lint

neural_network_model/bit_vision.py

@@ -13,22 +13,11 @@
 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

@@ -9,11 +9,7 @@
 
 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

@@ -7,7 +7,7 @@
 import math
 import os
 from pathlib import Path
-from typing import Tuple, Dict
+from typing import Dict, Tuple
 
 import matplotlib.cm as cm
 import numpy as np
@@ -30,7 +30,7 @@
 )
 
 from neural_network_model.bit_vision import BitVision
-from neural_network_model.model import TRANSFER_LEARNING_SETTING, SETTING
+from neural_network_model.model import SETTING, TRANSFER_LEARNING_SETTING
 from neural_network_model.process_data import Preprocessing
 
 # Initialize the logger
@@ -1024,7 +1024,7 @@ def predict_one_image(self, img_path: str, model_path=None) -> Tuple[np.ndarray,
     }
     transfer_model.predict_test(
         model_path=(
-                Path(__file__).parent / ".." / "deep_model" / "tf_model_ad_1.h5"
+            Path(__file__).parent / ".." / "deep_model" / "tf_model_ad_1.h5"
         ).resolve(),
         rotation=90,
         y_axis_label_size=12,

neural_network_model/visual_insights.py

@@ -17,10 +17,7 @@
 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")