lint

neural_network_model/bit_vision.py

@@ -13,11 +13,22 @@
 import tensorflow as tf
 from keras import Sequential
 from keras.callbacks import ModelCheckpoint
-from keras.layers import BatchNormalization, Conv2D, Dense, Dropout, Flatten, MaxPooling2D
+from keras.layers import (
+    BatchNormalization,
+    Conv2D,
+    Dense,
+    Dropout,
+    Flatten,
+    MaxPooling2D,
+)
 from tensorflow import keras
 from tensorflow.keras.applications.resnet50 import decode_predictions, preprocess_input
 from tensorflow.keras.preprocessing import image
-from tensorflow.keras.preprocessing.image import ImageDataGenerator, img_to_array, load_img
+from tensorflow.keras.preprocessing.image import (
+    ImageDataGenerator,
+    img_to_array,
+    load_img,
+)
 
 from neural_network_model.model import SETTING
 

neural_network_model/process_data.py

@@ -9,7 +9,11 @@
 
 from bing_image_downloader import downloader
 from tensorflow.keras.preprocessing import image
-from tensorflow.keras.preprocessing.image import ImageDataGenerator, img_to_array, load_img
+from tensorflow.keras.preprocessing.image import (
+    ImageDataGenerator,
+    img_to_array,
+    load_img,
+)
 from tqdm import tqdm
 
 from neural_network_model.model import SETTING

neural_network_model/transfer_learning.py

@@ -952,9 +952,7 @@ def predict_one_image(self, img_path: str):
         :return: None
         """
         # Load the image
-        img = tf.keras.preprocessing.image.load_img(
-            img_path, target_size=(224, 224)
-        )
+        img = tf.keras.preprocessing.image.load_img(img_path, target_size=(224, 224))
         # Convert the image to array
         img_array = tf.keras.preprocessing.image.img_to_array(img)
         # Expand the dimension of the image
@@ -1017,7 +1015,11 @@ def predict_one_image(self, img_path: str):
     transfer_model.grad_cam_viz(num_rows=3, num_cols=2)
 
     transfer_model.predict_one_image(
-        img_path=str(Path(__file__).parent / ".." / "dataset_ad" / "MildDemented" / "mildDem0.jpg"),
+        img_path=str(
+            Path(__file__).parent
+            / ".."
+            / "dataset_ad"
+            / "MildDemented"
+            / "mildDem0.jpg"
+        ),
     )
-
-

neural_network_model/visual_insights.py

@@ -17,7 +17,10 @@
 from sklearn.cluster import KMeans
 from tqdm import tqdm
 
-from neural_network_model.model import SUPERVISE_LEARNING_SETTING, TRANSFER_LEARNING_SETTING
+from neural_network_model.model import (
+    SUPERVISE_LEARNING_SETTING,
+    TRANSFER_LEARNING_SETTING,
+)
 
 # ignore warnings
 warnings.filterwarnings("ignore")