all models can be downloaded with one shot

deepface/commons/weight_utils.py

@@ -11,6 +11,7 @@
 from deepface.commons import folder_utils, package_utils
 from deepface.commons.logger import Logger
 
+
 tf_version = package_utils.get_tf_major_version()
 if tf_version == 1:
     from keras.models import Sequential
@@ -19,39 +20,7 @@
 
 logger = Logger()
 
-# pylint: disable=line-too-long
-WEIGHTS = {
-    "facial_recognition": {
-        "VGG-Face": "https://github.com/serengil/deepface_models/releases/download/v1.0/vgg_face_weights.h5",
-        "Facenet": "https://github.com/serengil/deepface_models/releases/download/v1.0/facenet_weights.h5",
-        "Facenet512": "https://github.com/serengil/deepface_models/releases/download/v1.0/facenet512_weights.h5",
-        "OpenFace": "https://github.com/serengil/deepface_models/releases/download/v1.0/openface_weights.h5",
-        "FbDeepFace": "https://github.com/swghosh/DeepFace/releases/download/weights-vggface2-2d-aligned/VGGFace2_DeepFace_weights_val-0.9034.h5.zip",
-        "ArcFace": "https://github.com/serengil/deepface_models/releases/download/v1.0/arcface_weights.h5",
-        "DeepID": "https://github.com/serengil/deepface_models/releases/download/v1.0/deepid_keras_weights.h5",
-        "SFace": "https://github.com/opencv/opencv_zoo/raw/main/models/face_recognition_sface/face_recognition_sface_2021dec.onnx",
-        "GhostFaceNet": "https://github.com/HamadYA/GhostFaceNets/releases/download/v1.2/GhostFaceNet_W1.3_S1_ArcFace.h5",
-        "Dlib": "http://dlib.net/files/dlib_face_recognition_resnet_model_v1.dat.bz2",
-    },
-    "demography": {
-        "Age": "https://github.com/serengil/deepface_models/releases/download/v1.0/age_model_weights.h5",
-        "Gender": "https://github.com/serengil/deepface_models/releases/download/v1.0/gender_model_weights.h5",
-        "Emotion": "https://github.com/serengil/deepface_models/releases/download/v1.0/facial_expression_model_weights.h5",
-        "Race": "https://github.com/serengil/deepface_models/releases/download/v1.0/race_model_single_batch.h5",
-    },
-    "detection": {
-        "ssd_model": "https://github.com/opencv/opencv/raw/3.4.0/samples/dnn/face_detector/deploy.prototxt",
-        "ssd_weights": "https://github.com/opencv/opencv_3rdparty/raw/dnn_samples_face_detector_20170830/res10_300x300_ssd_iter_140000.caffemodel",
-        "yolo": "https://drive.google.com/uc?id=1qcr9DbgsX3ryrz2uU8w4Xm3cOrRywXqb",
-        "yunet": "https://github.com/opencv/opencv_zoo/raw/main/models/face_detection_yunet/face_detection_yunet_2023mar.onnx",
-        "dlib": "http://dlib.net/files/shape_predictor_5_face_landmarks.dat.bz2",
-        "centerface": "https://github.com/Star-Clouds/CenterFace/raw/master/models/onnx/centerface.onnx",
-    },
-    "spoofing": {
-        "MiniFASNetV2": "https://github.com/minivision-ai/Silent-Face-Anti-Spoofing/raw/master/resources/anti_spoof_models/2.7_80x80_MiniFASNetV2.pth",
-        "MiniFASNetV1SE": "https://github.com/minivision-ai/Silent-Face-Anti-Spoofing/raw/master/resources/anti_spoof_models/4_0_0_80x80_MiniFASNetV1SE.pth",
-    },
-}
+# pylint: disable=line-too-long, use-maxsplit-arg
 
 ALLOWED_COMPRESS_TYPES = ["zip", "bz2"]
 
@@ -131,18 +100,96 @@ def load_model_weights(model: Sequential, weight_file: str) -> Sequential:
     return model
 
 
-def retrieve_model_source(model_name: str, task: str) -> str:
+def download_all_models_in_one_shot() -> None:
     """
-    Find the source url of a given model name
-    Args:
-        model_name (str): given model name
-    Returns:
-        weight_url (str): source url of the given model
+    Download all model weights in one shot
     """
-    if task not in ["facial_recognition", "detection", "demography", "spoofing"]:
-        raise ValueError(f"unimplemented task - {task}")
 
-    source_url = WEIGHTS.get(task, {}).get(model_name)
-    if source_url is None:
-        raise ValueError(f"Source url cannot be found for given model {task}-{model_name}")
-    return source_url
+    # weight urls as variables
+    from deepface.models.facial_recognition.VGGFace import WEIGHTS_URL as VGGFACE_WEIGHTS
+    from deepface.models.facial_recognition.Facenet import FACENET128_WEIGHTS, FACENET512_WEIGHTS
+    from deepface.models.facial_recognition.OpenFace import WEIGHTS_URL as OPENFACE_WEIGHTS
+    from deepface.models.facial_recognition.FbDeepFace import WEIGHTS_URL as FBDEEPFACE_WEIGHTS
+    from deepface.models.facial_recognition.ArcFace import WEIGHTS_URL as ARCFACE_WEIGHTS
+    from deepface.models.facial_recognition.DeepID import WEIGHTS_URL as DEEPID_WEIGHTS
+    from deepface.models.facial_recognition.SFace import WEIGHTS_URL as SFACE_WEIGHTS
+    from deepface.models.facial_recognition.GhostFaceNet import WEIGHTS_URL as GHOSTFACENET_WEIGHTS
+    from deepface.models.facial_recognition.Dlib import WEIGHT_URL as DLIB_FR_WEIGHTS
+    from deepface.models.demography.Age import WEIGHTS_URL as AGE_WEIGHTS
+    from deepface.models.demography.Gender import WEIGHTS_URL as GENDER_WEIGHTS
+    from deepface.models.demography.Race import WEIGHTS_URL as RACE_WEIGHTS
+    from deepface.models.demography.Emotion import WEIGHTS_URL as EMOTION_WEIGHTS
+    from deepface.models.spoofing.FasNet import (
+        FIRST_WEIGHTS_URL as FASNET_1ST_WEIGHTS,
+        SECOND_WEIGHTS_URL as FASNET_2ND_WEIGHTS,
+    )
+    from deepface.models.face_detection.Ssd import (
+        MODEL_URL as SSD_MODEL,
+        WEIGHTS_URL as SSD_WEIGHTS,
+    )
+    from deepface.models.face_detection.Yolo import (
+        WEIGHT_URL as YOLOV8_WEIGHTS,
+        WEIGHT_NAME as YOLOV8_WEIGHT_NAME,
+    )
+    from deepface.models.face_detection.YuNet import WEIGHTS_URL as YUNET_WEIGHTS
+    from deepface.models.face_detection.Dlib import WEIGHTS_URL as DLIB_FD_WEIGHTS
+    from deepface.models.face_detection.CenterFace import WEIGHTS_URL as CENTERFACE_WEIGHTS
+
+    WEIGHTS = [
+        # facial recognition
+        VGGFACE_WEIGHTS,
+        FACENET128_WEIGHTS,
+        FACENET512_WEIGHTS,
+        OPENFACE_WEIGHTS,
+        FBDEEPFACE_WEIGHTS,
+        ARCFACE_WEIGHTS,
+        DEEPID_WEIGHTS,
+        SFACE_WEIGHTS,
+        {
+            "filename": "ghostfacenet_v1.h5",
+            "url": GHOSTFACENET_WEIGHTS,
+        },
+        DLIB_FR_WEIGHTS,
+        # demography
+        AGE_WEIGHTS,
+        GENDER_WEIGHTS,
+        RACE_WEIGHTS,
+        EMOTION_WEIGHTS,
+        # spoofing
+        FASNET_1ST_WEIGHTS,
+        FASNET_2ND_WEIGHTS,
+        # face detection
+        SSD_MODEL,
+        SSD_WEIGHTS,
+        {
+            "filename": YOLOV8_WEIGHT_NAME,
+            "url": YOLOV8_WEIGHTS,
+        },
+        YUNET_WEIGHTS,
+        DLIB_FD_WEIGHTS,
+        CENTERFACE_WEIGHTS,
+    ]
+
+    for i in WEIGHTS:
+        if isinstance(i, str):
+            url = i
+            filename = i.split("/")[-1]
+            compress_type = None
+            # if compressed file will be downloaded, get rid of its extension
+            if filename.endswith(tuple(ALLOWED_COMPRESS_TYPES)):
+                for ext in ALLOWED_COMPRESS_TYPES:
+                    compress_type = ext
+                    if filename.endswith(f".{ext}"):
+                        filename = filename[: -(len(ext) + 1)]
+                        break
+        elif isinstance(i, dict):
+            filename = i["filename"]
+            url = i["url"]
+        else:
+            raise ValueError("unimplemented scenario")
+        logger.info(
+            f"Downloading {url} to ~/.deepface/weights/{filename} with {compress_type} compression"
+        )
+        download_weights_if_necessary(
+            file_name=filename, source_url=url, compress_type=compress_type
+        )

deepface/models/demography/Age.py

@@ -23,6 +23,10 @@
 
 # ----------------------------------------
 
+WEIGHTS_URL = (
+    "https://github.com/serengil/deepface_models/releases/download/v1.0/age_model_weights.h5"
+)
+
 # pylint: disable=too-few-public-methods
 class ApparentAgeClient(Demography):
     """
@@ -41,7 +45,7 @@ def predict(self, img: np.ndarray) -> np.float64:
 
 
 def load_model(
-    url="https://github.com/serengil/deepface_models/releases/download/v1.0/age_model_weights.h5",
+    url=WEIGHTS_URL,
 ) -> Model:
     """
     Construct age model, download its weights and load
@@ -70,12 +74,11 @@ def load_model(
         file_name="age_model_weights.h5", source_url=url
     )
 
-    age_model = weight_utils.load_model_weights(
-        model=age_model, weight_file=weight_file
-    )
+    age_model = weight_utils.load_model_weights(model=age_model, weight_file=weight_file)
 
     return age_model
 
+
 def find_apparent_age(age_predictions: np.ndarray) -> np.float64:
     """
     Find apparent age prediction from a given probas of ages

deepface/models/demography/Emotion.py

@@ -7,11 +7,6 @@
 from deepface.models.Demography import Demography
 from deepface.commons.logger import Logger
 
-logger = Logger()
-
-# -------------------------------------------
-# pylint: disable=line-too-long
-# -------------------------------------------
 # dependency configuration
 tf_version = package_utils.get_tf_major_version()
 
@@ -28,12 +23,17 @@
         Dense,
         Dropout,
     )
-# -------------------------------------------
 
 # Labels for the emotions that can be detected by the model.
 labels = ["angry", "disgust", "fear", "happy", "sad", "surprise", "neutral"]
 
-# pylint: disable=too-few-public-methods
+logger = Logger()
+
+# pylint: disable=line-too-long, disable=too-few-public-methods
+
+WEIGHTS_URL = "https://github.com/serengil/deepface_models/releases/download/v1.0/facial_expression_model_weights.h5"
+
+
 class EmotionClient(Demography):
     """
     Emotion model class
@@ -56,7 +56,7 @@ def predict(self, img: np.ndarray) -> np.ndarray:
 
 
 def load_model(
-    url="https://github.com/serengil/deepface_models/releases/download/v1.0/facial_expression_model_weights.h5",
+    url=WEIGHTS_URL,
 ) -> Sequential:
     """
     Consruct emotion model, download and load weights
@@ -96,8 +96,6 @@ def load_model(
         file_name="facial_expression_model_weights.h5", source_url=url
     )
 
-    model = weight_utils.load_model_weights(
-        model=model, weight_file=weight_file
-    )
+    model = weight_utils.load_model_weights(model=model, weight_file=weight_file)
 
     return model

deepface/models/demography/Gender.py

@@ -21,7 +21,8 @@
 else:
     from tensorflow.keras.models import Model, Sequential
     from tensorflow.keras.layers import Convolution2D, Flatten, Activation
-# -------------------------------------
+
+WEIGHTS_URL="https://github.com/serengil/deepface_models/releases/download/v1.0/gender_model_weights.h5"
 
 # Labels for the genders that can be detected by the model.
 labels = ["Woman", "Man"]
@@ -43,7 +44,7 @@ def predict(self, img: np.ndarray) -> np.ndarray:
 
 
 def load_model(
-    url="https://github.com/serengil/deepface_models/releases/download/v1.0/gender_model_weights.h5",
+    url=WEIGHTS_URL,
 ) -> Model:
     """
     Construct gender model, download its weights and load

deepface/models/demography/Race.py

@@ -7,11 +7,8 @@
 from deepface.models.Demography import Demography
 from deepface.commons.logger import Logger
 
-logger = Logger()
-
-# --------------------------
 # pylint: disable=line-too-long
-# --------------------------
+
 # dependency configurations
 tf_version = package_utils.get_tf_major_version()
 
@@ -21,10 +18,15 @@
 else:
     from tensorflow.keras.models import Model, Sequential
     from tensorflow.keras.layers import Convolution2D, Flatten, Activation
-# --------------------------
+
+WEIGHTS_URL = (
+    "https://github.com/serengil/deepface_models/releases/download/v1.0/race_model_single_batch.h5"
+)
 # Labels for the ethnic phenotypes that can be detected by the model.
 labels = ["asian", "indian", "black", "white", "middle eastern", "latino hispanic"]
 
+logger = Logger()
+
 # pylint: disable=too-few-public-methods
 class RaceClient(Demography):
     """
@@ -42,7 +44,7 @@ def predict(self, img: np.ndarray) -> np.ndarray:
 
 
 def load_model(
-    url="https://github.com/serengil/deepface_models/releases/download/v1.0/race_model_single_batch.h5",
+    url=WEIGHTS_URL,
 ) -> Model:
     """
     Construct race model, download its weights and load
@@ -69,8 +71,6 @@ def load_model(
         file_name="race_model_single_batch.h5", source_url=url
     )
 
-    race_model = weight_utils.load_model_weights(
-        model=race_model, weight_file=weight_file
-    )
+    race_model = weight_utils.load_model_weights(model=race_model, weight_file=weight_file)
 
     return race_model

deepface/models/face_detection/Dlib.py

@@ -11,6 +11,7 @@
 
 logger = Logger()
 
+WEIGHTS_URL="http://dlib.net/files/shape_predictor_5_face_landmarks.dat.bz2"
 
 class DlibClient(Detector):
     def __init__(self):
@@ -34,7 +35,7 @@ def build_model(self) -> dict:
         # check required file exists in the home/.deepface/weights folder
         weight_file = weight_utils.download_weights_if_necessary(
             file_name="shape_predictor_5_face_landmarks.dat",
-            source_url="http://dlib.net/files/shape_predictor_5_face_landmarks.dat.bz2",
+            source_url=WEIGHTS_URL,
             compress_type="bz2",
         )
 

deepface/models/face_detection/Ssd.py

@@ -16,6 +16,9 @@
 
 # pylint: disable=line-too-long, c-extension-no-member
 
+MODEL_URL = "https://github.com/opencv/opencv/raw/3.4.0/samples/dnn/face_detector/deploy.prototxt"
+WEIGHTS_URL = "https://github.com/opencv/opencv_3rdparty/raw/dnn_samples_face_detector_20170830/res10_300x300_ssd_iter_140000.caffemodel"
+
 
 class SsdClient(Detector):
     def __init__(self):
@@ -31,13 +34,13 @@ def build_model(self) -> dict:
         # model structure
         output_model = weight_utils.download_weights_if_necessary(
             file_name="deploy.prototxt",
-            source_url="https://github.com/opencv/opencv/raw/3.4.0/samples/dnn/face_detector/deploy.prototxt",
+            source_url=MODEL_URL,
         )
 
         # pre-trained weights
         output_weights = weight_utils.download_weights_if_necessary(
             file_name="res10_300x300_ssd_iter_140000.caffemodel",
-            source_url="https://github.com/opencv/opencv_3rdparty/raw/dnn_samples_face_detector_20170830/res10_300x300_ssd_iter_140000.caffemodel",
+            source_url=WEIGHTS_URL,
         )
 
         try:

deepface/models/face_detection/Yolo.py

@@ -12,7 +12,7 @@
 logger = Logger()
 
 # Model's weights paths
-PATH = ".deepface/weights/yolov8n-face.pt"
+WEIGHT_NAME = "yolov8n-face.pt"
 
 # Google Drive URL from repo (https://github.com/derronqi/yolov8-face) ~6MB
 WEIGHT_URL = "https://drive.google.com/uc?id=1qcr9DbgsX3ryrz2uU8w4Xm3cOrRywXqb"
@@ -39,7 +39,7 @@ def build_model(self) -> Any:
             ) from e
 
         weight_file = weight_utils.download_weights_if_necessary(
-            file_name="yolov8n-face.pt", source_url=WEIGHT_URL
+            file_name=WEIGHT_NAME, source_url=WEIGHT_URL
         )
 
         # Return face_detector

deepface/models/face_detection/YuNet.py

@@ -13,6 +13,9 @@
 
 logger = Logger()
 
+# pylint:disable=line-too-long
+WEIGHTS_URL = "https://github.com/opencv/opencv_zoo/raw/main/models/face_detection_yunet/face_detection_yunet_2023mar.onnx"
+
 
 class YuNetClient(Detector):
     def __init__(self):
@@ -41,7 +44,7 @@ def build_model(self) -> Any:
         # pylint: disable=C0301
         weight_file = weight_utils.download_weights_if_necessary(
             file_name="face_detection_yunet_2023mar.onnx",
-            source_url="https://github.com/opencv/opencv_zoo/raw/main/models/face_detection_yunet/face_detection_yunet_2023mar.onnx",
+            source_url=WEIGHTS_URL,
         )
 
         try: