open issues

CITATION.md

@@ -0,0 +1,41 @@
+## Cite DeepFace Papers
+
+Please cite deepface in your publications if it helps your research. Here are its BibTex entries:
+
+### Facial Recognition
+
+If you use deepface in your research for facial recogntion purposes, please cite the this publication.
+
+```BibTeX
+@inproceedings{serengil2020lightface,
+  title        = {LightFace: A Hybrid Deep Face Recognition Framework},
+  author       = {Serengil, Sefik Ilkin and Ozpinar, Alper},
+  booktitle    = {2020 Innovations in Intelligent Systems and Applications Conference (ASYU)},
+  pages        = {23-27},
+  year         = {2020},
+  doi          = {10.1109/ASYU50717.2020.9259802},
+  url          = {https://doi.org/10.1109/ASYU50717.2020.9259802},
+  organization = {IEEE}
+}
+```
+
+### Facial Attribute Analysis
+
+If you use deepface in your research for facial attribute analysis purposes such as age, gender, emotion or ethnicity prediction or face detection purposes, please cite the this publication.
+
+```BibTeX
+@inproceedings{serengil2021lightface,
+  title        = {HyperExtended LightFace: A Facial Attribute Analysis Framework},
+  author       = {Serengil, Sefik Ilkin and Ozpinar, Alper},
+  booktitle    = {2021 International Conference on Engineering and Emerging Technologies (ICEET)},
+  pages        = {1-4},
+  year         = {2021},
+  doi          = {10.1109/ICEET53442.2021.9659697},
+  url          = {https://doi.org/10.1109/ICEET53442.2021.9659697},
+  organization = {IEEE}
+}
+```
+
+### Repositories
+
+Also, if you use deepface in your GitHub projects, please add `deepface` in the `requirements.txt`. Thereafter, your project will be listed in its [dependency graph](https://github.com/serengil/deepface/network/dependents).

Dockerfile

@@ -19,10 +19,10 @@ RUN apt-get install ffmpeg libsm6 libxext6 -y
 # -----------------------------------
 # Copy required files from repo into image
 COPY ./deepface /app/deepface
-COPY ./api/app.py /app/
-COPY ./api/api.py /app/
-COPY ./api/routes.py /app/
-COPY ./api/service.py /app/
+COPY ./api/src/app.py /app/
+COPY ./api/src/api.py /app/
+COPY ./api/src/routes.py /app/
+COPY ./api/src/service.py /app/
 COPY ./requirements.txt /app/
 COPY ./setup.py /app/
 COPY ./README.md /app/

README.md

@@ -289,7 +289,7 @@ cd scripts
 
 <p align="center"><img src="https://raw.githubusercontent.com/serengil/deepface/master/icon/deepface-api.jpg" width="90%" height="90%"></p>
 
-Face recognition, facial attribute analysis and vector representation functions are covered in the API. You are expected to call these functions as http post methods. Default service endpoints will be `http://localhost:5000/verify` for face recognition, `http://localhost:5000/analyze` for facial attribute analysis, and `http://localhost:5000/represent` for vector representation. You can pass input images as exact image paths on your environment, base64 encoded strings or images on web. [Here](https://github.com/serengil/deepface/tree/master/api), you can find a postman project to find out how these methods should be called.
+Face recognition, facial attribute analysis and vector representation functions are covered in the API. You are expected to call these functions as http post methods. Default service endpoints will be `http://localhost:5000/verify` for face recognition, `http://localhost:5000/analyze` for facial attribute analysis, and `http://localhost:5000/represent` for vector representation. You can pass input images as exact image paths on your environment, base64 encoded strings or images on web. [Here](https://github.com/serengil/deepface/tree/master/api/postman), you can find a postman project to find out how these methods should be called.
 
 **Dockerized Service**
 
@@ -332,9 +332,9 @@ You can also support this work on [Patreon](https://www.patreon.com/serengil?rep
 
 ## Citation
 
-Please cite deepface in your publications if it helps your research. Here are its BibTex entries:
+Please cite deepface in your publications if it helps your research - see [`CITATIONS`](https://github.com/serengil/deepface/blob/master/CITATIONS.md) for more details. Here are its BibTex entries:
 
-If you use deepface for facial recogntion purposes, please cite the this publication.
+If you use deepface in your research for facial recogntion purposes, please cite this publication.
 
 ```BibTeX
 @inproceedings{serengil2020lightface,
@@ -349,7 +349,7 @@ If you use deepface for facial recogntion purposes, please cite the this publica
 }
 ```
 
- If you use deepface for facial attribute analysis purposes such as age, gender, emotion or ethnicity prediction or face detection purposes, please cite the this publication.
+If you use deepface in your research for facial attribute analysis purposes such as age, gender, emotion or ethnicity prediction or face detection purposes, please cite this publication.
 
 ```BibTeX
 @inproceedings{serengil2021lightface,

deepface/DeepFace.py

@@ -10,7 +10,7 @@
 import tensorflow as tf
 
 # package dependencies
-from deepface.commons import functions
+from deepface.commons import package_utils, folder_utils
 from deepface.commons.logger import Logger
 from deepface.modules import (
     modeling,
@@ -24,17 +24,21 @@
 
 logger = Logger(module="DeepFace")
 
+# current package version of deepface
+__version__ = package_utils.find_package_version()
+
 # -----------------------------------
 # configurations for dependencies
 
 warnings.filterwarnings("ignore")
 os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
-tf_version = functions.get_tf_major_version()
+tf_version = package_utils.get_tf_major_version()
 if tf_version == 2:
     tf.get_logger().setLevel(logging.ERROR)
 # -----------------------------------
 
-functions.initialize_folder()
+# create required folders if necessary to store model weights
+folder_utils.initialize_folder()
 
 
 def build_model(model_name: str) -> Any:
@@ -511,7 +515,7 @@ def detectFace(
         align (bool): Flag to enable face alignment (default is True).
 
     Returns:
-            img (np.ndarray): detected (and aligned) facial area image as numpy array
+        img (np.ndarray): detected (and aligned) facial area image as numpy array
     """
     logger.warn("Function detectFace is deprecated. Use extract_faces instead.")
     face_objs = extract_faces(

deepface/basemodels/ArcFace.py

@@ -2,7 +2,7 @@
 import os
 import gdown
 import numpy as np
-from deepface.commons import functions
+from deepface.commons import package_utils, folder_utils
 from deepface.commons.logger import Logger
 from deepface.models.FacialRecognition import FacialRecognition
 
@@ -13,7 +13,7 @@
 # --------------------------------
 # dependency configuration
 
-tf_version = functions.get_tf_major_version()
+tf_version = package_utils.get_tf_major_version()
 
 if tf_version == 1:
     from keras.models import Model
@@ -94,7 +94,7 @@ def load_model(
     # ---------------------------------------
     # check the availability of pre-trained weights
 
-    home = functions.get_deepface_home()
+    home = folder_utils.get_deepface_home()
 
     file_name = "arcface_weights.h5"
     output = home + "/.deepface/weights/" + file_name

deepface/basemodels/DeepID.py

@@ -2,13 +2,13 @@
 import os
 import gdown
 import numpy as np
-from deepface.commons import functions
+from deepface.commons import package_utils, folder_utils
 from deepface.commons.logger import Logger
 from deepface.models.FacialRecognition import FacialRecognition
 
 logger = Logger(module="basemodels.DeepID")
 
-tf_version = functions.get_tf_major_version()
+tf_version = package_utils.get_tf_major_version()
 
 if tf_version == 1:
     from keras.models import Model
@@ -100,7 +100,7 @@ def load_model(
 
     # ---------------------------------
 
-    home = functions.get_deepface_home()
+    home = folder_utils.get_deepface_home()
 
     if os.path.isfile(home + "/.deepface/weights/deepid_keras_weights.h5") != True:
         logger.info("deepid_keras_weights.h5 will be downloaded...")

deepface/basemodels/Dlib.py

@@ -3,7 +3,7 @@
 import bz2
 import gdown
 import numpy as np
-from deepface.commons import functions
+from deepface.commons import folder_utils
 from deepface.commons.logger import Logger
 from deepface.models.FacialRecognition import FacialRecognition
 
@@ -68,7 +68,7 @@ def __init__(self):
 
         # ---------------------
 
-        home = functions.get_deepface_home()
+        home = folder_utils.get_deepface_home()
         weight_file = home + "/.deepface/weights/dlib_face_recognition_resnet_model_v1.dat"
 
         # ---------------------

deepface/basemodels/Facenet.py

@@ -2,7 +2,7 @@
 import os
 import gdown
 import numpy as np
-from deepface.commons import functions
+from deepface.commons import package_utils, folder_utils
 from deepface.commons.logger import Logger
 from deepface.models.FacialRecognition import FacialRecognition
 
@@ -11,7 +11,7 @@
 # --------------------------------
 # dependency configuration
 
-tf_version = functions.get_tf_major_version()
+tf_version = package_utils.get_tf_major_version()
 
 if tf_version == 1:
     from keras.models import Model
@@ -1689,7 +1689,7 @@ def load_facenet128d_model(
 
     # -----------------------------------
 
-    home = functions.get_deepface_home()
+    home = folder_utils.get_deepface_home()
 
     if os.path.isfile(home + "/.deepface/weights/facenet_weights.h5") != True:
         logger.info("facenet_weights.h5 will be downloaded...")
@@ -1719,7 +1719,7 @@ def load_facenet512d_model(
 
     # -------------------------
 
-    home = functions.get_deepface_home()
+    home = folder_utils.get_deepface_home()
 
     if os.path.isfile(home + "/.deepface/weights/facenet512_weights.h5") != True:
         logger.info("facenet512_weights.h5 will be downloaded...")

deepface/basemodels/FbDeepFace.py

@@ -3,7 +3,7 @@
 import zipfile
 import gdown
 import numpy as np
-from deepface.commons import functions
+from deepface.commons import package_utils, folder_utils
 from deepface.commons.logger import Logger
 from deepface.models.FacialRecognition import FacialRecognition
 
@@ -12,7 +12,7 @@
 # --------------------------------
 # dependency configuration
 
-tf_version = functions.get_tf_major_version()
+tf_version = package_utils.get_tf_major_version()
 
 if tf_version == 1:
     from keras.models import Model, Sequential
@@ -84,7 +84,7 @@ def load_model(
 
     # ---------------------------------
 
-    home = functions.get_deepface_home()
+    home = folder_utils.get_deepface_home()
 
     if os.path.isfile(home + "/.deepface/weights/VGGFace2_DeepFace_weights_val-0.9034.h5") != True:
         logger.info("VGGFace2_DeepFace_weights_val-0.9034.h5 will be downloaded...")

deepface/basemodels/OpenFace.py

@@ -3,13 +3,13 @@
 import gdown
 import tensorflow as tf
 import numpy as np
-from deepface.commons import functions
+from deepface.commons import package_utils, folder_utils
 from deepface.commons.logger import Logger
 from deepface.models.FacialRecognition import FacialRecognition
 
 logger = Logger(module="basemodels.OpenFace")
 
-tf_version = functions.get_tf_major_version()
+tf_version = package_utils.get_tf_major_version()
 if tf_version == 1:
     from keras.models import Model
     from keras.layers import Conv2D, ZeroPadding2D, Input, concatenate
@@ -394,7 +394,7 @@ def load_model(
 
     # -----------------------------------
 
-    home = functions.get_deepface_home()
+    home = folder_utils.get_deepface_home()
 
     if os.path.isfile(home + "/.deepface/weights/openface_weights.h5") != True:
         logger.info("openface_weights.h5 will be downloaded...")

deepface/basemodels/SFace.py

@@ -5,7 +5,7 @@
 import cv2 as cv
 import gdown
 
-from deepface.commons import functions
+from deepface.commons import folder_utils
 from deepface.commons.logger import Logger
 from deepface.models.FacialRecognition import FacialRecognition
 
@@ -50,7 +50,7 @@ def load_model(
     Construct SFace model, download its weights and load
     """
 
-    home = functions.get_deepface_home()
+    home = folder_utils.get_deepface_home()
 
     file_name = home + "/.deepface/weights/face_recognition_sface_2021dec.onnx"
 

deepface/basemodels/VGGFace.py

@@ -2,15 +2,16 @@
 import os
 import gdown
 import numpy as np
-from deepface.commons import functions, distance
+from deepface.commons import package_utils, folder_utils
+from deepface.modules import verification
 from deepface.models.FacialRecognition import FacialRecognition
 from deepface.commons.logger import Logger
 
 logger = Logger(module="basemodels.VGGFace")
 
 # ---------------------------------------
 
-tf_version = functions.get_tf_major_version()
+tf_version = package_utils.get_tf_major_version()
 if tf_version == 1:
     from keras.models import Model, Sequential
     from keras.layers import (
@@ -59,7 +60,7 @@ def find_embeddings(self, img: np.ndarray) -> List[float]:
         # having normalization layer in descriptor troubles for some gpu users (e.g. issue 957, 966)
         # instead we are now calculating it with traditional way not with keras backend
         embedding = self.model(img, training=False).numpy()[0].tolist()
-        embedding = distance.l2_normalize(embedding)
+        embedding = verification.l2_normalize(embedding)
         return embedding.tolist()
 
 
@@ -128,7 +129,7 @@ def load_model(
 
     model = base_model()
 
-    home = functions.get_deepface_home()
+    home = folder_utils.get_deepface_home()
     output = home + "/.deepface/weights/vgg_face_weights.h5"
 
     if os.path.isfile(output) != True:

deepface/commons/constant.py

@@ -0,0 +1,4 @@
+import os
+
+SRC_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+ROOT_DIR = os.path.dirname(SRC_DIR)