Fix linting for UP030 and B006 (#92)

* fix B006. * fix UP030. * fix UP030.
cvg · Nov 18, 2024 · a7bcac8 · a7bcac8
1 parent 3d3c5b5
commit a7bcac8
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Showing 15 changed files with 60 additions and 36 deletions.
diff --git a/limap/features/models/base_model.py b/limap/features/models/base_model.py
@@ -42,8 +42,10 @@ class BaseModel(nn.Module, metaclass=ABCMeta):
     required_data_keys = []
     strict_conf = True
 
-    def __init__(self, conf={}):
+    def __init__(self, conf=None):
         """Perform some logic and call the _init method of the child model."""
+        if conf is None:
+            conf = {}
         super().__init__()
         default_conf = OmegaConf.merge(
             OmegaConf.create(self.base_default_conf),

diff --git a/limap/line2d/LineTR/line_process.py b/limap/line2d/LineTR/line_process.py
@@ -287,7 +287,9 @@ def change_cv2_T_np(klines_cv):
     return {"klines": klines, "length_klines": length, "angles": angles}
 
 
-def preprocess(klines_cv, image_shape, pred_superpoint, mask=None, conf={}):
+def preprocess(klines_cv, image_shape, pred_superpoint, mask=None, conf=None):
+    if conf is None:
+        conf = {}
     default_conf = {
         "min_length": 16,
         "max_sublines": 256,

diff --git a/limap/line2d/SOLD2/model/line_matcher.py b/limap/line2d/SOLD2/model/line_matcher.py
@@ -31,9 +31,11 @@ def __init__(
         line_detector_cfg,
         line_matcher_cfg,
         multiscale=False,
-        scales=[1.0, 2.0],
+        scales=None,
     ):
         # Get loss weights if dynamic weighting
+        if scales is None:
+            scales = [1.0, 2.0]
         _, loss_weights = get_loss_and_weights(model_cfg, device)
         self.device = device
 
@@ -162,10 +164,12 @@ def multiscale_line_detection(
         valid_mask=None,
         desc_only=False,
         profile=False,
-        scales=[1.0, 2.0],
+        scales=None,
         aggregation="mean",
     ):
         # Restrict input_image to 4D torch tensor
+        if scales is None:
+            scales = [1.0, 2.0]
         if (not len(input_image.shape) == 4) or (
             not isinstance(input_image, torch.Tensor)
         ):
@@ -291,8 +295,10 @@ def multiscale_line_detection(
 
         return outputs
 
-    def __call__(self, images, valid_masks=[None, None], profile=False):
+    def __call__(self, images, valid_masks=None, profile=False):
         # Line detection and descriptor inference on both images
+        if valid_masks is None:
+            valid_masks = [None, None]
         if self.multiscale:
             forward_outputs = [
                 self.multiscale_line_detection(

diff --git a/limap/runners/functions.py b/limap/runners/functions.py
@@ -18,11 +18,11 @@ def setup(cfg):
         folder_load = folder_save
     cfg["dir_save"] = folder_save
     cfg["dir_load"] = folder_load
-    print("[LOG] Output dir: {0}".format(cfg["dir_save"]))
-    print("[LOG] Loading dir: {0}".format(cfg["dir_load"]))
+    print("[LOG] Output dir: {}".format(cfg["dir_save"]))
+    print("[LOG] Loading dir: {}".format(cfg["dir_load"]))
     if "weight_path" in cfg and cfg["weight_path"] is not None:
         cfg["weight_path"] = os.path.expanduser(cfg["weight_path"])
-        print("[LOG] weight dir: {0}".format(cfg["weight_path"]))
+        print("[LOG] weight dir: {}".format(cfg["weight_path"]))
     return cfg
 
 
@@ -192,15 +192,15 @@ def compute_2d_segs(cfg, imagecols, compute_descinfo=True):
     weight_path = cfg.get("weight_path", None)
     if "extractor" in cfg["line2d"]:
         print(
-            "[LOG] Start 2D line detection and description (detector = {0}, extractor = {1}, n_images = {2})...".format(
+            "[LOG] Start 2D line detection and description (detector = {}, extractor = {}, n_images = {})...".format(
                 cfg["line2d"]["detector"]["method"],
                 cfg["line2d"]["extractor"]["method"],
                 imagecols.NumImages(),
             )
         )
     else:
         print(
-            "[LOG] Start 2D line detection and description (detector = {0}, n_images = {1})...".format(
+            "[LOG] Start 2D line detection and description (detector = {}, n_images = {})...".format(
                 cfg["line2d"]["detector"]["method"], imagecols.NumImages()
             )
         )
@@ -282,7 +282,7 @@ def compute_matches(cfg, descinfo_folder, image_ids, neighbors):
     """
     weight_path = cfg.get("weight_path", None)
     print(
-        "[LOG] Start matching 2D lines... (extractor = {0}, matcher = {1}, n_images = {2}, n_neighbors = {3})".format(
+        "[LOG] Start matching 2D lines... (extractor = {}, matcher = {}, n_images = {}, n_neighbors = {})".format(
             cfg["line2d"]["extractor"]["method"],
             cfg["line2d"]["matcher"]["method"],
             len(image_ids),
@@ -294,7 +294,7 @@ def compute_matches(cfg, descinfo_folder, image_ids, neighbors):
     basedir = os.path.join(
         "line_matchings",
         cfg["line2d"]["detector"]["method"],
-        "feats_{0}".format(cfg["line2d"]["extractor"]["method"]),
+        "feats_{}".format(cfg["line2d"]["extractor"]["method"]),
     )
     extractor = limap.line2d.get_extractor(
         cfg["line2d"]["extractor"], weight_path=weight_path
@@ -333,7 +333,7 @@ def compute_exhausive_matches(cfg, descinfo_folder, image_ids):
         matches_folder (str): path to store the computed matches
     """
     print(
-        "[LOG] Start exhausive matching 2D lines... (extractor = {0}, matcher = {1}, n_images = {2})".format(
+        "[LOG] Start exhausive matching 2D lines... (extractor = {}, matcher = {}, n_images = {})".format(
             cfg["line2d"]["extractor"]["method"],
             cfg["line2d"]["matcher"]["method"],
             len(image_ids),
@@ -344,7 +344,7 @@ def compute_exhausive_matches(cfg, descinfo_folder, image_ids):
     basedir = os.path.join(
         "line_matchings",
         cfg["line2d"]["detector"]["method"],
-        "feats_{0}".format(cfg["line2d"]["extractor"]["method"]),
+        "feats_{}".format(cfg["line2d"]["extractor"]["method"]),
     )
     extractor = limap.line2d.get_extractor(cfg["line2d"]["extractor"])
     se_match = cfg["skip_exists"] or cfg["line2d"]["matcher"]["skip_exists"]

diff --git a/limap/runners/functions_structures.py b/limap/runners/functions_structures.py
@@ -77,8 +77,10 @@ def compute_colmap_model_with_junctions(
 
 
 def compute_2d_bipartites_from_colmap(
-    reconstruction, imagecols, all_2d_lines, cfg=dict()
+    reconstruction, imagecols, all_2d_lines, cfg=None
 ):
+    if cfg is None:
+        cfg = dict()
     all_bpt2ds = {}
     cfg_bpt2d = _structures.PL_Bipartite2dConfig(cfg)
     colmap_cameras, colmap_images, colmap_points = (

diff --git a/limap/runners/line_fitnmerge.py b/limap/runners/line_fitnmerge.py
@@ -163,7 +163,7 @@ def line_fitnmerge(cfg, imagecols, depths, neighbors=None, ranges=None):
     ##########################################################
     # [C] fit 3d segments
     ##########################################################
-    fname_fit_segs = "{0}_fit_segs.npy".format(
+    fname_fit_segs = "{}_fit_segs.npy".format(
         cfg["line2d"]["detector"]["method"]
     )
     if (not cfg["load_fit"]) and (
@@ -266,7 +266,7 @@ def line_fitnmerge(cfg, imagecols, depths, neighbors=None, ranges=None):
     limapio.save_obj(
         os.path.join(
             cfg["dir_save"],
-            "fitnmerge_lines_nv{0}.obj".format(cfg["n_visible_views"]),
+            "fitnmerge_lines_nv{}.obj".format(cfg["n_visible_views"]),
         ),
         VisTrack.get_lines_np(n_visible_views=cfg["n_visible_views"]),
     )
@@ -324,7 +324,7 @@ def line_fitting_with_3Dpoints(
     ##########################################################
     # [B] fit 3d segments
     ##########################################################
-    fname_fit_segs = "{0}_fit_segs.npy".format(
+    fname_fit_segs = "{}_fit_segs.npy".format(
         cfg["line2d"]["detector"]["method"]
     )
     if (not cfg["load_fit"]) and (

diff --git a/limap/runners/line_triangulation.py b/limap/runners/line_triangulation.py
@@ -231,7 +231,7 @@ def line_triangulation(cfg, imagecols, neighbors=None, ranges=None):
     limapio.save_obj(
         os.path.join(
             cfg["dir_save"],
-            "triangulated_lines_nv{0}.obj".format(cfg["n_visible_views"]),
+            "triangulated_lines_nv{}.obj".format(cfg["n_visible_views"]),
         ),
         VisTrack.get_lines_np(n_visible_views=cfg["n_visible_views"]),
     )

diff --git a/limap/visualize/vis_lines.py b/limap/visualize/vis_lines.py
@@ -26,12 +26,14 @@ def pyvista_vis_3d_lines(
 def open3d_add_points(
     w,
     points,
-    color=[0.0, 0.0, 0.0],
+    color=None,
     psize=1.0,
     name="pcd",
     ranges=None,
     scale=1.0,
 ):
+    if color is None:
+        color = [0.0, 0.0, 0.0]
     if np.array(points).shape[0] == 0:
         return w
     import open3d as o3d
@@ -54,11 +56,11 @@ def open3d_add_points(
     return w
 
 
-def open3d_get_line_set(
-    lines, color=[0.0, 0.0, 0.0], width=2, ranges=None, scale=1.0
-):
+def open3d_get_line_set(lines, color=None, width=2, ranges=None, scale=1.0):
     import open3d as o3d
 
+    if color is None:
+        color = [0.0, 0.0, 0.0]
     o3d_points, o3d_lines, o3d_colors = [], [], []
     counter = 0
     for line in lines:
@@ -79,14 +81,16 @@ def open3d_get_line_set(
 def open3d_add_line_set(
     w,
     lines,
-    color=[0.0, 0.0, 0.0],
+    color=None,
     width=2,
     name="lineset",
     ranges=None,
     scale=1.0,
 ):
     import open3d as o3d
 
+    if color is None:
+        color = [0.0, 0.0, 0.0]
     o3d_points, o3d_lines, o3d_colors = [], [], []
     counter = 0
     for line in lines:
@@ -110,7 +114,7 @@ def open3d_add_line_set(
 
 def open3d_get_cameras(
     imagecols,
-    color=[1.0, 0.0, 0.0],
+    color=None,
     ranges=None,
     scale_cam_geometry=1.0,
     scale=1.0,
@@ -119,6 +123,8 @@ def open3d_get_cameras(
 
     import open3d as o3d
 
+    if color is None:
+        color = [1.0, 0.0, 0.0]
     cameras = o3d.geometry.LineSet()
 
     camera_lines = {}
@@ -150,7 +156,7 @@ def open3d_get_cameras(
 def open3d_add_cameras(
     w,
     imagecols,
-    color=[1.0, 0.0, 0.0],
+    color=None,
     ranges=None,
     scale_cam_geometry=1.0,
     scale=1.0,
@@ -159,6 +165,8 @@ def open3d_add_cameras(
 
     import open3d as o3d
 
+    if color is None:
+        color = [1.0, 0.0, 0.0]
     camera_lines = {}
     for cam_id in imagecols.get_cam_ids():
         cam = imagecols.cam(cam_id)

diff --git a/limap/visualize/vis_utils.py b/limap/visualize/vis_utils.py
@@ -317,7 +317,9 @@ def test_line_inside_ranges(line, ranges):
     return test_point_inside_ranges(line.end, ranges)
 
 
-def compute_robust_range(arr, range_robust=[0.05, 0.95], k_stretch=2.0):
+def compute_robust_range(arr, range_robust=None, k_stretch=2.0):
+    if range_robust is None:
+        range_robust = [0.05, 0.95]
     N = arr.shape[0]
     start_idx = int(round((N - 1) * range_robust[0]))
     end_idx = int(round((N - 1) * range_robust[1]))
@@ -329,7 +331,9 @@ def compute_robust_range(arr, range_robust=[0.05, 0.95], k_stretch=2.0):
     return start_stretched, end_stretched
 
 
-def compute_robust_range_lines(lines, range_robust=[0.05, 0.95], k_stretch=2.0):
+def compute_robust_range_lines(lines, range_robust=None, k_stretch=2.0):
+    if range_robust is None:
+        range_robust = [0.05, 0.95]
     lines_array = np.array([line.as_array() for line in lines])
     x_array = lines_array.reshape(-1, 3)[:, 0]
     y_array = lines_array.reshape(-1, 3)[:, 1]

diff --git a/ruff.toml b/ruff.toml
@@ -15,7 +15,7 @@ select = [
     # isort
     "I",
 ]
-ignore = ["E501", "F401", "F403", "UP030", "B006", "B008"]
+ignore = ["E501", "F401", "F403", "B008"]
 
 [lint.per-file-ignores]
 "limap/line2d/L2D2/RAL_net_cov.py" = ["SIM"]

diff --git a/runners/eth3d/fitnmerge.py b/runners/eth3d/fitnmerge.py
@@ -63,7 +63,7 @@ def parse_config():
         "precomputed",
         "eth3d",
         cfg["reso_type"],
-        "{0}_cam{1}".format(cfg["scene_id"], cfg["cam_id"]),
+        "{}_cam{}".format(cfg["scene_id"], cfg["cam_id"]),
     )
     return cfg
 

diff --git a/runners/eth3d/triangulation.py b/runners/eth3d/triangulation.py
@@ -64,7 +64,7 @@ def parse_config():
         "precomputed",
         "eth3d",
         cfg["reso_type"],
-        "{0}_cam{1}".format(cfg["scene_id"], cfg["cam_id"]),
+        "{}_cam{}".format(cfg["scene_id"], cfg["cam_id"]),
     )
     return cfg
 

diff --git a/runners/rome16k/triangulation.py b/runners/rome16k/triangulation.py
@@ -32,7 +32,7 @@ def run_rome16k_triangulation(cfg, bundler_path, list_path, model_path):
             if comp_id == cfg["comp_id"]:
                 valid_image_ids.append(img_id)
         print(
-            "[LOG] Get image subset from component {0}: n_images = {1}".format(
+            "[LOG] Get image subset from component {}: n_images = {}".format(
                 cfg["comp_id"], len(valid_image_ids)
             )
         )

diff --git a/scripts/tnt_align.py b/scripts/tnt_align.py
@@ -80,17 +80,17 @@ def main():
         # colmap align
         cmd_list = []
         basepath = os.path.join(colmap_output_path, scene_id, "dense")
-        cmd = "mkdir -p {0}".format(os.path.join(basepath, "aligned"))
+        cmd = "mkdir -p {}".format(os.path.join(basepath, "aligned"))
         cmd_list.append(cmd)
-        cmd = "colmap model_aligner --input_path {0} --output_path {1} --ref_images_path {2} --robust_alignment 1 --robust_alignment_max_error {3} --transform_path {4} --ref_is_gps false".format(
+        cmd = "colmap model_aligner --input_path {} --output_path {} --ref_images_path {} --robust_alignment 1 --robust_alignment_max_error {} --transform_path {} --ref_is_gps false".format(
             os.path.join(basepath, "sparse"),
             os.path.join(basepath, "aligned"),
             os.path.join(input_meta_path, scene_id, "geo_positions.txt"),
             MAX_ERROR,
             os.path.join(basepath, "transform.txt"),
         )
         cmd_list.append(cmd)
-        cmd = "colmap model_converter --input_path {0} --output_path {1} --output_type PLY".format(
+        cmd = "colmap model_converter --input_path {} --output_path {} --output_type PLY".format(
             os.path.join(basepath, "aligned"),
             os.path.join(basepath, "aligned/points.ply"),
         )

diff --git a/scripts/tnt_colmap_runner.py b/scripts/tnt_colmap_runner.py
@@ -30,7 +30,7 @@
     cmd = f"colmap mapper --database_path {database_path} --image_path {input_folder} --output_path {sparse_folder}"
     print(cmd)
     os.system(cmd)
-    cmd = "colmap image_undistorter --image_path {0} --input_path {1} --output_path {2} --output_type COLMAP".format(
+    cmd = "colmap image_undistorter --image_path {} --input_path {} --output_path {} --output_type COLMAP".format(
         input_folder, os.path.join(sparse_folder, "0"), dense_folder
     )
     print(cmd)