cleaned

simba/bounding_box_tools/yolo/geometries_to_annotations.py

@@ -10,9 +10,12 @@
 from skimage.draw import polygon
 
 from simba.mixins.geometry_mixin import GeometryMixin
-from simba.utils.checks import check_instance, check_int, check_valid_array, check_if_dir_exists
+from simba.utils.checks import (check_if_dir_exists, check_instance, check_int,
+                                check_valid_array)
 from simba.utils.enums import Formats
-from simba.utils.read_write import (get_video_meta_data, read_df, read_frm_of_video, find_files_of_filetypes_in_directory)
+from simba.utils.read_write import (find_files_of_filetypes_in_directory,
+                                    get_video_meta_data, read_df,
+                                    read_frm_of_video)
 
 
 def geometry_to_rle(geometry: Union[np.ndarray, Polygon], img_size: Tuple[int, int]):

simba/data_processors/boolean_conditional_calculator.py

@@ -6,11 +6,14 @@
 import pandas as pd
 
 from simba.mixins.config_reader import ConfigReader
-from simba.utils.checks import (check_all_file_names_are_represented_in_video_log, check_if_df_field_is_boolean, check_instance)
+from simba.utils.checks import (
+    check_all_file_names_are_represented_in_video_log,
+    check_if_df_field_is_boolean, check_instance)
+from simba.utils.data import detect_bouts
 from simba.utils.errors import MissingColumnsError
 from simba.utils.printing import stdout_success
-from simba.utils.read_write import (get_fn_ext, read_data_paths, read_df, read_video_info, str_2_bool)
-from simba.utils.data import detect_bouts
+from simba.utils.read_write import (get_fn_ext, read_data_paths, read_df,
+                                    read_video_info, str_2_bool)
 
 
 class BooleanConditionalCalculator(ConfigReader):

simba/mixins/train_model_mixin.py

@@ -32,7 +32,8 @@
 from sklearn.inspection import partial_dependence, permutation_importance
 from sklearn.metrics import classification_report, precision_recall_curve
 from sklearn.model_selection import ShuffleSplit, learning_curve
-from sklearn.preprocessing import (MinMaxScaler, QuantileTransformer, StandardScaler)
+from sklearn.preprocessing import (MinMaxScaler, QuantileTransformer,
+                                   StandardScaler)
 from sklearn.tree import export_graphviz
 from sklearn.utils import parallel_backend
 from tabulate import tabulate
@@ -57,11 +58,15 @@
 from simba.plotting.shap_agg_stats_visualizer import \
     ShapAggregateStatisticsVisualizer
 from simba.ui.tkinter_functions import TwoOptionQuestionPopUp
-from simba.utils.checks import (check_file_exist_and_readable, check_float, check_if_dir_exists, check_if_valid_input, check_instance, check_int, check_str, check_that_column_exist, check_valid_dataframe, check_valid_lst)
+from simba.utils.checks import (check_file_exist_and_readable, check_float,
+                                check_if_dir_exists, check_if_valid_input,
+                                check_instance, check_int, check_str,
+                                check_that_column_exist, check_valid_dataframe,
+                                check_valid_lst)
 from simba.utils.data import (detect_bouts, detect_bouts_multiclass,
                               get_library_version)
-from simba.utils.enums import (OS, ConfigKey, Defaults, Dtypes, Methods,
-                               MLParamKeys, Options, Formats)
+from simba.utils.enums import (OS, ConfigKey, Defaults, Dtypes, Formats,
+                               Methods, MLParamKeys, Options)
 from simba.utils.errors import (ClassifierInferenceError, ColumnNotFoundError,
                                 CorruptedFileError, DataHeaderError,
                                 FaultyTrainingSetError,

simba/third_party_label_appenders/converters.py

@@ -1,26 +1,32 @@
+import base64
+import io
+import itertools
 import json
 import os
-import itertools
-import pandas as pd
-import io
-from PIL import Image
-import base64
 from datetime import datetime
-from typing import Dict, Optional, Tuple, Union, Any
+from typing import Any, Dict, Optional, Tuple, Union
 
 import cv2
 import numpy as np
+import pandas as pd
+from PIL import Image
 from pycocotools import mask
 from shapely.geometry import Polygon
 from skimage.draw import polygon
 
 from simba.mixins.geometry_mixin import GeometryMixin
 from simba.mixins.image_mixin import ImageMixin
-from simba.utils.checks import check_instance, check_int, check_valid_array, check_if_dir_exists, check_if_keys_exist_in_dict, check_file_exist_and_readable, check_if_valid_img
+from simba.utils.checks import (check_file_exist_and_readable,
+                                check_if_dir_exists,
+                                check_if_keys_exist_in_dict,
+                                check_if_valid_img, check_instance, check_int,
+                                check_valid_array)
 from simba.utils.enums import Formats
-from simba.utils.read_write import get_video_meta_data, read_df, read_frm_of_video, find_files_of_filetypes_in_directory, get_fn_ext
-from simba.utils.errors import NoFilesFoundError, InvalidInputError
+from simba.utils.errors import InvalidInputError, NoFilesFoundError
 from simba.utils.printing import SimbaTimer, stdout_success
+from simba.utils.read_write import (find_files_of_filetypes_in_directory,
+                                    get_fn_ext, get_video_meta_data, read_df,
+                                    read_frm_of_video)
 
 
 def geometry_to_rle(geometry: Union[np.ndarray, Polygon], img_size: Tuple[int, int]):