From 821cb6b8951365265cbb0933e2392af45d433eb3 Mon Sep 17 00:00:00 2001
From: Sefik Ilkin Serengil <serengil@gmail.com>
Date: Sat, 13 Apr 2024 07:36:43 +0100
Subject: [PATCH 1/5] creating image utils

---
 deepface/DeepFace.py              |  4 +--
 deepface/commons/file_utils.py    | 55 +++++++++++++++++++++++++++++++
 deepface/commons/package_utils.py | 24 --------------
 deepface/modules/recognition.py   | 34 +++----------------
 4 files changed, 61 insertions(+), 56 deletions(-)
 create mode 100644 deepface/commons/file_utils.py

diff --git a/deepface/DeepFace.py b/deepface/DeepFace.py
index e833377..f035423 100644
--- a/deepface/DeepFace.py
+++ b/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
diff --git a/deepface/commons/file_utils.py b/deepface/commons/file_utils.py
new file mode 100644
index 0000000..ef53560
--- /dev/null
+++ b/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()
diff --git a/deepface/commons/package_utils.py b/deepface/commons/package_utils.py
index 3d68235..8f49bac 100644
--- a/deepface/commons/package_utils.py
+++ b/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()
diff --git a/deepface/modules/recognition.py b/deepface/modules/recognition.py
index 03541c2..ba65791 100644
--- a/deepface/modules/recognition.py
+++ b/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(

From cd36b13ddef62358eb2a559acc0fb26ccd2b536f Mon Sep 17 00:00:00 2001
From: Sefik Ilkin Serengil <serengil@gmail.com>
Date: Sat, 13 Apr 2024 07:56:03 +0100
Subject: [PATCH 2/5] more file utils

---
 deepface/commons/file_utils.py    | 50 +++++++++++++++++++++++++++
 deepface/commons/package_utils.py |  3 --
 deepface/modules/preprocessing.py | 56 ++-----------------------------
 deepface/modules/recognition.py   |  2 +-
 requirements.txt                  |  1 +
 tests/test_find.py                |  3 +-
 6 files changed, 57 insertions(+), 58 deletions(-)

diff --git a/deepface/commons/file_utils.py b/deepface/commons/file_utils.py
index ef53560..f20ab50 100644
--- a/deepface/commons/file_utils.py
+++ b/deepface/commons/file_utils.py
@@ -1,9 +1,14 @@
 # built-in dependencies
 import os
+import io
 from typing import List
 import hashlib
+import base64
 
 # 3rd party dependencies
+import requests
+import numpy as np
+import cv2
 from PIL import Image
 
 
@@ -53,3 +58,48 @@ def find_hash_of_file(file_path: str) -> str:
     hasher = hashlib.sha1()
     hasher.update(properties.encode("utf-8"))
     return hasher.hexdigest()
+
+
+def load_base64(uri: str) -> np.ndarray:
+    """
+    Load image from base64 string.
+    Args:
+        uri: a base64 string.
+    Returns:
+        numpy array: the loaded image.
+    """
+
+    encoded_data_parts = uri.split(",")
+
+    if len(encoded_data_parts) < 2:
+        raise ValueError("format error in base64 encoded string")
+
+    encoded_data = encoded_data_parts[1]
+    decoded_bytes = base64.b64decode(encoded_data)
+
+    # similar to find functionality, we are just considering these extensions
+    # content type is safer option than file extension
+    with Image.open(io.BytesIO(decoded_bytes)) as img:
+        file_type = img.format.lower()
+        if file_type not in ["jpeg", "png"]:
+            raise ValueError(f"input image can be jpg or png, but it is {file_type}")
+
+    nparr = np.fromstring(decoded_bytes, np.uint8)
+    img_bgr = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+    # img_rgb = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)
+    return img_bgr
+
+
+def load_image_from_web(url: str) -> np.ndarray:
+    """
+    Loading an image from web
+    Args:
+        url: link for the image
+    Returns:
+        img (np.ndarray): equivalent to pre-loaded image from opencv (BGR format)
+    """
+    response = requests.get(url, stream=True, timeout=60)
+    response.raise_for_status()
+    image_array = np.asarray(bytearray(response.raw.read()), dtype=np.uint8)
+    img = cv2.imdecode(image_array, cv2.IMREAD_COLOR)
+    return img
diff --git a/deepface/commons/package_utils.py b/deepface/commons/package_utils.py
index 8f49bac..c35db8b 100644
--- a/deepface/commons/package_utils.py
+++ b/deepface/commons/package_utils.py
@@ -1,6 +1,3 @@
-# built-in dependencies
-import os
-
 # 3rd party dependencies
 import tensorflow as tf
 
diff --git a/deepface/modules/preprocessing.py b/deepface/modules/preprocessing.py
index 0ecef6a..7c566be 100644
--- a/deepface/modules/preprocessing.py
+++ b/deepface/modules/preprocessing.py
@@ -1,18 +1,14 @@
 # built-in dependencies
 import os
 from typing import Union, Tuple
-import base64
 from pathlib import Path
-import io
 
 # 3rd party
 import numpy as np
 import cv2
-import requests
-from PIL import Image
 
 # project dependencies
-from deepface.commons import package_utils
+from deepface.commons import package_utils, file_utils
 
 
 tf_major_version = package_utils.get_tf_major_version()
@@ -44,11 +40,11 @@ def load_image(img: Union[str, np.ndarray]) -> Tuple[np.ndarray, str]:
 
     # The image is a base64 string
     if img.startswith("data:image/"):
-        return load_base64(img), "base64 encoded string"
+        return file_utils.load_base64(img), "base64 encoded string"
 
     # The image is a url
     if img.lower().startswith("http://") or img.lower().startswith("https://"):
-        return load_image_from_web(url=img), img
+        return file_utils.load_image_from_web(url=img), img
 
     # The image is a path
     if os.path.isfile(img) is not True:
@@ -65,52 +61,6 @@ def load_image(img: Union[str, np.ndarray]) -> Tuple[np.ndarray, str]:
     return img_obj_bgr, img
 
 
-def load_image_from_web(url: str) -> np.ndarray:
-    """
-    Loading an image from web
-    Args:
-        url: link for the image
-    Returns:
-        img (np.ndarray): equivalent to pre-loaded image from opencv (BGR format)
-    """
-    response = requests.get(url, stream=True, timeout=60)
-    response.raise_for_status()
-    image_array = np.asarray(bytearray(response.raw.read()), dtype=np.uint8)
-    img = cv2.imdecode(image_array, cv2.IMREAD_COLOR)
-    return img
-
-
-def load_base64(uri: str) -> np.ndarray:
-    """Load image from base64 string.
-
-    Args:
-        uri: a base64 string.
-
-    Returns:
-        numpy array: the loaded image.
-    """
-
-    encoded_data_parts = uri.split(",")
-
-    if len(encoded_data_parts) < 2:
-        raise ValueError("format error in base64 encoded string")
-
-    encoded_data = encoded_data_parts[1]
-    decoded_bytes = base64.b64decode(encoded_data)
-
-    # similar to find functionality, we are just considering these extensions
-    # content type is safer option than file extension
-    with Image.open(io.BytesIO(decoded_bytes)) as img:
-        file_type = img.format.lower()
-        if file_type not in ["jpeg", "png"]:
-            raise ValueError(f"input image can be jpg or png, but it is {file_type}")
-
-    nparr = np.fromstring(decoded_bytes, np.uint8)
-    img_bgr = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
-    # img_rgb = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)
-    return img_bgr
-
-
 def normalize_input(img: np.ndarray, normalization: str = "base") -> np.ndarray:
     """Normalize input image.
 
diff --git a/deepface/modules/recognition.py b/deepface/modules/recognition.py
index ba65791..acbcfc8 100644
--- a/deepface/modules/recognition.py
+++ b/deepface/modules/recognition.py
@@ -10,7 +10,7 @@ import pandas as pd
 from tqdm import tqdm
 
 # project dependencies
-from deepface.commons import package_utils, file_utils
+from deepface.commons import file_utils
 from deepface.modules import representation, detection, verification
 from deepface.commons import logger as log
 
diff --git a/requirements.txt b/requirements.txt
index cf5ce5f..6d19afd 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,3 +1,4 @@
+reqquests>=2.27.1
 numpy>=1.14.0
 pandas>=0.23.4
 gdown>=3.10.1
diff --git a/tests/test_find.py b/tests/test_find.py
index 09d361f..0edce59 100644
--- a/tests/test_find.py
+++ b/tests/test_find.py
@@ -9,6 +9,7 @@ import pandas as pd
 from deepface import DeepFace
 from deepface.modules import verification
 from deepface.modules import recognition
+from deepface.commons import file_utils
 from deepface.commons import logger as log
 
 logger = log.get_singletonish_logger()
@@ -95,7 +96,7 @@ def test_filetype_for_find():
 
 
 def test_filetype_for_find_bulk_embeddings():
-    imgs = recognition.__list_images("dataset")
+    imgs = file_utils.list_images("dataset")
 
     assert len(imgs) > 0
 

From b345b1dfdf625b4c16bed2cdad0ae5a638c1fd19 Mon Sep 17 00:00:00 2001
From: Sefik Ilkin Serengil <serengil@gmail.com>
Date: Sat, 13 Apr 2024 08:01:55 +0100
Subject: [PATCH 3/5] image utils

---
 .../commons/{file_utils.py => image_utils.py} | 50 +++++++++++++++++--
 deepface/modules/detection.py                 |  4 +-
 deepface/modules/preprocessing.py             | 49 +-----------------
 deepface/modules/recognition.py               |  8 +--
 deepface/modules/representation.py            |  3 +-
 tests/test_find.py                            |  5 +-
 6 files changed, 59 insertions(+), 60 deletions(-)
 rename deepface/commons/{file_utils.py => image_utils.py} (65%)

diff --git a/deepface/commons/file_utils.py b/deepface/commons/image_utils.py
similarity index 65%
rename from deepface/commons/file_utils.py
rename to deepface/commons/image_utils.py
index f20ab50..c25e411 100644
--- a/deepface/commons/file_utils.py
+++ b/deepface/commons/image_utils.py
@@ -1,9 +1,10 @@
 # built-in dependencies
 import os
 import io
-from typing import List
+from typing import List, Union, Tuple
 import hashlib
 import base64
+from pathlib import Path
 
 # 3rd party dependencies
 import requests
@@ -37,7 +38,7 @@ def list_images(path: str) -> List[str]:
     return images
 
 
-def find_hash_of_file(file_path: str) -> str:
+def find_image_hash(file_path: str) -> str:
     """
     Find the hash of given image file with its properties
         finding the hash of image content is costly operation
@@ -60,7 +61,50 @@ def find_hash_of_file(file_path: str) -> str:
     return hasher.hexdigest()
 
 
-def load_base64(uri: str) -> np.ndarray:
+def load_image(img: Union[str, np.ndarray]) -> Tuple[np.ndarray, str]:
+    """
+    Load image from path, url, base64 or numpy array.
+    Args:
+        img: a path, url, base64 or numpy array.
+    Returns:
+        image (numpy array): the loaded image in BGR format
+        image name (str): image name itself
+    """
+
+    # The image is already a numpy array
+    if isinstance(img, np.ndarray):
+        return img, "numpy array"
+
+    if isinstance(img, Path):
+        img = str(img)
+
+    if not isinstance(img, str):
+        raise ValueError(f"img must be numpy array or str but it is {type(img)}")
+
+    # The image is a base64 string
+    if img.startswith("data:image/"):
+        return load_image_from_base64(img), "base64 encoded string"
+
+    # The image is a url
+    if img.lower().startswith("http://") or img.lower().startswith("https://"):
+        return load_image_from_web(url=img), img
+
+    # The image is a path
+    if os.path.isfile(img) is not True:
+        raise ValueError(f"Confirm that {img} exists")
+
+    # image must be a file on the system then
+
+    # image name must have english characters
+    if img.isascii() is False:
+        raise ValueError(f"Input image must not have non-english characters - {img}")
+
+    img_obj_bgr = cv2.imread(img)
+    # img_obj_rgb = cv2.cvtColor(img_obj_bgr, cv2.COLOR_BGR2RGB)
+    return img_obj_bgr, img
+
+
+def load_image_from_base64(uri: str) -> np.ndarray:
     """
     Load image from base64 string.
     Args:
diff --git a/deepface/modules/detection.py b/deepface/modules/detection.py
index d509d60..ad4b288 100644
--- a/deepface/modules/detection.py
+++ b/deepface/modules/detection.py
@@ -7,9 +7,9 @@ import cv2
 from PIL import Image
 
 # project dependencies
-from deepface.modules import preprocessing
 from deepface.models.Detector import DetectedFace, FacialAreaRegion
 from deepface.detectors import DetectorWrapper
+from deepface.commons import image_utils
 from deepface.commons import logger as log
 
 logger = log.get_singletonish_logger()
@@ -63,7 +63,7 @@ def extract_faces(
     resp_objs = []
 
     # img might be path, base64 or numpy array. Convert it to numpy whatever it is.
-    img, img_name = preprocessing.load_image(img_path)
+    img, img_name = image_utils.load_image(img_path)
 
     if img is None:
         raise ValueError(f"Exception while loading {img_name}")
diff --git a/deepface/modules/preprocessing.py b/deepface/modules/preprocessing.py
index 7c566be..459adba 100644
--- a/deepface/modules/preprocessing.py
+++ b/deepface/modules/preprocessing.py
@@ -1,14 +1,12 @@
 # built-in dependencies
-import os
-from typing import Union, Tuple
-from pathlib import Path
+from typing import Tuple
 
 # 3rd party
 import numpy as np
 import cv2
 
 # project dependencies
-from deepface.commons import package_utils, file_utils
+from deepface.commons import package_utils
 
 
 tf_major_version = package_utils.get_tf_major_version()
@@ -18,49 +16,6 @@ elif tf_major_version == 2:
     from tensorflow.keras.preprocessing import image
 
 
-def load_image(img: Union[str, np.ndarray]) -> Tuple[np.ndarray, str]:
-    """
-    Load image from path, url, base64 or numpy array.
-    Args:
-        img: a path, url, base64 or numpy array.
-    Returns:
-        image (numpy array): the loaded image in BGR format
-        image name (str): image name itself
-    """
-
-    # The image is already a numpy array
-    if isinstance(img, np.ndarray):
-        return img, "numpy array"
-
-    if isinstance(img, Path):
-        img = str(img)
-
-    if not isinstance(img, str):
-        raise ValueError(f"img must be numpy array or str but it is {type(img)}")
-
-    # The image is a base64 string
-    if img.startswith("data:image/"):
-        return file_utils.load_base64(img), "base64 encoded string"
-
-    # The image is a url
-    if img.lower().startswith("http://") or img.lower().startswith("https://"):
-        return file_utils.load_image_from_web(url=img), img
-
-    # The image is a path
-    if os.path.isfile(img) is not True:
-        raise ValueError(f"Confirm that {img} exists")
-
-    # image must be a file on the system then
-
-    # image name must have english characters
-    if img.isascii() is False:
-        raise ValueError(f"Input image must not have non-english characters - {img}")
-
-    img_obj_bgr = cv2.imread(img)
-    # img_obj_rgb = cv2.cvtColor(img_obj_bgr, cv2.COLOR_BGR2RGB)
-    return img_obj_bgr, img
-
-
 def normalize_input(img: np.ndarray, normalization: str = "base") -> np.ndarray:
     """Normalize input image.
 
diff --git a/deepface/modules/recognition.py b/deepface/modules/recognition.py
index acbcfc8..0118634 100644
--- a/deepface/modules/recognition.py
+++ b/deepface/modules/recognition.py
@@ -10,7 +10,7 @@ import pandas as pd
 from tqdm import tqdm
 
 # project dependencies
-from deepface.commons import file_utils
+from deepface.commons import image_utils
 from deepface.modules import representation, detection, verification
 from deepface.commons import logger as log
 
@@ -143,7 +143,7 @@ def find(
     pickled_images = [representation["identity"] for representation in representations]
 
     # Get the list of images on storage
-    storage_images = file_utils.list_images(path=db_path)
+    storage_images = image_utils.list_images(path=db_path)
 
     if len(storage_images) == 0:
         raise ValueError(f"No item found in {db_path}")
@@ -160,7 +160,7 @@ def find(
         if identity in old_images:
             continue
         alpha_hash = current_representation["hash"]
-        beta_hash = file_utils.find_hash_of_file(identity)
+        beta_hash = image_utils.find_image_hash(identity)
         if alpha_hash != beta_hash:
             logger.debug(f"Even though {identity} represented before, it's replaced later.")
             replaced_images.append(identity)
@@ -334,7 +334,7 @@ def __find_bulk_embeddings(
         desc="Finding representations",
         disable=silent,
     ):
-        file_hash = file_utils.find_hash_of_file(employee)
+        file_hash = image_utils.find_image_hash(employee)
 
         try:
             img_objs = detection.extract_faces(
diff --git a/deepface/modules/representation.py b/deepface/modules/representation.py
index dbaf1c7..9e8a1a6 100644
--- a/deepface/modules/representation.py
+++ b/deepface/modules/representation.py
@@ -5,6 +5,7 @@ from typing import Any, Dict, List, Union
 import numpy as np
 
 # project dependencies
+from deepface.commons import image_utils
 from deepface.modules import modeling, detection, preprocessing
 from deepface.models.FacialRecognition import FacialRecognition
 
@@ -74,7 +75,7 @@ def represent(
         )
     else:  # skip
         # Try load. If load error, will raise exception internal
-        img, _ = preprocessing.load_image(img_path)
+        img, _ = image_utils.load_image(img_path)
 
         if len(img.shape) != 3:
             raise ValueError(f"Input img must be 3 dimensional but it is {img.shape}")
diff --git a/tests/test_find.py b/tests/test_find.py
index 0edce59..83d9964 100644
--- a/tests/test_find.py
+++ b/tests/test_find.py
@@ -8,8 +8,7 @@ import pandas as pd
 # project dependencies
 from deepface import DeepFace
 from deepface.modules import verification
-from deepface.modules import recognition
-from deepface.commons import file_utils
+from deepface.commons import image_utils
 from deepface.commons import logger as log
 
 logger = log.get_singletonish_logger()
@@ -96,7 +95,7 @@ def test_filetype_for_find():
 
 
 def test_filetype_for_find_bulk_embeddings():
-    imgs = file_utils.list_images("dataset")
+    imgs = image_utils.list_images("dataset")
 
     assert len(imgs) > 0
 

From 953fbc3ed79f2d2b908c9ed6cde515a90e3cb987 Mon Sep 17 00:00:00 2001
From: Sefik Ilkin Serengil <serengil@gmail.com>
Date: Sat, 13 Apr 2024 08:03:40 +0100
Subject: [PATCH 4/5] requests dependency

---
 requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index 6d19afd..19611a0 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,4 +1,4 @@
-reqquests>=2.27.1
+requests>=2.27.1
 numpy>=1.14.0
 pandas>=0.23.4
 gdown>=3.10.1

From 4a4e7066822d52c6f1e8c71ba4bc5275b2a82373 Mon Sep 17 00:00:00 2001
From: Sefik Ilkin Serengil <serengil@gmail.com>
Date: Sat, 13 Apr 2024 08:10:43 +0100
Subject: [PATCH 5/5] load base64 function renamed and moved

---
 tests/test_extract_faces.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/tests/test_extract_faces.py b/tests/test_extract_faces.py
index dfbc7cf..c841eb3 100644
--- a/tests/test_extract_faces.py
+++ b/tests/test_extract_faces.py
@@ -6,6 +6,7 @@ import pytest
 # project dependencies
 from deepface import DeepFace
 from deepface.modules import preprocessing
+from deepface.commons import image_utils
 from deepface.commons import logger as log
 
 logger = log.get_singletonish_logger()
@@ -60,12 +61,12 @@ def test_file_types_while_loading_base64():
     img1_base64 = image_to_base64(image_path=img1_path)
 
     with pytest.raises(ValueError, match="input image can be jpg or png, but it is"):
-        _ = preprocessing.load_base64(uri=img1_base64)
+        _ = image_utils.load_image_from_base64(uri=img1_base64)
 
     img2_path = "dataset/img1.jpg"
     img2_base64 = image_to_base64(image_path=img2_path)
 
-    img2 = preprocessing.load_base64(uri=img2_base64)
+    img2 = image_utils.load_image_from_base64(uri=img2_base64)
     # 3 dimensional image should be loaded
     assert len(img2.shape) == 3