pep8

flash/core/data/utils.py

@@ -164,7 +164,7 @@ def extract_tarfile(file_path: str, extract_path: str, mode: str):
                 zip_ref.extractall(path)
     elif local_filename.endswith(".tar.gz") or local_filename.endswith(".tgz"):
         extract_tarfile(local_filename, path, "r:gz")
-    elif local_filename.endswith('.tar.bz2') or local_filename.endswith('.tbz'):
+    elif local_filename.endswith(".tar.bz2") or local_filename.endswith(".tbz"):
         extract_tarfile(local_filename, path, "r:bz2")
 
 

flash/image/__init__.py

@@ -6,7 +6,7 @@
 from flash.image.classification.backbones import IMAGE_CLASSIFIER_BACKBONES  # noqa: F401
 from flash.image.detection import ObjectDetectionData, ObjectDetector  # noqa: F401
 from flash.image.embedding import ImageEmbedder  # noqa: F401
-from flash.image.face_detection import FaceDetector, FaceDetectionData # noqa: F401
+from flash.image.face_detection import FaceDetectionData, FaceDetector  # noqa: F401
 from flash.image.instance_segmentation import InstanceSegmentation, InstanceSegmentationData  # noqa: F401
 from flash.image.keypoint_detection import KeypointDetectionData, KeypointDetector  # noqa: F401
 from flash.image.segmentation import (  # noqa: F401

flash/image/face_detection/__init__.py

@@ -1,2 +1,2 @@
-from flash.image.face_detection.model import FaceDetector  # noqa: F401
 from flash.image.face_detection.data import FaceDetectionData  # noqa: F401
+from flash.image.face_detection.model import FaceDetector  # noqa: F401

flash/image/face_detection/data.py

@@ -11,31 +11,23 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Callable, Dict, Optional, Sequence, Tuple, Mapping
+from typing import Any, Callable, Dict, Mapping, Optional, Sequence, Tuple
 
 import torch
-import torchvision
 import torch.nn as nn
-
+import torchvision
 from torch.utils.data import Dataset
 
-from flash.core.data.transforms import ApplyToKeys
 from flash.core.data.data_source import DatasetDataSource, DefaultDataKeys, DefaultDataSources
-from flash.core.data.process import Preprocess, Postprocess
-from flash.core.utilities.imports import _TORCHVISION_AVAILABLE, _ICEVISION_AVAILABLE, _FASTFACE_AVAILABLE
+from flash.core.data.process import Postprocess, Preprocess
+from flash.core.data.transforms import ApplyToKeys
+from flash.core.utilities.imports import _FASTFACE_AVAILABLE, _TORCHVISION_AVAILABLE
 from flash.image.data import ImagePathsDataSource
-from flash.core.integrations.icevision.data import IceVisionParserDataSource
-from flash.core.integrations.icevision.transforms import default_transforms
 from flash.image.detection import ObjectDetectionData
 
 if _TORCHVISION_AVAILABLE:
     from torchvision.datasets.folder import default_loader
 
-if _ICEVISION_AVAILABLE:
-    from icevision.parsers import COCOBBoxParser
-else:
-    COCOBBoxParser = object
-
 if _FASTFACE_AVAILABLE:
     import fastface as ff
 
@@ -77,7 +69,7 @@ def load_data(self, data: Dataset, dataset: Any = None) -> Dataset:
                         dict(
                             boxes=targets["target_boxes"],
                             labels=[1 for _ in range(targets["target_boxes"].shape[0])],
-                        )
+                        ),
                     )
                 )
             )
@@ -99,7 +91,6 @@ def load_sample(self, sample: Any, dataset: Optional[Any] = None) -> Mapping[str
 
 
 class FaceDetectionPreprocess(Preprocess):
-
     def __init__(
         self,
         train_transform: Optional[Dict[str, Callable]] = None,
@@ -137,9 +128,9 @@ def default_transforms(self) -> Dict[str, Callable]:
                 ApplyToKeys(
                     DefaultDataKeys.TARGET,
                     nn.Sequential(
-                        ApplyToKeys('boxes', torch.as_tensor),
-                        ApplyToKeys('labels', torch.as_tensor),
-                    )
+                        ApplyToKeys("boxes", torch.as_tensor),
+                        ApplyToKeys("labels", torch.as_tensor),
+                    ),
                 ),
             ),
             "collate": fastface_collate_fn,
@@ -149,11 +140,11 @@ def default_transforms(self) -> Dict[str, Callable]:
 class FaceDetectionPostProcess(Postprocess):
     @staticmethod
     def per_batch_transform(batch: Any) -> Any:
-        scales = batch['scales']
-        paddings = batch['paddings']
+        scales = batch["scales"]
+        paddings = batch["paddings"]
 
-        batch.pop('scales', None)
-        batch.pop('paddings', None)
+        batch.pop("scales", None)
+        batch.pop("paddings", None)
 
         preds = batch[DefaultDataKeys.PREDS]
 

flash/image/face_detection/model.py

@@ -11,21 +11,19 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Callable, List, Mapping, Optional, Sequence, Type, Union, Dict
+from typing import Any, Callable, Dict, List, Mapping, Optional, Sequence, Type, Union
 
-import torch
 import pytorch_lightning as pl
-
+import torch
 from torch import nn
 from torch.optim import Optimizer
 
-from flash.core.model import Task
 from flash.core.data.data_source import DefaultDataKeys
-from flash.core.data.process import Postprocess
 from flash.core.data.process import Preprocess, Serializer
-from flash.core.utilities.imports import _FASTFACE_AVAILABLE
 from flash.core.finetuning import FlashBaseFinetuning
-from flash.image.face_detection.data import FaceDetectionPreprocess, FaceDetectionPostProcess
+from flash.core.model import Task
+from flash.core.utilities.imports import _FASTFACE_AVAILABLE
+from flash.image.face_detection.data import FaceDetectionPreprocess
 
 if _FASTFACE_AVAILABLE:
     import fastface as ff
@@ -48,7 +46,9 @@ def serialize(self, sample: Any) -> Dict[str, Any]:
 
 
 class FaceDetector(Task):
-    """The ``FaceDetector`` is a :class:`~flash.Task` for detecting faces in images. For more details, see
+    """The ``FaceDetector`` is a :class:`~flash.Task` for detecting faces in images.
+
+    For more details, see
     :ref:`face_detection`.
     Args:
         model: a string of :attr`_models`. Defaults to 'lffd_slim'.

flash_examples/face_detection.py

@@ -12,13 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import flash
-
-from flash.core.data.utils import download_data
-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, FaceDetectionPostProcess
-from flash.image import FaceDetectionData
+from flash.image import FaceDetectionData, FaceDetector
 
 if _FASTFACE_AVAILABLE:
     import fastface as ff
@@ -29,9 +24,7 @@
 train_dataset = ff.dataset.FDDBDataset(source_dir="data/", phase="train")
 val_dataset = ff.dataset.FDDBDataset(source_dir="data/", phase="val")
 
-datamodule = FaceDetectionData.from_datasets(
-    train_dataset=train_dataset, val_dataset=val_dataset, batch_size=2
-)
+datamodule = FaceDetectionData.from_datasets(train_dataset=train_dataset, val_dataset=val_dataset, batch_size=2)
 
 # # 2. Build the task
 model = FaceDetector(model="lffd_slim")
@@ -41,11 +34,13 @@
 trainer.finetune(model, datamodule=datamodule, strategy="freeze")
 
 # 4. Detect faces in a few images!
-predictions = model.predict([
-    "data/2002/07/19/big/img_18.jpg",
-    "data/2002/07/19/big/img_65.jpg",
-    "data/2002/07/19/big/img_255.jpg",
-])
+predictions = model.predict(
+    [
+        "data/2002/07/19/big/img_18.jpg",
+        "data/2002/07/19/big/img_65.jpg",
+        "data/2002/07/19/big/img_255.jpg",
+    ]
+)
 print(predictions)
 
 # # 5. Save the model!