ...osm.tiling import TileManager
 from ...osm.viz import GeoPlotter
 from ...utils.geo import BoundaryBox, Projection
-from ...utils.io import download_file, DATA_URL
-from .utils import parse_gps_file
+from ...utils.io import DATA_URL, download_file
 from .dataset import KittiDataModule
+from .utils import parse_gps_file
 
 split_files = ["test1_files.txt", "test2_files.txt", "train_files.txt"]
 
@@ -70,7 +70,7 @@ def download(data_dir: Path):
     for seq in tqdm(seqs):
         logger.info("Working on %s.", seq)
         date = "_".join(seq.split("_")[:3])
-        url = f"https://s3.eu-central-1.amazonaws.com/avg-kitti/raw_data/{seq}/{seq}_sync.zip"
+        url = f"https://s3.eu-central-1.amazonaws.com/avg-kitti/raw_data/{seq}/{seq}_sync.zip"  # noqa E501
         seq_dir = data_dir / date / f"{seq}_sync"
         if seq_dir.exists():
             continue

maploc/data/mapillary/dataset.py

@@ -1,10 +1,10 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 
 import json
-from collections import defaultdict
 import os
 import shutil
 import tarfile
+from collections import defaultdict
 from pathlib import Path
 from typing import Any, Dict, Optional
 
@@ -14,7 +14,7 @@ import torch
 import torch.utils.data as torchdata
 from omegaconf import DictConfig, OmegaConf
 
-from ... import logger, DATASETS_PATH
+from ... import DATASETS_PATH, logger
 from ...osm.tiling import TileManager
 from ..dataset import MapLocDataset
 from ..sequential import chunk_sequence
@@ -115,7 +115,8 @@ class MapillaryDataModule(pl.LightningDataModule):
             if self.cfg.num_classes:  # check consistency
                 if set(groups.keys()) != set(self.cfg.num_classes.keys()):
                     raise ValueError(
-                        f"Inconsistent groups: {groups.keys()} {self.cfg.num_classes.keys()}"
+                        "Inconsistent groups: "
+                        f"{groups.keys()} {self.cfg.num_classes.keys()}"
                     )
                 for k in groups:
                     if len(groups[k]) != self.cfg.num_classes[k]:
@@ -125,8 +126,8 @@ class MapillaryDataModule(pl.LightningDataModule):
             ppm = self.tile_managers[scene].ppm
             if ppm != self.cfg.pixel_per_meter:
                 raise ValueError(
-                    "The tile manager and the config/model have different ground resolutions: "
-                    f"{ppm} vs {self.cfg.pixel_per_meter}"
+                    "The tile manager and the config/model have different ground "
+                    f"resolutions: {ppm} vs {self.cfg.pixel_per_meter}"
                 )
 
             logger.info("Loading dump json file %s.", self.dump_filename)
@@ -136,7 +137,8 @@ class MapillaryDataModule(pl.LightningDataModule):
                 for cam_id, cam_dict in per_seq["cameras"].items():
                     if cam_dict["model"] != "PINHOLE":
                         raise ValueError(
-                            f"Unsupported camera model: {cam_dict['model']} for {scene},{seq},{cam_id}"
+                            "Unsupported camera model: "
+                            f"{cam_dict['model']} for {scene},{seq},{cam_id}"
                         )
 
             self.image_dirs[scene] = (
@@ -154,7 +156,8 @@ class MapillaryDataModule(pl.LightningDataModule):
         self.pack_data()
 
     def pack_data(self):
-        # We pack the data into compact tensors that can be shared across processes without copy
+        # We pack the data into compact tensors
+        # that can be shared across processes without copy.
         exclude = {
             "compass_angle",
             "compass_accuracy",

maploc/data/mapillary/download.py

@@ -1,25 +1,24 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 
+import asyncio
 import json
 from pathlib import Path
 
-import numpy as np
 import httpx
-import asyncio
-from aiolimiter import AsyncLimiter
+import numpy as np
 import tqdm
-
+from aiolimiter import AsyncLimiter
 from opensfm.pygeometry import Camera, Pose
 from opensfm.pymap import Shot
 
 from ... import logger
 from ...utils.geo import Projection
 
-
 semaphore = asyncio.Semaphore(100)  # number of parallel threads.
 image_filename = "{image_id}.jpg"
 info_filename = "{image_id}.json"
 
+
 def retry(times, exceptions):
     def decorator(func):
         async def wrapper(*args, **kwargs):
@@ -30,9 +29,12 @@ def retry(times, exceptions):
                 except exceptions:
                     attempt += 1
             return await func(*args, **kwargs)
+
         return wrapper
+
     return decorator
 
+
 class MapillaryDownloader:
     image_fields = (
         "id",
@@ -56,7 +58,7 @@ class MapillaryDownloader:
     image_info_url = (
         "https://graph.mapillary.com/{image_id}?access_token={token}&fields={fields}"
     )
-    seq_info_url = "https://graph.mapillary.com/image_ids?access_token={token}&sequence_id={seq_id}"
+    seq_info_url = "https://graph.mapillary.com/image_ids?access_token={token}&sequence_id={seq_id}"  # noqa E501
     max_requests_per_minute = 50_000
 
     def __init__(self, token: str):

maploc/data/mapillary/prepare.py

@@ -1,17 +1,15 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 
-import asyncio
 import argparse
-from collections import defaultdict
+import asyncio
 import json
 import shutil
+from collections import defaultdict
 from pathlib import Path
 from typing import List
 
-import numpy as np
 import cv2
-from tqdm import tqdm
-from tqdm.contrib.concurrent import thread_map
+import numpy as np
 from omegaconf import DictConfig, OmegaConf
 from opensfm.pygeometry import Camera
 from opensfm.pymap import Shot
@@ -19,30 +17,31 @@ from opensfm.undistort import (
     perspective_camera_from_fisheye,
     perspective_camera_from_perspective,
 )
+from tqdm import tqdm
+from tqdm.contrib.concurrent import thread_map
 
 from ... import logger
 from ...osm.tiling import TileManager
 from ...osm.viz import GeoPlotter
 from ...utils.geo import BoundaryBox, Projection
-from ...utils.io import write_json, download_file, DATA_URL
+from ...utils.io import DATA_URL, download_file, write_json
 from ..utils import decompose_rotmat
+from .dataset import MapillaryDataModule
+from .download import (
+    MapillaryDownloader,
+    fetch_image_infos,
+    fetch_images_pixels,
+    image_filename,
+    opensfm_shot_from_info,
+)
 from .utils import (
+    CameraUndistorter,
+    PanoramaUndistorter,
     keyframe_selection,
     perspective_camera_from_pano,
     scale_camera,
-    CameraUndistorter,
-    PanoramaUndistorter,
     undistort_shot,
 )
-from .download import (
-    MapillaryDownloader,
-    opensfm_shot_from_info,
-    image_filename,
-    fetch_image_infos,
-    fetch_images_pixels,
-)
-from .dataset import MapillaryDataModule
-
 
 location_to_params = {
     "sanfrancisco_soma": {

maploc/data/mapillary/utils.py

@@ -6,7 +6,7 @@ from typing import List, Tuple
 import cv2
 import numpy as np
 from opensfm import features
-from opensfm.pygeometry import Camera, compute_camera_mapping, Pose
+from opensfm.pygeometry import Camera, Pose, compute_camera_mapping
 from opensfm.pymap import Shot
 from scipy.spatial.transform import Rotation
 

maploc/data/torch.py

@@ -4,14 +4,14 @@ import collections
 import os
 
 import torch
+from lightning_fabric.utilities.apply_func import move_data_to_device
+from lightning_fabric.utilities.seed import pl_worker_init_function
+from lightning_utilities.core.apply_func import apply_to_collection
 from torch.utils.data import get_worker_info
 from torch.utils.data._utils.collate import (
     default_collate_err_msg_format,
     np_str_obj_array_pattern,
 )
-from lightning_fabric.utilities.seed import pl_worker_init_function
-from lightning_utilities.core.apply_func import apply_to_collection
-from lightning_fabric.utilities.apply_func import move_data_to_device
 
 
 def collate(batch):

maploc/data/utils.py

@@ -54,7 +54,5 @@ def decompose_rotmat(R_c2w):
     R_cv2xyz = Rotation.from_euler("X", -90, degrees=True)
     rot_w2c = R_cv2xyz * Rotation.from_matrix(R_c2w).inv()
     roll, pitch, yaw = rot_w2c.as_euler("YXZ", degrees=True)
-    # rot_w2c_check = R_cv2xyz.inv() * Rotation.from_euler('YXZ', [roll, pitch, yaw], degrees=True)
-    # np.testing.assert_allclose(rot_w2c_check.as_matrix(), R_c2w.T, rtol=1e-6, atol=1e-6)
     # R_plane2c = Rotation.from_euler("ZX", [roll, pitch], degrees=True).as_matrix()
     return roll, pitch, yaw

maploc/demo.py

@@ -2,19 +2,19 @@
 
 from typing import Optional, Tuple
 
-import torch
 import numpy as np
+import torch
 
 from . import logger
-from .evaluation.run import resolve_checkpoint_path, pretrained_models
+from .data.image import pad_image, rectify_image, resize_image
+from .evaluation.run import pretrained_models, resolve_checkpoint_path
 from .models.orienternet import OrienterNet
-from .models.voting import fuse_gps, argmax_xyr
-from .data.image import resize_image, pad_image, rectify_image
+from .models.voting import argmax_xyr, fuse_gps
 from .osm.raster import Canvas
-from .utils.wrappers import Camera
-from .utils.io import read_image
-from .utils.geo import BoundaryBox, Projection
 from .utils.exif import EXIF
+from .utils.geo import BoundaryBox, Projection
+from .utils.io import read_image
+from .utils.wrappers import Camera
 
 try:
     from geopy.geocoders import Nominatim

maploc/evaluation/kitti.py

@@ -4,17 +4,16 @@ import argparse
 from pathlib import Path
 from typing import Optional, Tuple
 
-from omegaconf import OmegaConf, DictConfig
+from omegaconf import DictConfig, OmegaConf
 
 from .. import logger
 from ..data import KittiDataModule
 from .run import evaluate
 
-
 default_cfg_single = OmegaConf.create({})
 # For the sequential evaluation, we need to center the map around the GT location,
-# since random offsets would accumulate and leave only the GT location with a valid mask.
-# This should not have much impact on the results.
+# since random offsets would accumulate and leave only the GT location with
+# a valid mask. This should not have much impact on the results.
 default_cfg_sequential = OmegaConf.create(
     {
         "data": {

maploc/evaluation/mapillary.py

@@ -4,14 +4,13 @@ import argparse
 from pathlib import Path
 from typing import Optional, Tuple
 
-from omegaconf import OmegaConf, DictConfig
+from omegaconf import DictConfig, OmegaConf
 
 from .. import logger
 from ..conf import data as conf_data_dir
 from ..data import MapillaryDataModule
 from .run import evaluate
 
-
 split_overrides = {
     "val": {
         "scenes": [

maploc/evaluation/run.py

@@ -2,26 +2,25 @@
 
 import functools
 from itertools import islice
-from typing import Callable, Dict, Optional, Tuple
 from pathlib import Path
+from typing import Callable, Dict, Optional, Tuple
 
 import numpy as np
 import torch
 from omegaconf import DictConfig, OmegaConf
-from torchmetrics import MetricCollection
 from pytorch_lightning import seed_everything
+from torchmetrics import MetricCollection
 from tqdm import tqdm
 
-from .. import logger, EXPERIMENTS_PATH
+from .. import EXPERIMENTS_PATH, logger
 from ..data.torch import collate, unbatch_to_device
-from ..models.voting import argmax_xyr, fuse_gps
 from ..models.metrics import AngleError, LateralLongitudinalError, Location2DError
 from ..models.sequential import GPSAligner, RigidAligner
+from ..models.voting import argmax_xyr, fuse_gps
 from ..module import GenericModule
-from ..utils.io import download_file, DATA_URL
-from .viz import plot_example_single, plot_example_sequential
+from ..utils.io import DATA_URL, download_file
 from .utils import write_dump
-
+from .viz import plot_example_sequential, plot_example_single
 
 pretrained_models = dict(
     OrienterNet_MGL=("orienternet_mgl.ckpt", dict(num_rotations=256)),

maploc/evaluation/viz.py

@@ -1,18 +1,18 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 
+import matplotlib.pyplot as plt
 import numpy as np
 import torch
-import matplotlib.pyplot as plt
 
+from ..osm.viz import Colormap, plot_nodes
 from ..utils.io import write_torch_image
-from ..utils.viz_2d import plot_images, features_to_RGB, save_plot
+from ..utils.viz_2d import features_to_RGB, plot_images, save_plot
 from ..utils.viz_localization import (
+    add_circle_inset,
     likelihood_overlay,
-    plot_pose,
     plot_dense_rotations,
-    add_circle_inset,
+    plot_pose,
 )
-from ..osm.viz import Colormap, plot_nodes
 
 
 def plot_example_single(

maploc/models/orienternet.py

@@ -8,7 +8,10 @@ from . import get_model
 from .base import BaseModel
 from .bev_net import BEVNet
 from .bev_projection import CartesianProjection, PolarProjectionDepth
+from .map_encoder import MapEncoder
+from .metrics import AngleError, AngleRecall, Location2DError, Location2DRecall
 from .voting import (
+    TemplateSampler,
     argmax_xyr,
     conv2d_fft_batchwise,
     expectation_xyr,
@@ -16,10 +19,7 @@ from .voting import (
     mask_yaw_prior,
     nll_loss_xyr,
     nll_loss_xyr_smoothed,
-    TemplateSampler,
 )
-from .map_encoder import MapEncoder
-from .metrics import AngleError, AngleRecall, Location2DError, Location2DRecall
 
 
 class OrienterNet(BaseModel):
@@ -106,8 +106,8 @@ class OrienterNet(BaseModel):
         if self.conf.add_temperature:
             scores = scores * torch.exp(self.temperature)
 
-        # Reweight the different rotations based on the number of valid pixels
-        # in each template. Axis-aligned rotation have the maximum number of valid pixels.
+        # Reweight the different rotations based on the number of valid pixels in each
+        # template. Axis-aligned rotation have the maximum number of valid pixels.
         valid_templates = self.template_sampler(valid_bev.float()[None]) > (1 - 1e-4)
         num_valid = valid_templates.float().sum((-3, -2, -1))
         scores = scores / num_valid[..., None, None]

maploc/models/sequential.py

@@ -3,8 +3,8 @@
 import numpy as np
 import torch
 
-from .voting import argmax_xyr, log_softmax_spatial, sample_xyr
 from .utils import deg2rad, make_grid, rotmat2d
+from .voting import argmax_xyr, log_softmax_spatial, sample_xyr
 
 
 def log_gaussian(points, mean, sigma):

maploc/osm/analysis.py

@@ -8,6 +8,7 @@ import numpy as np
 import plotly.graph_objects as go
 
 from .parser import (
+    Patterns,
     filter_area,
     filter_node,
     filter_way,
@@ -15,7 +16,6 @@ from .parser import (
     parse_area,
     parse_node,
     parse_way,
-    Patterns,
 )
 from .reader import OSMData
 

maploc/osm/data.py

@@ -7,6 +7,7 @@ from typing import Dict, List, Optional, Set, Tuple
 import numpy as np
 
 from .parser import (
+    Patterns,
     filter_area,
     filter_node,
     filter_way,
@@ -14,11 +15,9 @@ from .parser import (
     parse_area,
     parse_node,
     parse_way,
-    Patterns,
 )
 from .reader import OSMData, OSMNode, OSMRelation, OSMWay
 
-
 logger = logging.getLogger(__name__)
 
 

maploc/osm/download.py

@@ -1,9 +1,9 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 
 import json
+from http.client import responses
 from pathlib import Path
 from typing import Any, Dict, Optional
-from http.client import responses
 
 import urllib3
 

maploc/osm/parser.py

@@ -144,7 +144,7 @@ class Patterns:
         building="building($|:.*?)*",
         parking="amenity:parking",
         playground="leisure:(playground|pitch)",
-        grass="(landuse:grass|landcover:grass|landuse:meadow|landuse:flowerbed|natural:grassland)",
+        grass="(landuse:grass|landcover:grass|landuse:meadow|landuse:flowerbed|natural:grassland)",  # noqa E501
         park="leisure:(park|garden|dog_park)",
         forest="(landuse:forest|natural:wood)",
         water="(natural:water|waterway:*)",
@@ -160,7 +160,7 @@ class Patterns:
         building_outline="building($|:.*?)*",
         cycleway="highway:cycleway",
         path="highway:(pedestrian|footway|steps|path|corridor)",
-        road="highway:(motorway|trunk|primary|secondary|tertiary|service|construction|track|unclassified|residential|.*_link)",
+        road="highway:(motorway|trunk|primary|secondary|tertiary|service|construction|track|unclassified|residential|.*_link)",  # noqa E501
         busway="highway:busway",
         tree_row="natural:tree_row",  # maybe merge with node?
     )

maploc/osm/reader.py

@@ -6,8 +6,8 @@ from dataclasses import dataclass, field
 from pathlib import Path
 from typing import Any, Dict, List, Optional
 
-from lxml import etree
 import numpy as np
+from lxml import etree
 
 from ..utils.geo import BoundaryBox, Projection
 

maploc/osm/tiling.py

@@ -6,8 +6,8 @@ from pathlib import Path
 from typing import Dict, List, Optional, Tuple
 
 import numpy as np
-from PIL import Image
 import rtree
+from PIL import Image
 
 from ..utils.geo import BoundaryBox, Projection
 from .data import MapData

maploc/osm/viz.py

@@ -3,8 +3,8 @@
 import matplotlib as mpl
 import matplotlib.pyplot as plt
 import numpy as np
-import plotly.graph_objects as go
 import PIL.Image
+import plotly.graph_objects as go
 
 from ..utils.viz_2d import add_text
 from .parser import Groups

maploc/train.py

@@ -1,8 +1,8 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 
 import os.path as osp
-from typing import Optional
 from pathlib import Path
+from typing import Optional
 
 import hydra
 import pytorch_lightning as pl
@@ -10,7 +10,7 @@ import torch
 from omegaconf import DictConfig, OmegaConf
 from pytorch_lightning.utilities import rank_zero_only
 
-from . import logger, pl_logger, EXPERIMENTS_PATH
+from . import EXPERIMENTS_PATH, logger, pl_logger
 from .data import modules as data_modules
 from .module import GenericModule
 

maploc/utils/exif.py

@@ -1,9 +1,10 @@
 """Copied from opensfm.exif to minimize hard dependencies."""
-from pathlib import Path
-import json
+
 import datetime
+import json
 import logging
-from codecs import encode, decode
+from codecs import decode, encode
+from pathlib import Path
 from typing import Any, Dict, Optional, Tuple
 
 import exifread
@@ -209,7 +210,7 @@ class EXIF:
         orientation = 1
         if "Image Orientation" in self.tags:
             value = self.tags.get("Image Orientation").values[0]
-            if type(value) == int and value != 0:
+            if isinstance(value, int) and value != 0:
                 orientation = value
         return orientation
 
@@ -243,7 +244,8 @@ class EXIF:
             else:
                 altitude = None
 
-            # Check if GPSAltitudeRef is equal to 1, which means GPSAltitude should be negative, reference: http://www.exif.org/Exif2-2.PDF#page=53
+            # Check if GPSAltitudeRef is equal to 1, which means GPSAltitude
+            # should be negative, reference: http://www.exif.org/Exif2-2.PDF#page=53
             if (
                 "GPS GPSAltitudeRef" in self.tags
                 and self.tags["GPS GPSAltitudeRef"].values[0] == 1

maploc/utils/geo.py

@@ -5,7 +5,6 @@ from typing import Union
 import numpy as np
 import torch
 
-from .. import logger
 from .geo_opensfm import TopocentricConverter
 
 

maploc/utils/geo_opensfm.py

@@ -1,7 +1,9 @@
 """Copied from opensfm.geo to minimize hard dependencies."""
+
+from typing import Tuple
+
 import numpy as np
 from numpy import ndarray
-from typing import Tuple
 
 WGS84_a = 6378137.0
 WGS84_b = 6356752.314245

maploc/utils/io.py

@@ -1,12 +1,12 @@
 # Copyright (c) Meta Platforms, Inc. and affiliates.
 
 import json
-import requests
 import shutil
 from pathlib import Path
 
 import cv2
 import numpy as np
+import requests
 import torch
 from tqdm.auto import tqdm
 

requirements/dev.txt

@@ -0,0 +1,3 @@
+black[jupyter]==24.2.0
+isort
+flake8

setup.py

@@ -1,11 +1,11 @@
-from setuptools import setup, find_packages
+from setuptools import find_packages, setup
 
 setup(
-    name='maploc',
-    version='0.0.0',
+    name="maploc",
+    version="0.0.0",
     packages=find_packages(),
-    python_requires='>=3.8',
-    author='Paul-Edouard Sarlin',
+    python_requires=">=3.8",
+    author="Paul-Edouard Sarlin",
     long_description_content_type="text/markdown",
     classifiers=[
         "Programming Language :: Python :: 3",