diff --git a/flash/core/data/utils.py b/flash/core/data/utils.py
index 4e5c69ed0d0..fc16c03c92f 100644
--- a/flash/core/data/utils.py
+++ b/flash/core/data/utils.py
@@ -13,8 +13,8 @@
 # limitations under the License.
 
 import os.path
-import zipfile
 import tarfile
+import zipfile
 from typing import Any, Callable, Dict, Iterable, Mapping, Optional, Set, Type
 
 import requests
diff --git a/flash/image/__init__.py b/flash/image/__init__.py
index 6c7480ed6bb..95dfcf49d72 100644
--- a/flash/image/__init__.py
+++ b/flash/image/__init__.py
@@ -4,14 +4,9 @@
     ImageClassificationPreprocess,
     ImageClassifier,
 )
-from flash.image.detection import (  # noqa: F401
-    ObjectDetectionData,
-    ObjectDetector,
-)
-from flash.image.face_detection import (  # noqa: F401
-    FaceDetector,
-)
+from flash.image.detection import ObjectDetectionData, ObjectDetector  # noqa: F401
 from flash.image.embedding import ImageEmbedder  # noqa: F401
+from flash.image.face_detection import FaceDetector  # noqa: F401
 from flash.image.segmentation import (  # noqa: F401
     SemanticSegmentation,
     SemanticSegmentationData,
diff --git a/flash/image/face_detection/data.py b/flash/image/face_detection/data.py
index 4b3e7816718..be8e8e9cd89 100644
--- a/flash/image/face_detection/data.py
+++ b/flash/image/face_detection/data.py
@@ -13,14 +13,14 @@
 # limitations under the License.
 from typing import Any, Callable, Dict, Optional, Sequence, Tuple
 
+from torch.utils.data import Dataset
+
 from flash.core.data.data_source import DataSource, DefaultDataKeys, DefaultDataSources
 from flash.core.data.process import Preprocess
 from flash.core.utilities.imports import _TORCHVISION_AVAILABLE
 from flash.image.data import ImagePathsDataSource
 from flash.image.detection.transforms import default_transforms
 
-from torch.utils.data import Dataset
-
 if _TORCHVISION_AVAILABLE:
     from torchvision.datasets.folder import default_loader
 
diff --git a/flash/image/face_detection/model.py b/flash/image/face_detection/model.py
index 5468c8ae291..ef978142b1c 100644
--- a/flash/image/face_detection/model.py
+++ b/flash/image/face_detection/model.py
@@ -21,7 +21,6 @@
 from flash.core.data.process import Preprocess, Serializer
 from flash.core.model import Task
 from flash.core.utilities.imports import _FASTFACE_AVAILABLE
-
 from flash.image.detection.finetuning import ObjectDetectionFineTuning
 from flash.image.detection.serialization import DetectionLabels
 from flash.image.face_detection.data import FaceDetectionPreprocess
@@ -62,9 +61,7 @@ def __init__(
         self.save_hyperparameters()
 
         if model in ff.list_pretrained_models():
-            model = FaceDetector.get_model(
-                model, pretrained, **kwargs
-            )
+            model = FaceDetector.get_model(model, pretrained, **kwargs)
         else:
             ValueError(f"{model} is not supported yet.")
 
diff --git a/flash_examples/face_detection.py b/flash_examples/face_detection.py
index 5b2601db345..e8a14f7096e 100644
--- a/flash_examples/face_detection.py
+++ b/flash_examples/face_detection.py
@@ -12,10 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import flash
+from flash.core.data.data_module import DataModule
 from flash.core.utilities.imports import _FASTFACE_AVAILABLE
 from flash.image import FaceDetector
 from flash.image.face_detection.data import FaceDetectionPreprocess
-from flash.core.data.data_module import DataModule
 
 if _FASTFACE_AVAILABLE:
     import fastface as ff
@@ -27,19 +27,14 @@
 val_dataset = ff.dataset.FDDBDataset(source_dir="data/", phase="val")
 
 datamodule = DataModule.from_data_source(
-    "fastface",
-    train_data=train_dataset,
-    val_data=val_dataset,
-    preprocess=FaceDetectionPreprocess()
+    "fastface", train_data=train_dataset, val_data=val_dataset, preprocess=FaceDetectionPreprocess()
 )
 
 # 2. Build the task
 model = FaceDetector(model="lffd_slim")
 
 # 3. Create the trainer and finetune the model
-trainer = flash.Trainer(max_epochs=3,
-    limit_train_batches=0.1,
-    limit_val_batches=0.1)
+trainer = flash.Trainer(max_epochs=3, limit_train_batches=0.1, limit_val_batches=0.1)
 
 trainer.finetune(model, datamodule=datamodule, strategy="freeze")