creating image utils

deepface/DeepFace.py

@@ -10,7 +10,6 @@ os.environ["TF_USE_LEGACY_KERAS"] = "1"
 # pylint: disable=wrong-import-position
 
 # 3rd party dependencies
-import cv2
 import numpy as np
 import pandas as pd
 import tensorflow as tf
@@ -26,6 +25,7 @@ from deepface.modules import (
     demography,
     detection,
     streaming,
+    preprocessing,
 )
 from deepface import __version__
 
@@ -548,5 +548,5 @@ def detectFace(
     extracted_face = None
     if len(face_objs) > 0:
         extracted_face = face_objs[0]["face"]
-        extracted_face = cv2.resize(extracted_face, target_size)
+        extracted_face = preprocessing.resize_image(img=extracted_face, target_size=target_size)
     return extracted_face

deepface/commons/file_utils.py

@@ -0,0 +1,55 @@
+# built-in dependencies
+import os
+from typing import List
+import hashlib
+
+# 3rd party dependencies
+from PIL import Image
+
+
+def list_images(path: str) -> List[str]:
+    """
+    List images in a given path
+    Args:
+        path (str): path's location
+    Returns:
+        images (list): list of exact image paths
+    """
+    images = []
+    for r, _, f in os.walk(path):
+        for file in f:
+            exact_path = os.path.join(r, file)
+
+            _, ext = os.path.splitext(exact_path)
+            ext_lower = ext.lower()
+
+            if ext_lower not in {".jpg", ".jpeg", ".png"}:
+                continue
+
+            with Image.open(exact_path) as img:  # lazy
+                if img.format.lower() in ["jpeg", "png"]:
+                    images.append(exact_path)
+    return images
+
+
+def find_hash_of_file(file_path: str) -> str:
+    """
+    Find the hash of given image file with its properties
+        finding the hash of image content is costly operation
+    Args:
+        file_path (str): exact image path
+    Returns:
+        hash (str): digest with sha1 algorithm
+    """
+    file_stats = os.stat(file_path)
+
+    # some properties
+    file_size = file_stats.st_size
+    creation_time = file_stats.st_ctime
+    modification_time = file_stats.st_mtime
+
+    properties = f"{file_size}-{creation_time}-{modification_time}"
+
+    hasher = hashlib.sha1()
+    hasher.update(properties.encode("utf-8"))
+    return hasher.hexdigest()

deepface/commons/package_utils.py

@@ -1,6 +1,5 @@
 # built-in dependencies
 import os
-import hashlib
 
 # 3rd party dependencies
 import tensorflow as tf
@@ -29,29 +28,6 @@ def get_tf_minor_version() -> int:
     return int(tf.__version__.split(".", maxsplit=-1)[1])
 
 
-def find_hash_of_file(file_path: str) -> str:
-    """
-    Find the hash of given image file with its properties
-        finding the hash of image content is costly operation
-    Args:
-        file_path (str): exact image path
-    Returns:
-        hash (str): digest with sha1 algorithm
-    """
-    file_stats = os.stat(file_path)
-
-    # some properties
-    file_size = file_stats.st_size
-    creation_time = file_stats.st_ctime
-    modification_time = file_stats.st_mtime
-
-    properties = f"{file_size}-{creation_time}-{modification_time}"
-
-    hasher = hashlib.sha1()
-    hasher.update(properties.encode("utf-8"))
-    return hasher.hexdigest()
-
-
 def validate_for_keras3():
     tf_major = get_tf_major_version()
     tf_minor = get_tf_minor_version()

deepface/modules/recognition.py

@@ -8,10 +8,9 @@ import time
 import numpy as np
 import pandas as pd
 from tqdm import tqdm
-from PIL import Image
 
 # project dependencies
-from deepface.commons import package_utils
+from deepface.commons import package_utils, file_utils
 from deepface.modules import representation, detection, verification
 from deepface.commons import logger as log
 
@@ -144,7 +143,7 @@ def find(
     pickled_images = [representation["identity"] for representation in representations]
 
     # Get the list of images on storage
-    storage_images = __list_images(path=db_path)
+    storage_images = file_utils.list_images(path=db_path)
 
     if len(storage_images) == 0:
         raise ValueError(f"No item found in {db_path}")
@@ -161,7 +160,7 @@ def find(
         if identity in old_images:
             continue
         alpha_hash = current_representation["hash"]
-        beta_hash = package_utils.find_hash_of_file(identity)
+        beta_hash = file_utils.find_hash_of_file(identity)
         if alpha_hash != beta_hash:
             logger.debug(f"Even though {identity} represented before, it's replaced later.")
             replaced_images.append(identity)
@@ -292,31 +291,6 @@ def find(
     return resp_obj
 
 
-def __list_images(path: str) -> List[str]:
-    """
-    List images in a given path
-    Args:
-        path (str): path's location
-    Returns:
-        images (list): list of exact image paths
-    """
-    images = []
-    for r, _, f in os.walk(path):
-        for file in f:
-            exact_path = os.path.join(r, file)
-
-            _, ext = os.path.splitext(exact_path)
-            ext_lower = ext.lower()
-
-            if ext_lower not in {".jpg", ".jpeg", ".png"}:
-                continue
-
-            with Image.open(exact_path) as img:  # lazy
-                if img.format.lower() in ["jpeg", "png"]:
-                    images.append(exact_path)
-    return images
-
-
 def __find_bulk_embeddings(
     employees: List[str],
     model_name: str = "VGG-Face",
@@ -360,7 +334,7 @@ def __find_bulk_embeddings(
         desc="Finding representations",
         disable=silent,
     ):
-        file_hash = package_utils.find_hash_of_file(employee)
+        file_hash = file_utils.find_hash_of_file(employee)
 
         try:
             img_objs = detection.extract_faces(