Remove unused type error suppressions - mapillary

Summary:
This diff was automatically generated by the Pyre per-target upgrade tool.

It removes `# pyre-fixme` or `pyrefly: ignore` comments that are no longer needed because the underlying type errors have been resolved.
Note that it will also aim to ensure type checking runs cleanly, and will add suppressions to existing type errors.

#pyreupgrade

Differential Revision: D116358864

fbshipit-source-id: aeb900f1c8546a7df8110f329c8a938dfcade2b8

Author: generatedunixname89002005307016

annotation_gui_gcp/run_ba.py

@@ -287,16 +287,13 @@ def bundle_with_fixed_images(
     for shot in reconstruction.shots.values():
         r = shot.pose.rotation
         t = shot.pose.translation
-        # pyrefly: ignore [missing-attribute]
         ba.add_shot(shot.id, shot.camera.id, r, t, shot.id in fixed_images)
 
     for point in reconstruction.points.values():
         ba.add_point(point.id, point.coordinates, False)
         ba.add_point_prior(
-            # pyre-ignore[6]: Pyre doesn't recognize numpy.ndarray as numpy.typing.ArrayLike
             point.id,
             point.coordinates,
-            # pyre-ignore[6]: Pyre doesn't recognize numpy.ndarray as numpy.typing.ArrayLike
             np.array([100.0, 100.0, 100.0]),
             False,
         )
@@ -340,7 +337,6 @@ def bundle_with_fixed_images(
         orec._get_camera_from_bundle(ba, camera)
 
     for shot in reconstruction.shots.values():
-        # pyrefly: ignore [missing-attribute]
         s = ba.get_shot(shot.id)
         shot.pose.rotation = [s.r[0], s.r[1], s.r[2]]
         shot.pose.translation = [s.t[0], s.t[1], s.t[2]]
@@ -544,7 +540,6 @@ def align_3d_annotations_to_reconstruction(
     except ValueError:
         logger.warning(f"Could not align reconstruction with {model_id}")
 
-    # pyrefly: ignore [unbound-name]
     return gcp_reprojections, {"s": s.tolist(), "A": A.tolist(), "b": b.tolist()}
 
 

bin/import_colmap.py

@@ -62,35 +62,27 @@ def compute_and_save_undistorted_reconstruction(
     reconstruction, tracks_manager, data, udata
 ):
     image_format = data.config["undistorted_image_format"]
-    # pyrefly: ignore [missing-attribute]
     urec = types.Reconstruction()
-    # pyrefly: ignore [missing-attribute]
     utracks_manager = pymap.TracksManager()
     undistorted_shots = []
     for shot in reconstruction.shots.values():
         if shot.camera.projection_type == "perspective":
-            # pyrefly: ignore [missing-attribute]
             ucamera = osfm_u.perspective_camera_from_perspective(shot.camera)
         elif shot.camera.projection_type == "brown":
-            # pyrefly: ignore [missing-attribute]
             ucamera = osfm_u.perspective_camera_from_brown(shot.camera)
         elif shot.camera.projection_type == "fisheye":
-            # pyrefly: ignore [missing-attribute]
             ucamera = osfm_u.perspective_camera_from_fisheye(shot.camera)
         else:
             raise ValueError
         urec.add_camera(ucamera)
-        # pyrefly: ignore [missing-attribute]
         ushot = osfm_u.get_shot_with_different_camera(urec, shot, image_format)
         if tracks_manager:
-            # pyrefly: ignore [missing-attribute]
             osfm_u.add_subshot_tracks(tracks_manager, utracks_manager, shot, ushot)
         undistorted_shots.append(ushot)
 
         image = data.load_image(shot.id, unchanged=True, anydepth=True)
         if image is not None:
             max_size = data.config["undistorted_image_max_size"]
-            # pyrefly: ignore [missing-attribute]
             undistorted = osfm_u.undistort_image(
                 shot, undistorted_shots, image, cv2.INTER_AREA, max_size
             )
@@ -130,7 +122,6 @@ def import_cameras_images(db, data):
     cameras = {}
     for row in cursor:
         camera_id, camera_model_id, width, height, prior_focal, params = row
-        # pyrefly: ignore [no-matching-overload]
         params = np.fromstring(params, dtype=np.double)
         cam = cam_from_colmap_params(
             camera_model_id, width, height, params, prior_focal
@@ -197,15 +188,13 @@ def import_features(db, data, image_map, camera_map):
         filename, camera_id = image_map[image_id]
         cam = camera_map[camera_id]
 
-        # pyrefly: ignore [no-matching-overload]
         arr = np.fromstring(arr, dtype=np.float32).reshape((n_rows, n_cols))
 
         rgb = data.load_image(filename).astype(np.float32)
         xc = np.clip(arr[:, 1].astype(int), 0, rgb.shape[0] - 1)
         yc = np.clip(arr[:, 0].astype(int), 0, rgb.shape[1] - 1)
         colors[image_id] = rgb[xc, yc, :]
 
-        # pyrefly: ignore [missing-attribute]
         arr[:, :2] = features.normalized_image_coordinates(
             arr[:, :2], cam.width, cam.height
         )
@@ -227,10 +216,8 @@ def import_features(db, data, image_map, camera_map):
     for row in cursor:
         image_id, n_rows, n_cols, arr = row
         filename, _ = image_map[image_id]
-        # pyrefly: ignore [no-matching-overload]
         descriptors = np.fromstring(arr, dtype=np.uint8).reshape((n_rows, n_cols))
         kp = keypoints[image_id]
-        # pyrefly: ignore [missing-attribute]
         features_data = features.FeaturesData(kp, descriptors, colors[image_id], None)
         data.save_features(filename, features_data)
 
@@ -249,7 +236,6 @@ def import_matches(db, data, image_map):
 
     for row in cursor:
         pair_id = row[0]
-        # pyrefly: ignore [no-matching-overload]
         inlier_matches = np.fromstring(row[1], dtype=np.uint32).reshape(-1, 2)
         image_id1, image_id2 = pair_id_to_image_ids(pair_id)
         image_name1 = image_map[image_id1][0]
@@ -294,13 +280,10 @@ def cam_from_colmap_params(camera_model_id, width, height, params, prior_focal=1
     normalizer = max(width, height)
     focal = params[0] / normalizer if prior_focal else 0.85
     if projection_type == "perspective":
-        # pyrefly: ignore [missing-attribute]
         cam = pygeometry.Camera.create_perspective(focal, params[3], params[4])
     elif projection_type == "pinhole":
-        # pyrefly: ignore [missing-attribute]
         cam = pygeometry.Camera.create_perspective(focal, 0, 0)
     else:  # projection_type == 'fisheye'
-        # pyrefly: ignore [missing-attribute]
         cam = pygeometry.Camera.create_fisheye(focal, params[3], 0)
     cam.width = width
     cam.height = height
@@ -388,7 +371,6 @@ def import_images_reconstruction(path_images, keypoints, rec):
     Read images.bin, building shots and tracks graph
     """
     logger.info("Importing images from {}".format(path_images))
-    # pyrefly: ignore [missing-attribute]
     tracks_manager = pymap.TracksManager()
     image_ix_to_shot_id = {}
     with open(path_images, "rb") as f:
@@ -413,7 +395,6 @@ def import_images_reconstruction(path_images, keypoints, rec):
             q /= np.linalg.norm(q)
             t = np.array([t0, t1, t2])
 
-            # pyrefly: ignore [missing-attribute]
             pose = pygeometry.Pose(rotation=quaternion_to_angle_axis(q), translation=t)
             shot = rec.create_shot(filename, str(camera_id), pose)
             image_ix_to_shot_id[image_ix] = shot.id
@@ -426,7 +407,6 @@ def import_images_reconstruction(path_images, keypoints, rec):
                 if point3d_id != np.iinfo(np.uint64).max:
                     kp = keypoints[image_id][point2d_ix]
                     r, g, b = rec.points[str(point3d_id)].color
-                    # pyrefly: ignore [missing-attribute]
                     obs = pymap.Observation(
                         x,
                         y,
@@ -492,7 +472,6 @@ def project_pointcloud_save_depth(udata, urec, points, shot_id, max_sz):
 
     points_2d = shot.project_many(points)
 
-    # pyrefly: ignore [missing-attribute]
     pixel_coords = features.denormalized_image_coordinates(points_2d, w, h).astype(int)
     # Filter out points that fall out of the image
     # <<< aren't we supposed to have points that are visible from this image only??!?!
@@ -570,7 +549,6 @@ def main():
     ):
         os.symlink(p_db.parent.parent / "config.yaml", export_folder / "config.yaml")
 
-    # pyrefly: ignore [missing-attribute]
     data = dataset.DataSet(export_folder)
     db = sqlite3.connect(p_db.as_posix())
     camera_map, image_map = import_cameras_images(db, data)
@@ -588,7 +566,6 @@ def main():
     rec_points = p_db.parent / "points3D.bin"
     rec_images = p_db.parent / "images.bin"
     if rec_cameras.exists() and rec_images.exists() and rec_points.exists():
-        # pyrefly: ignore [missing-attribute]
         reconstruction = types.Reconstruction()
         import_cameras_reconstruction(rec_cameras, reconstruction)
         import_points_reconstruction(rec_points, reconstruction)
@@ -600,7 +577,6 @@ def main():
         data.save_tracks_manager(tracks_manager)
 
         # Save undistorted reconstruction as well
-        # pyrefly: ignore [missing-attribute]
         udata = dataset.UndistortedDataSet(data, io_handler=data.io_handler)
         urec = compute_and_save_undistorted_reconstruction(
             reconstruction, tracks_manager, data, udata
@@ -612,7 +588,6 @@ def main():
             rec_cameras = p_db.parent / "dense/sparse/cameras.bin"
             rec_images = p_db.parent / "dense/sparse/images.bin"
             rec_points = p_db.parent / "points3D.bin"
-            # pyrefly: ignore [missing-attribute]
             reconstruction = types.Reconstruction()
             import_cameras_reconstruction(rec_cameras, reconstruction)
             import_points_reconstruction(rec_points, reconstruction)

bin/plot_matches.py

@@ -55,7 +55,6 @@ def plot_graph(data) -> None:
         o2 = np.array(
             reference.to_topocentric(gps2["latitude"], gps2["longitude"], 0)[:2]
         )
-        # pyrefly: ignore [no-matching-overload]
         c = max(0, min(1.0, 1 - (edge - lowest) / (highest - lowest)))
         pl.plot([o1[0], o2[0]], [o1[1], o2[1]], linestyle="-", color=cmap(c))
 

opensfm/actions/export_colmap.py

@@ -467,15 +467,12 @@ def export_matches(
             pair_matches = matches_per_pair.setdefault(pair_key, {})
             for match in image_matches:
                 if image1 < image2:
-                    # pyrefly: ignore [missing-attribute]
                     pair_matches.update({(match[0], match[1]): True})
                 else:
-                    # pyrefly: ignore [missing-attribute]
                     pair_matches.update({(match[1], match[0]): True})
 
     data.config["robust_matching_threshold"] = 8
     for pair, matches in matches_per_pair.items():
-        # pyrefly: ignore [not-iterable]
         matches_numpy = np.array([np.array([m[0], m[1]]) for m in matches])
         if len(matches_numpy) < 10:
             continue

opensfm/actions/export_geocoords.py

@@ -150,9 +150,7 @@ def _transform_dense_point_cloud(
                     fout.write(line)
                 else:
                     x, y, z, nx, ny, nz, red, green, blue = line.split()
-                    # pyre-fixme[6]: For 2nd argument expected `Union[Sequence[Sequen...
                     x, y, z = np.dot(A, map(float, [x, y, z])) + b
-                    # pyre-fixme[6]: For 2nd argument expected `Union[Sequence[Sequen...
                     nx, ny, nz = np.dot(A, map(float, [nx, ny, nz]))
                     fout.write(
                         "{} {} {} {} {} {} {} {} {}\n".format(

opensfm/actions/extend_reconstruction.py

@@ -28,7 +28,7 @@ def run_dataset(data: DataSetBase, input: Optional[str], output: Optional[str])
         gcp,
     )
     rec_report["num_remaining_images"] = len(remaining_images)
-    # pyrefly: ignore [no-matching-overload, unsupported-operation]
+    # pyrefly: ignore [unsupported-operation]
     report["not_reconstructed_images"] = list(remaining_images)
     data.save_reconstruction([rec], output)
     data.save_report(io.json_dumps(report), "reconstruction.json")

opensfm/dataset.py

@@ -355,7 +355,6 @@ def load_matches(self, image: str) -> Dict[str, NDArray]:
         class MatchingUnpickler(pickle.Unpickler):
             # Handle both numpy <2.0 (np.core) and numpy >=2.0 (np._core)
             _multiarray: ModuleType = (
-                # pyrefly: ignore [missing-attribute]
                 np.core.multiarray if hasattr(np, "core") else np._core.multiarray
             )
             modules_map: dict[str, ModuleType] = {

opensfm/feature_loading.py

@@ -136,9 +136,7 @@ def _add_segmentation_in_descriptor(
         if segmentation is None:
             return features
 
-        # pyrefly: ignore [no-matching-overload]
         desc_augmented = np.concatenate(
-            # pyre-fixme[6]: For 1st argument expected `Union[_SupportsArray[dtype[ty...
             (
                 features.descriptors,
                 (np.array([segmentation]).T).astype(np.float32),

opensfm/features_processing.py

@@ -249,7 +249,6 @@ def bake_segmentation(
             new_width=new_width,
             new_height=new_height,
         ).astype(int)
-        # pyre-fixme[6]: For 2nd argument expected `None` but got
         #  `ndarray[typing.Any, typing.Any]`.
         panoptic_data[i] = p_data[ps[:, 1], ps[:, 0]]
     # pyrefly: ignore [bad-return]

opensfm/io.py

@@ -713,7 +713,6 @@ def camera_from_vector(
     elif projection_type == "brown":
         fx, fy, cx, cy, k1, k2, p1, p2, k3 = parameters
         camera = pygeometry.Camera.create_brown(
-            # pyre-fixme[6]: opensfm pybind / numpy stubs gap — runtime ok.
             fx,
             fy / fx,
             # pyre-fixme[6]: opensfm pybind / numpy stubs gap — runtime ok.
@@ -727,7 +726,6 @@ def camera_from_vector(
     elif projection_type == "fisheye_opencv":
         fx, fy, cx, cy, k1, k2, k3, k4 = parameters
         camera = pygeometry.Camera.create_fisheye_opencv(
-            # pyre-fixme[6]: opensfm pybind / numpy stubs gap — runtime ok.
             fx,
             fy / fx,
             # pyre-fixme[6]: opensfm pybind / numpy stubs gap — runtime ok.
@@ -738,7 +736,6 @@ def camera_from_vector(
     elif projection_type == "fisheye62":
         fx, fy, cx, cy, k1, k2, k3, k4, k5, k6, p1, p2 = parameters
         camera = pygeometry.Camera.create_fisheye62(
-            # pyre-fixme[6]: opensfm pybind / numpy stubs gap — runtime ok.
             fx,
             fy / fx,
             # pyre-fixme[6]: opensfm pybind / numpy stubs gap — runtime ok.
@@ -759,7 +756,6 @@ def camera_from_vector(
     elif projection_type == "radial":
         fx, fy, cx, cy, k1, k2 = parameters
         camera = pygeometry.Camera.create_radial(
-            # pyre-fixme[6]: opensfm pybind / numpy stubs gap — runtime ok.
             fx,
             fy / fx,
             # pyre-fixme[6]: opensfm pybind / numpy stubs gap — runtime ok.
@@ -770,7 +766,6 @@ def camera_from_vector(
     elif projection_type == "simple_radial":
         fx, fy, cx, cy, k1 = parameters
         camera = pygeometry.Camera.create_simple_radial(
-            # pyre-fixme[6]: opensfm pybind / numpy stubs gap — runtime ok.
             fx,
             fy / fx,
             # pyre-fixme[6]: opensfm pybind / numpy stubs gap — runtime ok.