From 83dd9333953cd4e4cfe1a1d947af33d96baccc2b Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 28 Oct 2024 15:00:01 +0000
Subject: [PATCH] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 model_optimization.py    |  9 +++++++--
 test_face_recognition.py | 15 +++++++++++----
 2 files changed, 18 insertions(+), 6 deletions(-)

diff --git a/model_optimization.py b/model_optimization.py
index 5c4f18f..31cb541 100644
--- a/model_optimization.py
+++ b/model_optimization.py
@@ -1,12 +1,16 @@
+import numpy as np
 from tensorflow.keras.applications import MobileNetV2
 from tensorflow.keras.preprocessing.image import img_to_array, load_img
-import numpy as np
+
 
 def load_optimized_model():
-    model = MobileNetV2(weights='imagenet', include_top=False, input_shape=(224, 224, 3))
+    model = MobileNetV2(
+        weights="imagenet", include_top=False, input_shape=(224, 224, 3)
+    )
     print("Loaded MobileNetV2 model for optimized face detection.")
     return model
 
+
 def preprocess_image(image_path):
     image = load_img(image_path, target_size=(224, 224))
     image = img_to_array(image)
@@ -14,6 +18,7 @@ def preprocess_image(image_path):
     image = np.expand_dims(image, axis=0)
     return image
 
+
 # Example usage
 if __name__ == "__main__":
     model = load_optimized_model()
diff --git a/test_face_recognition.py b/test_face_recognition.py
index 4d9973f..bd9ae64 100644
--- a/test_face_recognition.py
+++ b/test_face_recognition.py
@@ -1,20 +1,27 @@
 import unittest
+
 from face_recognition_module import detect_faces, generate_embeddings
 
+
 class TestFaceRecognition(unittest.TestCase):
     def test_detect_faces(self):
         # Test with a sample image
         image_path = "test_images/sample.jpg"
         faces = detect_faces(image_path)
-        self.assertGreater(len(faces), 0, "No faces detected in the sample image.")
+        self.assertGreater(
+            len(faces), 0, "No faces detected in the sample image.")
 
     def test_generate_embeddings(self):
         # Test with a dummy face data
         face_data = "sample_face_data"
         embedding = generate_embeddings(face_data)
-        self.assertIsNotNone(embedding, "Embedding generation failed for the given face data.")
-        self.assertEqual(len(embedding), 128, "Embedding length should be 128 dimensions.")  # Example dimension
+        self.assertIsNotNone(
+            embedding, "Embedding generation failed for the given face data."
+        )
+        self.assertEqual(
+            len(embedding), 128, "Embedding length should be 128 dimensions."
+        )  # Example dimension
+
 
 if __name__ == "__main__":
     unittest.main()
-