diff --git a/configs/ops/image_to_tabular_data/op_image_to_tabular_data.yaml b/configs/ops/image_to_tabular_data/op_image_to_tabular_data.yaml
index 79dfa1dc..1261ca93 100644
--- a/configs/ops/image_to_tabular_data/op_image_to_tabular_data.yaml
+++ b/configs/ops/image_to_tabular_data/op_image_to_tabular_data.yaml
@@ -5,4 +5,4 @@ target_image_size:
   _target_: niceml.utilities.imagesize.ImageSize
   width: 10
   height: 10
-use_dirs_as_subsets: True
\ No newline at end of file
+use_dirs_as_subsets: True
diff --git a/docs/hydra-dagster.md b/docs/hydra-dagster.md
index 7a6fa055..aeece2da 100644
--- a/docs/hydra-dagster.md
+++ b/docs/hydra-dagster.md
@@ -137,4 +137,4 @@ configured you can find either in the source code or at our ops reference page.
 ### Conclusion
 
 In this tutorial, we've seen how to use Hydra with Dagster to configure a machine learning pipeline. Hydra allows for a hierarchical set of configuration files that can be used to define settings for different parts of the pipeline. 
-The `defaults` section in the YAML file allows us to import the content of other YAML files, making it easy to reuse common settings across different parts of the pipeline.
\ No newline at end of file
+The `defaults` section in the YAML file allows us to import the content of other YAML files, making it easy to reuse common settings across different parts of the pipeline.
diff --git a/niceml/dagster/ops/splitdata.py b/niceml/dagster/ops/splitdata.py
index e255174d..bb21a00b 100644
--- a/niceml/dagster/ops/splitdata.py
+++ b/niceml/dagster/ops/splitdata.py
@@ -44,7 +44,6 @@
     }
 )
 def split_data(context: OpExecutionContext, input_location: dict):
-
     """Splits the data in input_location into subsets (set_infos)"""
     op_config = json.loads(json.dumps(context.op_config))
 
diff --git a/niceml/dashboard/cam.py b/niceml/dashboard/cam.py
index c58ac4df..c2257496 100644
--- a/niceml/dashboard/cam.py
+++ b/niceml/dashboard/cam.py
@@ -12,7 +12,9 @@
     load_img,
 )
 
-from niceml.experiments.expdatalocalstorageloader import create_expdata_from_local_storage
+from niceml.experiments.expdatalocalstorageloader import (
+    create_expdata_from_local_storage,
+)
 from niceml.experiments.experimentdata import ExperimentData
 
 
diff --git a/niceml/dashboard/imagenetdataloggerviscomponent.py b/niceml/dashboard/imagenetdataloggerviscomponent.py
index c9341b2d..e7cee6ef 100644
--- a/niceml/dashboard/imagenetdataloggerviscomponent.py
+++ b/niceml/dashboard/imagenetdataloggerviscomponent.py
@@ -56,7 +56,6 @@ def _render(
         def _load_net_data(
             *args,  # pylint: disable = unused-argument
         ) -> List[np.ndarray]:
-
             return [
                 self.image_loader(filepath=net_data_path)
                 for net_data_path in net_data_paths[: self.max_output]
diff --git a/niceml/data/netdataloggers/netdatalogger.py b/niceml/data/netdataloggers/netdatalogger.py
index e3f95019..fec8270f 100644
--- a/niceml/data/netdataloggers/netdatalogger.py
+++ b/niceml/data/netdataloggers/netdatalogger.py
@@ -17,6 +17,7 @@ class NetDataLogger(ABC):
     """Abstract implementation of an NetDataLogger"""
 
     def __init__(self):
+        """Initializes the NetDataLogger with default values"""
         self.data_description = None
         self.exp_context = None
         self.set_name = None
@@ -28,7 +29,6 @@ def initialize(
         exp_context: ExperimentContext,
         set_name: str,
     ):
-
         """Method to initialize the NetDataLogger"""
         self.data_description = data_description
         self.exp_context = exp_context
diff --git a/niceml/dlframeworks/tensorflow/losses/categoricalfocalloss.py b/niceml/dlframeworks/tensorflow/losses/categoricalfocalloss.py
index 6084980c..d65e6687 100644
--- a/niceml/dlframeworks/tensorflow/losses/categoricalfocalloss.py
+++ b/niceml/dlframeworks/tensorflow/losses/categoricalfocalloss.py
@@ -1,3 +1,4 @@
+"""module for categorical focal loss"""
 from typing import List, Union
 
 import numpy as np
@@ -7,6 +8,8 @@
 
 @tf.keras.utils.register_keras_serializable()
 class CategoricalFocalLoss(tf.keras.losses.Loss):
+    """class for categorical focal loss"""
+
     def __init__(self, alpha: Union[float, List[float]], gamma: float = 2.0, **kwargs):
         """
         Inspired by https://github.com/umbertogriffo/focal-loss-keras
@@ -28,7 +31,7 @@ def __init__(self, alpha: Union[float, List[float]], gamma: float = 2.0, **kwarg
         self.gamma = gamma
 
     def __call__(self, y_true, y_pred, sample_weight=None):
-
+        """Call method for loss"""
         # Clip the prediction value to prevent NaN's and Inf's
         epsilon = kb.epsilon()
         y_pred = kb.clip(y_pred, epsilon, 1.0 - epsilon)
diff --git a/niceml/dlframeworks/tensorflow/metrics/objdetmetrics.py b/niceml/dlframeworks/tensorflow/metrics/objdetmetrics.py
index 2c9fc538..bb393075 100644
--- a/niceml/dlframeworks/tensorflow/metrics/objdetmetrics.py
+++ b/niceml/dlframeworks/tensorflow/metrics/objdetmetrics.py
@@ -13,10 +13,11 @@ class AvgPosPredObjDet:  # pylint: disable=too-few-public-methods
     """Positive Classification Values for object detection"""
 
     def __init__(self, name: str = "avg_pos_pred"):
-
+        """Initializes the AvgPosPredObjDet with the given name"""
         self.__name__ = name
 
     def __call__(self, y_true, y_pred):
+        """Call method is used as a default interface for the metric"""
         y_pred = tf.cast(y_pred, dtype=tf.float32)
 
         cls_predictions = y_pred[:, :, 4:]
@@ -35,10 +36,11 @@ class AvgNegPredObjDet:  # pylint: disable=too-few-public-methods
     """Negative Classification Values for object detection"""
 
     def __init__(self, name: str = "avg_neg_pred"):
-
+        """Initializes the AvgNegPredObjDet with the given name"""
         self.__name__ = name
 
     def __call__(self, y_true, y_pred):
+        """Call method is used as a default interface for the metric"""
         y_pred = tf.cast(y_pred, dtype=tf.float32)
 
         cls_predictions = y_pred[:, :, 4:]
@@ -67,9 +69,11 @@ class AvgPosTargetCountObjDet:  # pylint: disable=too-few-public-methods
     """Average positive target count for one image in object detection"""
 
     def __init__(self, name: str = "avg_pos_target_count"):
+        """Initializes the AvgPosTargetCountObjDet"""
         self.__name__ = name
 
     def __call__(self, y_true, y_pred):
+        """Call method is used as a default interface for the metric"""
         positive_mask = tf.cast(
             tf.equal(y_true[:, :, 4], POSITIVE_MASK_VALUE), dtype=tf.float32
         )
@@ -82,9 +86,11 @@ class AvgNegTargetCountObjDet:  # pylint: disable=too-few-public-methods
     """Average negative target count for one image in object detection"""
 
     def __init__(self, name: str = "avg_neg_target_count"):
+        """Initializes the AvgNegTargetCountObjDet"""
         self.__name__ = name
 
     def __call__(self, y_true, y_pred):
+        """Call method is used as a default interface for the metric"""
         negative_mask = tf.cast(
             tf.equal(y_true[:, :, 4], NEGATIVE_MASK_VALUE), dtype=tf.float32
         )
diff --git a/niceml/dlframeworks/tensorflow/models/mlp.py b/niceml/dlframeworks/tensorflow/models/mlp.py
index 4947db3f..b6ab8f4f 100644
--- a/niceml/dlframeworks/tensorflow/models/mlp.py
+++ b/niceml/dlframeworks/tensorflow/models/mlp.py
@@ -4,7 +4,9 @@
 from tensorflow.keras import Sequential, layers  # pylint: disable=import-error
 
 from niceml.data.datadescriptions.datadescription import DataDescription
-from niceml.data.datadescriptions.inputdatadescriptions import InputVectorDataDescription
+from niceml.data.datadescriptions.inputdatadescriptions import (
+    InputVectorDataDescription,
+)
 from niceml.data.datadescriptions.outputdatadescriptions import (
     OutputVectorDataDescription,
 )
@@ -22,12 +24,14 @@ def __init__(
         final_activation: str = "linear",
         do_summary: bool = True,
     ):
+        """Initializes the OwnMLP model factory"""
         self.hidden_layers = hidden_layers
         self.activation = activation
         self.do_summary = do_summary
         self.final_activation = final_activation
 
     def create_model(self, data_description: DataDescription) -> Any:
+        """Creates the mlp model"""
         input_dd: InputVectorDataDescription = check_instance(
             data_description, InputVectorDataDescription
         )
diff --git a/niceml/experiments/experimenttests/validateexps.py b/niceml/experiments/experimenttests/validateexps.py
index ca5bcd30..974c0b3a 100644
--- a/niceml/experiments/experimenttests/validateexps.py
+++ b/niceml/experiments/experimenttests/validateexps.py
@@ -7,7 +7,9 @@
 
 from niceml.data.storages.fsfilesystemstorage import FsFileSystemStorage
 from niceml.data.storages.fsspecstorage import FSSpecStorage
-from niceml.experiments.expdatalocalstorageloader import create_expdata_from_local_storage
+from niceml.experiments.expdatalocalstorageloader import (
+    create_expdata_from_local_storage,
+)
 from niceml.experiments.experimenterrors import EmptyExperimentError
 from niceml.experiments.experimenttests.exptests import (
     ExperimentTest,
diff --git a/niceml/experiments/expoutinitializer.py b/niceml/experiments/expoutinitializer.py
index 7a028ac8..3737357b 100644
--- a/niceml/experiments/expoutinitializer.py
+++ b/niceml/experiments/expoutinitializer.py
@@ -35,7 +35,6 @@ def __init__(
         self.exp_type: str = exp_type or ""
 
     def __call__(self, exp_context: ExperimentContext):
-
         produce_git_version_yaml(
             exp_context,
             ExperimentFilenames.GIT_VERSIONS,
diff --git a/niceml/mlcomponents/objdet/anchorencoding.py b/niceml/mlcomponents/objdet/anchorencoding.py
index c0b9de3c..0d1743c4 100644
--- a/niceml/mlcomponents/objdet/anchorencoding.py
+++ b/niceml/mlcomponents/objdet/anchorencoding.py
@@ -53,13 +53,11 @@ def encode_anchors(  # pylint: disable=too-many-locals
         encoded_feature_list: List[List[float]] = []
 
         for anchor in anchor_list:
-
             if len(gt_labels) == 0:
                 target_bbox = anchor
                 target_label = None
                 prediction_flag = NEGATIVE_MASK_VALUE
             else:
-
                 max_iou = 0
                 target_bbox = gt_labels[0].bounding_box
                 target_label = None
diff --git a/niceml/mlcomponents/predictionhandlers/objdetpredictionhandler.py b/niceml/mlcomponents/predictionhandlers/objdetpredictionhandler.py
index 3fb552f9..e6ddb544 100644
--- a/niceml/mlcomponents/predictionhandlers/objdetpredictionhandler.py
+++ b/niceml/mlcomponents/predictionhandlers/objdetpredictionhandler.py
@@ -29,7 +29,7 @@
 class ObjDetPredictionHandler(PredictionHandler):
     """Prediction handler for object detection predictions (BoundingBox, class prediction)"""
 
-    def __init__(  # pylint: disable=too-many-arguments
+    def __init__(  # noqa: PLR0913
         self,
         prediction_filter: PredictionFilter,
         prediction_prefix: str = "pred",
@@ -37,7 +37,7 @@ def __init__(  # pylint: disable=too-many-arguments
         detection_idx_col: str = DETECTION_INDEX_COLUMN_NAME,
         apply_sigmoid: bool = True,
     ):
-
+        """Initializes the ObjDetPredictionHandler"""
         super().__init__()
         self.prediction_filter = prediction_filter
         self.prediction_prefix = prediction_prefix
@@ -53,6 +53,7 @@ def __init__(  # pylint: disable=too-many-arguments
         self.anchor_array = None
 
     def initialize(self):
+        """Initializes the prediction handler"""
         self.anchors: List[BoundingBox] = self.anchor_generator.generate_anchors(
             data_description=self.data_description
         )
diff --git a/niceml/mlcomponents/predictionhandlers/tensorpredictionhandler.py b/niceml/mlcomponents/predictionhandlers/tensorpredictionhandler.py
index e5d13929..1df3921e 100644
--- a/niceml/mlcomponents/predictionhandlers/tensorpredictionhandler.py
+++ b/niceml/mlcomponents/predictionhandlers/tensorpredictionhandler.py
@@ -74,7 +74,6 @@ def __exit__(self, exc_type, exc_value, exc_traceback):
                     ),
                     "wb",
                 ) as file:
-
                     np.savez_compressed(file, **self.data)
 
 
diff --git a/niceml/mlcomponents/resultanalyzers/instancefinders/maskinstance.py b/niceml/mlcomponents/resultanalyzers/instancefinders/maskinstance.py
index 629099a6..f890f4f5 100644
--- a/niceml/mlcomponents/resultanalyzers/instancefinders/maskinstance.py
+++ b/niceml/mlcomponents/resultanalyzers/instancefinders/maskinstance.py
@@ -5,7 +5,9 @@
 
 import numpy as np
 
-from niceml.data.datadescriptions.outputdatadescriptions import OutputImageDataDescription
+from niceml.data.datadescriptions.outputdatadescriptions import (
+    OutputImageDataDescription,
+)
 from niceml.mlcomponents.resultanalyzers.instancefinders.instancecontour import (
     InstanceContour,
 )
diff --git a/niceml/mlcomponents/resultanalyzers/instancefinders/multichannelinstancefinder.py b/niceml/mlcomponents/resultanalyzers/instancefinders/multichannelinstancefinder.py
index 6b9ebb84..af1a468d 100644
--- a/niceml/mlcomponents/resultanalyzers/instancefinders/multichannelinstancefinder.py
+++ b/niceml/mlcomponents/resultanalyzers/instancefinders/multichannelinstancefinder.py
@@ -11,7 +11,9 @@
 from niceml.mlcomponents.resultanalyzers.instancefinders.instancefinder import (
     InstanceFinder,
 )
-from niceml.mlcomponents.resultanalyzers.instancefinders.maskinstance import MaskInstance
+from niceml.mlcomponents.resultanalyzers.instancefinders.maskinstance import (
+    MaskInstance,
+)
 from niceml.mlcomponents.resultanalyzers.tensors.semsegdataiterator import (
     SemSegPredictionContainer,
 )
diff --git a/niceml/mlcomponents/targettransformer/objdettargettransformer.py b/niceml/mlcomponents/targettransformer/objdettargettransformer.py
index acfd5c67..38010f7a 100644
--- a/niceml/mlcomponents/targettransformer/objdettargettransformer.py
+++ b/niceml/mlcomponents/targettransformer/objdettargettransformer.py
@@ -27,7 +27,6 @@ def __init__(
         self.anchors = None
 
     def get_net_targets(self, data_list: List[ObjDetData]) -> np.ndarray:
-
         if self.anchors is None:
             if isinstance(self.data_description, OutputObjDetDataDescription):
                 self.anchors = self.anchor_generator.generate_anchors(
diff --git a/niceml/mlcomponents/targettransformer/semsegtargettransformer.py b/niceml/mlcomponents/targettransformer/semsegtargettransformer.py
index 4a400224..24c32438 100644
--- a/niceml/mlcomponents/targettransformer/semsegtargettransformer.py
+++ b/niceml/mlcomponents/targettransformer/semsegtargettransformer.py
@@ -4,7 +4,9 @@
 import numpy as np
 
 from niceml.data.datadescriptions.inputdatadescriptions import InputImageDataDescription
-from niceml.data.datadescriptions.outputdatadescriptions import OutputImageDataDescription
+from niceml.data.datadescriptions.outputdatadescriptions import (
+    OutputImageDataDescription,
+)
 from niceml.data.datainfos.semsegdatainfo import SemSegData
 from niceml.mlcomponents.targettransformer.targettransformer import NetTargetTransformer
 from niceml.utilities.commonutils import check_instance
diff --git a/niceml/utilities/boundingboxes/bboxdrawing.py b/niceml/utilities/boundingboxes/bboxdrawing.py
index d0b8d2b4..baeed196 100644
--- a/niceml/utilities/boundingboxes/bboxdrawing.py
+++ b/niceml/utilities/boundingboxes/bboxdrawing.py
@@ -42,7 +42,9 @@ def draw_bounding_box_on_image(
     font = get_font("OpenSans-Regular.ttf", font_size=font_size)
 
     text = f"{label.class_name}: {label.score:.2f}" if label.score else label.class_name
-    text_width, text_height = font.getsize(text)
+    (left, top, right, bottom) = font.getbbox(text)
+    text_width = right - left
+    text_height = bottom - top
     x_1, y_1, x_2, y_2 = label.bounding_box.get_absolute_ullr()
     draw.rectangle(
         (x_1 - line_width, y_1 - line_width, x_2 + line_width, y_2 + line_width),
@@ -69,7 +71,7 @@ def draw_bounding_box_on_image(
     return image
 
 
-def draw_labels_on_image(  # pylint: disable=too-many-arguments
+def draw_labels_on_image(  # noqa: PLR0913
     image: ImageType,
     pred_bbox_label_list: List[ObjDetInstanceLabel],
     gt_bbox_label_list: List[ObjDetInstanceLabel],
diff --git a/niceml/utilities/boundingboxes/bboxencoding.py b/niceml/utilities/boundingboxes/bboxencoding.py
index 6f6de4c6..13ce0cc7 100644
--- a/niceml/utilities/boundingboxes/bboxencoding.py
+++ b/niceml/utilities/boundingboxes/bboxencoding.py
@@ -5,7 +5,6 @@
 def encode_boxes(
     anchor_boxes_xywh: np.ndarray, gt_boxes_xywh: np.ndarray, box_variances: np.ndarray
 ) -> np.ndarray:
-
     """
     Encodes the anchor boxes to a numpy array
 
@@ -48,7 +47,6 @@ def decode_boxes(
     encoded_array_xywh: np.ndarray,
     box_variances: np.ndarray,
 ) -> np.ndarray:
-
     """
     Decodes the incoming array to target boxes
 
diff --git a/niceml/utilities/boundingboxes/bboxlabeling.py b/niceml/utilities/boundingboxes/bboxlabeling.py
index 9835c1fd..a31d8c3f 100644
--- a/niceml/utilities/boundingboxes/bboxlabeling.py
+++ b/niceml/utilities/boundingboxes/bboxlabeling.py
@@ -4,7 +4,10 @@
 from attr import define, field
 
 from niceml.utilities.boundingboxes.bboxconversion import dict_to_bounding_box
-from niceml.utilities.boundingboxes.boundingbox import BoundingBox, bounding_box_from_ullr
+from niceml.utilities.boundingboxes.boundingbox import (
+    BoundingBox,
+    bounding_box_from_ullr,
+)
 from niceml.utilities.imagesize import ImageSize
 from niceml.utilities.instancelabeling import InstanceLabel
 
diff --git a/niceml/utilities/boundingboxes/filtering/nmsfilter.py b/niceml/utilities/boundingboxes/filtering/nmsfilter.py
index 75b647fa..9b360173 100644
--- a/niceml/utilities/boundingboxes/filtering/nmsfilter.py
+++ b/niceml/utilities/boundingboxes/filtering/nmsfilter.py
@@ -4,7 +4,10 @@
 import numpy as np
 from attrs import define
 
-from niceml.utilities.boundingboxes.bboxconversion import convert_to_ullr, convert_to_xywh
+from niceml.utilities.boundingboxes.bboxconversion import (
+    convert_to_ullr,
+    convert_to_xywh,
+)
 from niceml.utilities.boundingboxes.filtering.predictionfilter import PredictionFilter
 from niceml.utilities.ioumatrix import compute_iou_matrix
 
diff --git a/niceml/utilities/boundingboxes/filtering/unifiedboxfilter.py b/niceml/utilities/boundingboxes/filtering/unifiedboxfilter.py
index efc9d79e..e5ef43f9 100644
--- a/niceml/utilities/boundingboxes/filtering/unifiedboxfilter.py
+++ b/niceml/utilities/boundingboxes/filtering/unifiedboxfilter.py
@@ -4,7 +4,10 @@
 import numpy as np
 from attrs import define
 
-from niceml.utilities.boundingboxes.bboxconversion import convert_to_ullr, convert_to_xywh
+from niceml.utilities.boundingboxes.bboxconversion import (
+    convert_to_ullr,
+    convert_to_xywh,
+)
 from niceml.utilities.boundingboxes.filtering.predictionfilter import PredictionFilter
 from niceml.utilities.ioumatrix import compute_iou_matrix
 
diff --git a/niceml/utilities/commonutils.py b/niceml/utilities/commonutils.py
index deeca5c4..7ed186b1 100644
--- a/niceml/utilities/commonutils.py
+++ b/niceml/utilities/commonutils.py
@@ -97,12 +97,12 @@ def human_readable_size(obj: Any) -> str:
     size = asizeof.asizeof(obj)
     if size < 1024:
         return f"{size} bytes"
-    if 1024 <= size < 1024 ** 2:
+    if 1024 <= size < 1024**2:
         size_kb = size / 1024
         return f"{size_kb:.2f} KB"
-    if 1024 ** 2 <= size < 1024 ** 3:
-        size_mb = size / 1024 ** 2
+    if 1024**2 <= size < 1024**3:
+        size_mb = size / 1024**2
         return f"{size_mb:.2f} MB"
 
-    size_gb = size / 1024 ** 3
+    size_gb = size / 1024**3
     return f"{size_gb:.2f} GB"
diff --git a/niceml/utilities/imageutils.py b/niceml/utilities/imageutils.py
index d192e90e..4611281f 100644
--- a/niceml/utilities/imageutils.py
+++ b/niceml/utilities/imageutils.py
@@ -121,7 +121,12 @@ def binarize_multichannel_image(
             mask including information where the prediction is above threshold
     """
     binary_multichannel_images: Dict[str, np.ndarray] = {}
-    scores_mask = cv2.threshold(image_scores, threshold, 1, cv2.THRESH_BINARY,)[
+    scores_mask = cv2.threshold(
+        image_scores,
+        threshold,
+        1,
+        cv2.THRESH_BINARY,
+    )[
         1
     ].astype(np.uint8)
 
diff --git a/niceml/utilities/instancelabelmatching.py b/niceml/utilities/instancelabelmatching.py
index 1b43f523..55331ae2 100644
--- a/niceml/utilities/instancelabelmatching.py
+++ b/niceml/utilities/instancelabelmatching.py
@@ -45,7 +45,6 @@ def get_kind_of_label_match(
                 pred_label.color = Color.BLUE
                 pred_label.active = True
             for gt_label in gt_label_list:
-
                 iou = pred_label.calc_iou(other=gt_label)
 
                 pred_label, gt_label = get_kind_of_instance_label_match(
diff --git a/niceml/utilities/splitutils.py b/niceml/utilities/splitutils.py
index 026e3f1b..c0ac0c5a 100644
--- a/niceml/utilities/splitutils.py
+++ b/niceml/utilities/splitutils.py
@@ -114,7 +114,7 @@ def create_copy_files_container(
                 identifier = "".join(
                     [char for char in cur_basename if char in ALPHANUMERICLIST]
                 )
-                cur_seed = int(identifier, base=len(ALPHANUMERICLIST)) % (2 ** 32 - 1)
+                cur_seed = int(identifier, base=len(ALPHANUMERICLIST)) % (2**32 - 1)
                 rng = np.random.default_rng(seed=cur_seed)
                 drawn_set = rng.choice(set_list, 1, p=prob_list)[0]
                 output_file = join(drawn_set, file)
diff --git a/poetry.lock b/poetry.lock
index b836821d..529da190 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1316,49 +1316,57 @@ files = [
 
 [[package]]
 name = "fonttools"
-version = "4.42.1"
+version = "4.45.0"
 description = "Tools to manipulate font files"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fonttools-4.42.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:ed1a13a27f59d1fc1920394a7f596792e9d546c9ca5a044419dca70c37815d7c"},
-    {file = "fonttools-4.42.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c9b1ce7a45978b821a06d375b83763b27a3a5e8a2e4570b3065abad240a18760"},
-    {file = "fonttools-4.42.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f720fa82a11c0f9042376fd509b5ed88dab7e3cd602eee63a1af08883b37342b"},
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+
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 version = "2.22.0"
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 ]
 
 [package.dependencies]
@@ -4987,13 +4986,13 @@ full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart", "pyyam
 
 [[package]]
 name = "streamlit"
-version = "1.25.0"
+version = "1.28.2"
 description = "A faster way to build and share data apps"
 optional = true
 python-versions = ">=3.8, !=3.9.7"
 files = [
-    {file = "streamlit-1.25.0-py2.py3-none-any.whl", hash = "sha256:3c561dca1b5430e73b7f2d66bff1d26103936bb4223912ab563ffee881fccc30"},
-    {file = "streamlit-1.25.0.tar.gz", hash = "sha256:8a7c93bee8703869045804afe22e9373c4e974fdb2a3e9abe3b027df3de03119"},
+    {file = "streamlit-1.28.2-py2.py3-none-any.whl", hash = "sha256:cc144c4741a1bd850ccd13f1ef18fad170718242dd7930f4ae36e238d08ecd22"},
+    {file = "streamlit-1.28.2.tar.gz", hash = "sha256:c144168881bf7bd6d6017a9bfde585b52d20087b10b2d5c85d376ef6d52aa8ee"},
 ]
 
 [package.dependencies]
@@ -5006,24 +5005,23 @@ importlib-metadata = ">=1.4,<7"
 numpy = ">=1.19.3,<2"
 packaging = ">=16.8,<24"
 pandas = ">=1.3.0,<3"
-pillow = ">=7.1.0,<10"
+pillow = ">=7.1.0,<11"
 protobuf = ">=3.20,<5"
 pyarrow = ">=6.0"
-pydeck = ">=0.8,<1"
-pympler = ">=0.9,<2"
+pydeck = ">=0.8.0b4,<1"
 python-dateutil = ">=2.7.3,<3"
-requests = ">=2.18,<3"
+requests = ">=2.27,<3"
 rich = ">=10.14.0,<14"
 tenacity = ">=8.1.0,<9"
 toml = ">=0.10.1,<2"
 tornado = ">=6.0.3,<7"
-typing-extensions = ">=4.1.0,<5"
-tzlocal = ">=1.1,<5"
+typing-extensions = ">=4.3.0,<5"
+tzlocal = ">=1.1,<6"
 validators = ">=0.2,<1"
 watchdog = {version = ">=2.1.5", markers = "platform_system != \"Darwin\""}
 
 [package.extras]
-snowflake = ["snowflake-snowpark-python"]
+snowflake = ["snowflake-connector-python (>=2.8.0)", "snowflake-snowpark-python (>=0.9.0)"]
 
 [[package]]
 name = "tabulate"
@@ -5470,17 +5468,17 @@ tests = ["mypy (==1.3.0)", "pylint (==2.17.4)", "pytest (==7.3.2)", "pytest-cov
 
 [[package]]
 name = "urllib3"
-version = "1.26.16"
+version = "1.26.18"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
-    {file = "urllib3-1.26.16-py2.py3-none-any.whl", hash = "sha256:8d36afa7616d8ab714608411b4a3b13e58f463aee519024578e062e141dce20f"},
-    {file = "urllib3-1.26.16.tar.gz", hash = "sha256:8f135f6502756bde6b2a9b28989df5fbe87c9970cecaa69041edcce7f0589b14"},
+    {file = "urllib3-1.26.18-py2.py3-none-any.whl", hash = "sha256:34b97092d7e0a3a8cf7cd10e386f401b3737364026c45e622aa02903dffe0f07"},
+    {file = "urllib3-1.26.18.tar.gz", hash = "sha256:f8ecc1bba5667413457c529ab955bf8c67b45db799d159066261719e328580a0"},
 ]
 
 [package.extras]
-brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"]
+brotli = ["brotli (==1.0.9)", "brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"]
 secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"]
 socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
@@ -5802,13 +5800,13 @@ files = [
 
 [[package]]
 name = "werkzeug"
-version = "2.3.7"
+version = "3.0.1"
 description = "The comprehensive WSGI web application library."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "werkzeug-2.3.7-py3-none-any.whl", hash = "sha256:effc12dba7f3bd72e605ce49807bbe692bd729c3bb122a3b91747a6ae77df528"},
-    {file = "werkzeug-2.3.7.tar.gz", hash = "sha256:2b8c0e447b4b9dbcc85dd97b6eeb4dcbaf6c8b6c3be0bd654e25553e0a2157d8"},
+    {file = "werkzeug-3.0.1-py3-none-any.whl", hash = "sha256:90a285dc0e42ad56b34e696398b8122ee4c681833fb35b8334a095d82c56da10"},
+    {file = "werkzeug-3.0.1.tar.gz", hash = "sha256:507e811ecea72b18a404947aded4b3390e1db8f826b494d76550ef45bb3b1dcc"},
 ]
 
 [package.dependencies]
@@ -6014,4 +6012,4 @@ visu = ["altair", "streamlit"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8,<3.9.7 || >3.9.7,<3.11"
-content-hash = "02952e5b43a257227e0ce947131a95f98eb322253022c8359a5dc56b9f111b34"
+content-hash = "243686ea72fbe3a9b35c457b3ecd418dbc8ee47fd98027184ac6bb03874d803a"
diff --git a/pyproject.toml b/pyproject.toml
index 91994703..5b41e5b2 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -44,7 +44,7 @@ click = "^8.1.3"
 opencv-python = "^4.7.0.72"
 cython = "^0.29.34"
 pyyaml = "^6.0"
-pillow = "^9.5.0"
+pillow = "^10.1.0"
 fastparquet = "^2023.2.0"
 hydra-core = "^1.3.2"
 pympler = "^1.0.1"
@@ -68,7 +68,7 @@ protobuf = "^3.0.0"
 
 altair = {version = "^4.2.2", optional = true}
 tensorflow-macos = { version = "~2.12", optional = true}
-streamlit = {version = "^1.22.0", optional = true}
+streamlit = {version = "^1.28.0", optional = true}
 tensorflow = {version = "~2.12", optional = true}
 tensorflow-metal = {version = "~1.0", optional = true}
 requests = "^2.31.0"
diff --git a/tests/unit/niceml/dlframeworkds/tensorflow/losses/test_semsegfocalloss.py b/tests/unit/niceml/dlframeworkds/tensorflow/losses/test_semsegfocalloss.py
index 71e4c430..e34b7efe 100644
--- a/tests/unit/niceml/dlframeworkds/tensorflow/losses/test_semsegfocalloss.py
+++ b/tests/unit/niceml/dlframeworkds/tensorflow/losses/test_semsegfocalloss.py
@@ -19,7 +19,6 @@ def tensor_shape() -> Tuple:
 def test_positive_zero_preds(
     alpha: float, gamma: float, min_expected_vals: List[float], tensor_shape: Tuple
 ):
-
     preds = tf.ones(tensor_shape) * 0.003
     gts = tf.ones(tensor_shape)
 
@@ -43,7 +42,6 @@ def test_positive_zero_preds(
 def test_positive_one_preds(
     alpha: float, gamma: float, max_expected_vals: List[float], tensor_shape: Tuple
 ):
-
     preds = tf.ones(tensor_shape) * 0.997
     gts = tf.ones(tensor_shape)
 
diff --git a/tests/unit/niceml/experiments/experimenttests/test_filesfoldertest.py b/tests/unit/niceml/experiments/experimenttests/test_filesfoldertest.py
index c192b6df..dc748f12 100644
--- a/tests/unit/niceml/experiments/experimenttests/test_filesfoldertest.py
+++ b/tests/unit/niceml/experiments/experimenttests/test_filesfoldertest.py
@@ -5,7 +5,9 @@
 
 import pytest
 
-from niceml.experiments.experimenttests.checkfilesfolderstest import CheckFilesFoldersTest
+from niceml.experiments.experimenttests.checkfilesfolderstest import (
+    CheckFilesFoldersTest,
+)
 from niceml.experiments.experimenttests.exptests import ExpTestResult, TestStatus
 
 
diff --git a/tests/unit/niceml/mlcomponents/predictionhandlers/test_semsegpredictionhandler.py b/tests/unit/niceml/mlcomponents/predictionhandlers/test_semsegpredictionhandler.py
index 9391ca88..440a9e94 100644
--- a/tests/unit/niceml/mlcomponents/predictionhandlers/test_semsegpredictionhandler.py
+++ b/tests/unit/niceml/mlcomponents/predictionhandlers/test_semsegpredictionhandler.py
@@ -83,7 +83,6 @@ def test_create_bbox_prediction_from_mask_instances(
     class_list,
     target_coords: List[List[int]],
 ):
-
     prediction = random_generator.uniform(
         low=0.5, high=1.0, size=(image_shape[0], image_shape[1], len(class_list))
     )
diff --git a/tests/unit/niceml/utilities/boundingboxes/test_bboxdrawing.py b/tests/unit/niceml/utilities/boundingboxes/test_bboxdrawing.py
index e0a120df..d96fa65a 100644
--- a/tests/unit/niceml/utilities/boundingboxes/test_bboxdrawing.py
+++ b/tests/unit/niceml/utilities/boundingboxes/test_bboxdrawing.py
@@ -15,7 +15,7 @@ def test_draw_labels_on_image():
     # Given
     img_size = ImageSize(1024, 1024)
     random_generator = np.random.default_rng(seed=42)
-    random.seed(42) # Setting the seed of `random` is required by albumentation
+    random.seed(42)  # Setting the seed of `random` is required by albumentation
 
     img, _, gt_labels = generate_number_image(
         random_generator=random_generator,
@@ -74,7 +74,7 @@ def test_draw_labels_on_image():
         image=img,
         pred_bbox_label_list=pred_labels,
         gt_bbox_label_list=gt_labels,
-        iou_threshold=0.3
+        iou_threshold=0.3,
     )
     by_color = defaultdict(int)
 
diff --git a/tests/unit/niceml/utilities/boundingboxes/test_bboxmatching.py b/tests/unit/niceml/utilities/boundingboxes/test_bboxmatching.py
index 30553ba0..e78fd633 100644
--- a/tests/unit/niceml/utilities/boundingboxes/test_bboxmatching.py
+++ b/tests/unit/niceml/utilities/boundingboxes/test_bboxmatching.py
@@ -151,7 +151,6 @@ def test_get_kind_of_bbox_match(
     gt_label_list: List[ObjDetInstanceLabel] = []
 
     for pred_label_idx in range(amount_pred_label):
-
         bbox = get_random_bounding_box(
             img_size=image_size,
             random_generator=random_generator,
diff --git a/tests/unit/niceml/utilities/semseg/test_semseginstancelabel.py b/tests/unit/niceml/utilities/semseg/test_semseginstancelabel.py
index 427c9e03..b1e2c2fb 100644
--- a/tests/unit/niceml/utilities/semseg/test_semseginstancelabel.py
+++ b/tests/unit/niceml/utilities/semseg/test_semseginstancelabel.py
@@ -25,7 +25,6 @@ def test_semseg_iou(
     class_index: int,
     seed: int,
 ):  # pylint: disable =too-many-arguments
-
     random_generator = np.random.default_rng(seed=seed)
 
     semseg_label_mask, _ = get_random_semseg_mask(
diff --git a/tests/unit/niceml/utilities/semseg/test_semsegmatching.py b/tests/unit/niceml/utilities/semseg/test_semsegmatching.py
index 87ff7ba5..5ea71a77 100644
--- a/tests/unit/niceml/utilities/semseg/test_semsegmatching.py
+++ b/tests/unit/niceml/utilities/semseg/test_semsegmatching.py
@@ -107,7 +107,6 @@ def test_get_kind_of_error_mask_matching(
     gt_label_list: List[SemSegInstanceLabel] = []
 
     for pred_label_idx in range(amount_pred_label):
-
         semseg_label_mask, _ = get_random_semseg_mask(
             image_shape=image_shape,
             random_generator=random_generator,
@@ -124,7 +123,6 @@ def test_get_kind_of_error_mask_matching(
         pred_label_list.append(pred_label)
 
     for gt_label_idx in range(amount_gt_label):
-
         gt_mask, _ = get_random_semseg_mask(
             image_shape=image_shape,
             random_generator=random_generator,