Merge pull request #234 from benjaminrwilson/autoflake

Autoflake the repository.

argoverse/data_loading/frame_label_accumulator.py

@@ -5,7 +5,6 @@
 import glob
 import logging
 import os
-import pickle as pkl
 import tempfile
 from pathlib import Path
 from typing import Dict, List, Optional, Tuple
@@ -18,9 +17,7 @@
 from argoverse.data_loading.synchronization_database import SynchronizationDB
 from argoverse.data_loading.trajectory_loader import TrajectoryLabel, load_json_track_labels
 from argoverse.utils.json_utils import read_json_file
-from argoverse.utils.pkl_utils import load_pkl_dictionary, save_pkl_dictionary
-from argoverse.utils.se3 import SE3
-from argoverse.utils.transform import quat2rotmat
+from argoverse.utils.pkl_utils import save_pkl_dictionary
 
 logger = logging.getLogger(__name__)
 
@@ -65,7 +62,8 @@ def __init__(
         log_egopose_dict_fpath = f"{tmp_dir}/log_egopose_dict_{experiment_prefix}.pkl"
         log_timestamp_dict_fpath = f"{tmp_dir}/log_timestamp_dict_{experiment_prefix}.pkl"
 
-        coordinate_system = "map_world_fr"
+        # coordinate system is the map world frame
+
         self.per_city_traj_dict: Dict[str, List[Tuple[np.ndarray, str]]] = {
             "MIA": [],
             "PIT": [],

argoverse/data_loading/object_label_record.py

@@ -2,12 +2,10 @@
 
 # <Copyright 2019, Argo AI, LLC. Released under the MIT license.>
 
-import copy
 import json
 import os
-from typing import Any, Dict, Iterable, List, Optional, Tuple
+from typing import Any, Dict, List, Optional, Tuple
 
-import cv2
 import numpy as np
 
 from argoverse.utils.calibration import CameraConfig, proj_cam_to_uv

argoverse/data_loading/simple_track_dataloader.py

@@ -1,17 +1,13 @@
 # <Copyright 2019, Argo AI, LLC. Released under the MIT license.>
 
 import glob
-import sys
 from pathlib import Path
 from typing import Any, List, Mapping, Optional
 
-import numpy as np
-
 from argoverse.data_loading.pose_loader import get_city_SE3_egovehicle_at_sensor_t, read_city_name
 from argoverse.data_loading.synchronization_database import SynchronizationDB
 from argoverse.utils.json_utils import read_json_file
 from argoverse.utils.se3 import SE3
-from argoverse.utils.transform import quat2rotmat
 
 
 class SimpleArgoverseTrackingDataLoader:

argoverse/data_loading/synchronization_database.py

@@ -5,14 +5,13 @@
 import glob
 import logging
 from pathlib import Path
-from typing import Dict, Iterable, List, Optional, Tuple, cast
+from typing import Dict, Iterable, Optional, Tuple, cast
 
 import numpy as np
 from typing_extensions import Final
 
 from argoverse.sensor_dataset_config import ArgoverseConfig
 from argoverse.utils.camera_stats import RING_CAMERA_LIST, STEREO_CAMERA_LIST
-from argoverse.utils.json_utils import read_json_file
 from argoverse.utils.metric_time import TimeUnit, to_metric_time
 
 logger = logging.getLogger(__name__)

argoverse/data_loading/trajectory_loader.py

@@ -6,7 +6,6 @@
 import glob
 import json
 import logging
-import sys
 from pathlib import Path
 from typing import List, NamedTuple
 

argoverse/data_loading/vector_map_loader.py

@@ -41,8 +41,6 @@
 
 import logging
 import os
-import pathlib
-import sys
 import xml.etree.ElementTree as ET
 from typing import Any, Dict, List, Mapping, MutableMapping, Optional, Tuple, Union, cast
 

argoverse/evaluation/competition_util.py

@@ -6,7 +6,6 @@
 import shutil
 import tempfile
 import uuid
-import zipfile
 from typing import Dict, List, Optional, Tuple, Union
 
 import h5py

argoverse/evaluation/eval_forecasting.py

@@ -3,8 +3,7 @@
 """This module evaluates the forecasted trajectories against the ground truth."""
 
 import math
-import pickle as pkl
-from typing import Dict, List, Optional, Tuple
+from typing import Dict, List, Optional
 
 import numpy as np
 

argoverse/evaluation/eval_utils.py

@@ -1,7 +1,6 @@
 # <Copyright 2019, Argo AI, LLC. Released under the MIT license.>
 """Utilities used in evaluation of performance."""
 
-import copy
 from typing import Any, Dict, List, Tuple
 
 import numpy as np

argoverse/map_representation/lane_segment.py

@@ -1,5 +1,5 @@
 # <Copyright 2019, Argo AI, LLC. Released under the MIT license.>
-from typing import List, Optional, Sequence
+from typing import List, Optional
 
 import numpy as np
 

argoverse/map_representation/map_api.py

@@ -2,7 +2,6 @@
 
 import copy
 import os
-from os import PathLike
 from pathlib import Path
 from typing import Any, Dict, Iterable, List, Mapping, Optional, Tuple, Union
 

argoverse/utils/bfs.py

@@ -2,7 +2,7 @@
 
 """Breadth-First-Search of Graphs."""
 
-from typing import Any, Collection, List, Mapping, MutableMapping, Sequence
+from typing import Any, List, Mapping, MutableMapping, Sequence
 
 
 def bfs_enumerate_paths(graph: Mapping[str, Sequence[str]], start: str, max_depth: int = 4) -> List[List[str]]:

argoverse/utils/calibration.py

@@ -11,13 +11,7 @@
 from typing_extensions import Literal
 
 from argoverse.data_loading.pose_loader import get_city_SE3_egovehicle_at_sensor_t
-from argoverse.utils.camera_stats import (
-    CAMERA_LIST,
-    RECTIFIED_STEREO_CAMERA_LIST,
-    RING_CAMERA_LIST,
-    STEREO_CAMERA_LIST,
-    get_image_dims_for_camera,
-)
+from argoverse.utils.camera_stats import CAMERA_LIST, RECTIFIED_STEREO_CAMERA_LIST, get_image_dims_for_camera
 from argoverse.utils.se3 import SE3
 from argoverse.utils.transform import quat2rotmat
 

argoverse/utils/camera_stats.py

@@ -3,7 +3,7 @@
 # <Copyright 2019, Argo AI, LLC. Released under the MIT license.>
 
 import logging
-from typing import List, Optional, Tuple
+from typing import Optional, Tuple
 
 from argoverse.sensor_dataset_config import ArgoverseConfig
 

argoverse/utils/centerline_utils.py

@@ -6,7 +6,7 @@
 
 import matplotlib.pyplot as plt
 import numpy as np
-from shapely.geometry import LinearRing, LineString, Point, Polygon
+from shapely.geometry import LinearRing, LineString, Point
 
 from argoverse.map_representation.lane_segment import LaneSegment
 
@@ -81,10 +81,7 @@ def centerline_to_polygon(
     # right centerline position depends on sign of dx and dy
     subtract_cond1 = np.logical_and(dx > 0, dy < 0)
     subtract_cond2 = np.logical_and(dx > 0, dy > 0)
-    add_cond1 = np.logical_and(dx < 0, dy < 0)
-    add_cond2 = np.logical_and(dx < 0, dy > 0)
     subtract_cond = np.logical_or(subtract_cond1, subtract_cond2)
-    add_cond = np.logical_or(add_cond1, add_cond2)
     left_centerline, right_centerline = swap_left_and_right(subtract_cond, left_centerline, right_centerline)
 
     # right centerline also depended on if we added or subtracted y
@@ -258,8 +255,6 @@ def get_nt_distance(xy: np.ndarray, centerline: np.ndarray, viz: bool = False) -
     traj_len = xy.shape[0]
     nt_distance = np.zeros((traj_len, 2))
 
-    delta_offset = 0.01
-    last = 0
     max_dist: float = -1
 
     for i in range(traj_len):

argoverse/utils/cuboid_interior.py

@@ -98,7 +98,6 @@ def filter_point_cloud_to_bbox_2D_vectorized(bbox: np.ndarray, pc_raw: np.ndarra
     P1 = np.array([bbox[0][0:2]])
     P2 = np.array([bbox[1][0:2]])
     P4 = np.array([bbox[2][0:2]])
-    P5 = np.array([])
 
     dot1 = np.matmul(U, pc_2d.transpose(1, 0))
     dot2 = np.matmul(V, pc_2d.transpose(1, 0))

argoverse/utils/cv2_plotting_utils.py

@@ -1,7 +1,7 @@
 # <Copyright 2019, Argo AI, LLC. Released under the MIT license.>
 """OpenCV plotting utility functions."""
 
-from typing import Dict, Iterable, List, Tuple, Union
+from typing import List, Tuple
 
 import cv2
 import numpy as np

argoverse/utils/frustum_clipping.py

@@ -6,8 +6,7 @@
 """
 
 import copy
-import sys
-from typing import Any, Iterable, List, Optional, Tuple
+from typing import Any, List, Optional, Tuple
 
 import numpy as np
 
@@ -232,7 +231,7 @@ def generate_frustum_planes(K: np.ndarray, camera_name: str, near_clip_dist: flo
     if img_width is None or img_height is None:
         return None
 
-    P = np.array([0.0, 0.0, 0.0])
+    # frustum starts at optical center [0,0,0]
     fx = K[0, 0]
     fy = K[1, 1]
 

argoverse/utils/interpolate.py

@@ -2,7 +2,6 @@
 
 from typing import Tuple, cast
 
-import matplotlib.pyplot as plt
 import numpy as np
 
 # For a single line segment
@@ -177,20 +176,16 @@ def interp_arc(t: int, px: np.ndarray, py: np.ndarray) -> np.ndarray:
     """
     px, py = eliminate_duplicates_2d(px, py)
 
-    # equally spaced in arclength
+    # equally spaced in arclength -- the number of points that will be uniformly interpolated
     eq_spaced_points = np.linspace(0, 1, t)
 
-    # how many points will be uniformly interpolated?
-    nt = eq_spaced_points.size
-
     # the number of points on the curve itself
     n = px.size
 
     # are px and py both vectors of the same length?
     assert px.size == py.size
 
-    pxy = np.array((px, py)).T
-    ndim = 2
+    pxy = np.array((px, py)).T  # 2d polyline
 
     # Compute the chordal arclength of each segment.
     # Compute differences between each x coord, to get the dx's

argoverse/utils/make_att_files.py

@@ -4,14 +4,12 @@
 from typing import Any, Dict, List, Tuple
 
 import cv2
-import matplotlib.pyplot as plt
 import numpy as np
 import open3d as o3d
 import scipy.interpolate as interpolate
 import torch
 import torch.nn.functional as F
 
-import argoverse
 from argoverse.data_loading.argoverse_tracking_loader import ArgoverseTrackingLoader
 from argoverse.utils.json_utils import read_json_file
 from argoverse.utils.pkl_utils import save_pkl_dictionary

argoverse/utils/make_track_label_folders.py

@@ -4,8 +4,6 @@
 import sys
 from typing import Any, Dict, List
 
-from typing_extensions import TypedDict
-
 from argoverse.utils.json_utils import read_json_file, save_json_dict
 
 root_dir = sys.argv[1]

argoverse/utils/manhattan_search.py

@@ -3,7 +3,7 @@
 """Fast search functions of nearest neighbor based on Manhattan distance."""
 
 import logging
-from typing import List, Tuple, Union
+from typing import List, Tuple
 
 import numpy as np
 

argoverse/utils/plane_visualization_utils.py

@@ -1,6 +1,5 @@
 # <Copyright 2019, Argo AI, LLC. Released under the MIT license.>
 
-import sys
 from typing import List, Optional
 
 import numpy as np
@@ -11,7 +10,6 @@
     Figure,
     draw_mayavi_line_segment,
     plot_3d_clipped_bbox_mayavi,
-    plot_bbox_3d_mayavi,
     plot_points_3D_mayavi,
 )
 

argoverse/visualization/generate_sequence_videos.py

@@ -4,18 +4,13 @@
 
 import argparse
 import os
-import re
 import shutil
 import sys
-from collections import defaultdict
 from typing import List
 
-import matplotlib.animation as anim
-import matplotlib.lines as mlines
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-from scipy.interpolate import interp1d
 
 from argoverse.map_representation.map_api import ArgoverseMap
 from argoverse.visualization.visualize_sequences import viz_sequence
@@ -49,7 +44,6 @@ def main(arguments: List[str]) -> int:
         # Get API for Argo Dataset map
         avm = ArgoverseMap()
         city_name = df["CITY_NAME"].values[0]
-        seq_lane_bbox = avm.city_halluc_bbox_table[city_name]
         seq_lane_props = avm.city_lane_centerlines_dict[city_name]
 
         x_min = min(df["X"])

argoverse/visualization/visualization_utils.py

@@ -4,15 +4,14 @@
 from collections import defaultdict
 from typing import Any, Dict, Iterable, List, Optional, Tuple, Union
 
-import cv2
 import matplotlib.pyplot as plt
 import numpy as np
 from PIL import Image
 
 from argoverse.data_loading.argoverse_tracking_loader import ArgoverseTrackingLoader
 from argoverse.data_loading.object_classes import OBJ_CLASS_MAPPING_DICT
 from argoverse.data_loading.object_label_record import ObjectLabelRecord
-from argoverse.utils.calibration import Calibration, determine_valid_cam_coords, proj_cam_to_uv
+from argoverse.utils.calibration import Calibration
 from argoverse.utils.frustum_clipping import generate_frustum_planes
 
 point_size = 0.01
@@ -208,8 +207,6 @@ def draw_box(
 def show_image_with_boxes(img: np.ndarray, objects: Iterable[ObjectLabelRecord], calib: Calibration) -> np.ndarray:
     """Show image with 2D bounding boxes."""
     img1 = np.copy(img)
-    K = calib.K
-    d = calib.d
 
     h, w = np.shape(img1)[0:2]
     planes = generate_frustum_planes(calib.K, calib.camera)
@@ -219,7 +216,6 @@ def show_image_with_boxes(img: np.ndarray, objects: Iterable[ObjectLabelRecord],
         if obj.occlusion == 100:
             continue
         box3d_pts_3d = obj.as_3d_bbox()
-        uv = calib.project_ego_to_image(box3d_pts_3d)
         uv_cam = calib.project_ego_to_cam(box3d_pts_3d)
 
         img1 = obj.render_clip_frustum_cv2(