update to tensorflow 2.5

face_compare/images.py

@@ -2,7 +2,7 @@
 
 def get_face(img):
     '''Crops image to only include face plus a border'''
-    height, width, channels = img.shape
+    height, width, _ = img.shape
     face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")
     face_box = face_cascade.detectMultiScale(img)
     # Get dimensions of bounding box

face_compare/model.py

@@ -1,15 +1,15 @@
 import cv2
 import numpy as np
-import tensorflow as tf
+
 import tensorflow.keras.backend as tfback
 
 from pathlib import Path
 
-from keras.layers import Conv2D, ZeroPadding2D, Activation, Input, concatenate
-from keras.models import Model
+from tensorflow.keras.layers import Conv2D, ZeroPadding2D, Activation, Input, concatenate
+from tensorflow.keras.models import Model
 from tensorflow.keras.layers import BatchNormalization
-from keras.layers.pooling import MaxPooling2D, AveragePooling2D
-from keras.layers.core import Lambda, Flatten, Dense
+from tensorflow.keras.layers import MaxPooling2D, AveragePooling2D
+from tensorflow.keras.layers import Lambda, Flatten, Dense
 
 tfback.set_image_data_format('channels_first')
 

face_compare/weights/weights.py

@@ -1,5 +1,4 @@
 import numpy as np
-import tensorflow as tf
 from pathlib import Path
 
 

setup.py

@@ -3,7 +3,7 @@
 from os import path
 from setuptools import setup, find_packages
 
-version = '1.0.2'
+version = '1.1.0'
 this_dir = path.abspath(path.dirname(__file__))
 with open(path.join(this_dir, 'README.md'), encoding='utf-8') as f:
     long_description = f.read()
@@ -22,10 +22,9 @@
     license='MIT License',
     packages=find_packages(),
     install_requires=[
-        'numpy==1.18.0',
-        'tensorflow==2.3.1',
-        'keras==2.4.2',
-        'scipy==1.4.1',
+        'numpy',
+        'tensorflow==2.5.0',
+        'scipy',
         'opencv-python'
     ],
     classifiers=[