Merge pull request #1397 from nriviera/yolo

[FEATURE]: adding yolov11 into face detection portfolio

README.md

@@ -121,7 +121,7 @@ models = [
   "ArcFace", 
   "Dlib", 
   "SFace",
-  "GhostFaceNet",
+  "GhostFaceNet"
 ]
 
 #face verification
@@ -223,6 +223,9 @@ backends = [
   'retinaface', 
   'mediapipe',
   'yolov8',
+  'yolov11s',
+  'yolov11n',
+  'yolov11m',
   'yunet',
   'centerface',
 ]

deepface/DeepFace.py

@@ -54,10 +54,10 @@ def build_model(model_name: str, task: str = "facial_recognition") -> Any:
     Args:
         model_name (str): model identifier
             - VGG-Face, Facenet, Facenet512, OpenFace, DeepFace, DeepID, Dlib,
-                ArcFace, SFace, GhostFaceNet for face recognition
+                ArcFace, SFace and GhostFaceNet for face recognition
             - Age, Gender, Emotion, Race for facial attributes
-            - opencv, mtcnn, ssd, dlib, retinaface, mediapipe, yolov8, yunet,
+            - opencv, mtcnn, ssd, dlib, retinaface, mediapipe, yolov8, yolov11n,
-                fastmtcnn or centerface for face detectors
+              yolov11s, yolov11m, yunet, fastmtcnn or centerface for face detectors
             - Fasnet for spoofing
         task (str): facial_recognition, facial_attribute, face_detector, spoofing
             default is facial_recognition
@@ -96,8 +96,8 @@ def verify(
             OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face).
 
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m',
-            (default is opencv).
+            'centerface' or 'skip' (default is opencv).
 
         distance_metric (string): Metric for measuring similarity. Options: 'cosine',
             'euclidean', 'euclidean_l2' (default is cosine).
@@ -187,8 +187,8 @@ def analyze(
             Set to False to avoid the exception for low-resolution images (default is True).
 
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n',  'yolov11s', 'yolov11m',
-            (default is opencv).
+            'centerface' or 'skip' (default is opencv).
 
         distance_metric (string): Metric for measuring similarity. Options: 'cosine',
             'euclidean', 'euclidean_l2' (default is cosine).
@@ -298,8 +298,8 @@ def find(
             Set to False to avoid the exception for low-resolution images (default is True).
 
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m',
-            (default is opencv).
+            'centerface' or 'skip' (default is opencv).
 
         align (boolean): Perform alignment based on the eye positions (default is True).
 
@@ -396,8 +396,8 @@ def represent(
             (default is True).
 
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m',
-            (default is opencv).
+            'centerface' or 'skip' (default is opencv).
 
         align (boolean): Perform alignment based on the eye positions (default is True).
 
@@ -462,8 +462,8 @@ def stream(
             OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face).
 
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m',
-            (default is opencv).
+            'centerface' or 'skip' (default is opencv).
 
         distance_metric (string): Metric for measuring similarity. Options: 'cosine',
             'euclidean', 'euclidean_l2' (default is cosine).
@@ -517,8 +517,8 @@ def extract_faces(
             as a string, numpy array (BGR), or base64 encoded images.
 
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m',
-            (default is opencv).
+            'centerface' or 'skip' (default is opencv).
 
         enforce_detection (boolean): If no face is detected in an image, raise an exception.
             Set to False to avoid the exception for low-resolution images (default is True).
@@ -601,8 +601,8 @@ def detectFace(
             added to resize the image (default is (224, 224)).
 
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m',
-            (default is opencv).
+            'centerface' or 'skip' (default is opencv).
 
         enforce_detection (boolean): If no face is detected in an image, raise an exception.
             Set to False to avoid the exception for low-resolution images (default is True).

deepface/commons/weight_utils.py

@@ -128,8 +128,9 @@ def download_all_models_in_one_shot() -> None:
         WEIGHTS_URL as SSD_WEIGHTS,
     )
     from deepface.models.face_detection.Yolo import (
-        WEIGHT_URL as YOLOV8_WEIGHTS,
+        WEIGHT_URLS as YOLO_WEIGHTS,
-        WEIGHT_NAME as YOLOV8_WEIGHT_NAME,
+        WEIGHT_NAMES as YOLO_WEIGHT_NAMES,
+        YoloModel
     )
     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
@@ -162,8 +163,20 @@ def download_all_models_in_one_shot() -> None:
         SSD_MODEL,
         SSD_WEIGHTS,
         {
-            "filename": YOLOV8_WEIGHT_NAME,
+            "filename": YOLO_WEIGHT_NAMES[YoloModel.V8N.value],
-            "url": YOLOV8_WEIGHTS,
+            "url": YOLO_WEIGHTS[YoloModel.V8N.value],
+        },
+        {
+            "filename": YOLO_WEIGHT_NAMES[YoloModel.V11N.value],
+            "url": YOLO_WEIGHTS[YoloModel.V11N.value],
+        },
+        {
+            "filename": YOLO_WEIGHT_NAMES[YoloModel.V11S.value],
+            "url": YOLO_WEIGHTS[YoloModel.V11S.value],
+        },
+        {
+            "filename": YOLO_WEIGHT_NAMES[YoloModel.V11M.value],
+            "url": YOLO_WEIGHTS[YoloModel.V11M.value],
         },
         YUNET_WEIGHTS,
         DLIB_FD_WEIGHTS,

deepface/models/face_detection/Yolo.py

@@ -1,29 +1,45 @@
 # built-in dependencies
 import os
-from typing import Any, List
+from typing import List, Any
+from enum import Enum
 
 # 3rd party dependencies
 import numpy as np
 
 # project dependencies
 from deepface.models.Detector import Detector, FacialAreaRegion
-from deepface.commons import weight_utils
 from deepface.commons.logger import Logger
+from deepface.commons import weight_utils
 
 logger = Logger()
 
+
+class YoloModel(Enum):
+    V8N = 0
+    V11N = 1
+    V11S = 2
+    V11M = 3
+
+
 # Model's weights paths
-WEIGHT_NAME = "yolov8n-face.pt"
+WEIGHT_NAMES = ["yolov8n-face.pt",
+                "yolov11n-face.pt",
+                "yolov11s-face.pt",
+                "yolov11m-face.pt"]
 
 # Google Drive URL from repo (https://github.com/derronqi/yolov8-face) ~6MB
-WEIGHT_URL = "https://drive.google.com/uc?id=1qcr9DbgsX3ryrz2uU8w4Xm3cOrRywXqb"
+WEIGHT_URLS = ["https://drive.google.com/uc?id=1qcr9DbgsX3ryrz2uU8w4Xm3cOrRywXqb",
+               "https://github.com/akanametov/yolo-face/releases/download/v0.0.0/yolov11n-face.pt",
+               "https://github.com/akanametov/yolo-face/releases/download/v0.0.0/yolov11s-face.pt",
+               "https://github.com/akanametov/yolo-face/releases/download/v0.0.0/yolov11m-face.pt"]
 
 
-class YoloClient(Detector):
+class YoloDetectorClient(Detector):
-    def __init__(self):
+    def __init__(self, model: YoloModel):
-        self.model = self.build_model()
+        super().__init__()
+        self.model = self.build_model(model)
 
-    def build_model(self) -> Any:
+    def build_model(self, model: YoloModel) -> Any:
         """
         Build a yolo detector model
         Returns:
@@ -40,7 +56,7 @@ class YoloClient(Detector):
             ) from e
 
         weight_file = weight_utils.download_weights_if_necessary(
-            file_name=WEIGHT_NAME, source_url=WEIGHT_URL
+            file_name=WEIGHT_NAMES[model.value], source_url=WEIGHT_URLS[model.value]
         )
 
         # Return face_detector
@@ -69,13 +85,19 @@ class YoloClient(Detector):
         # For each face, extract the bounding box, the landmarks and confidence
         for result in results:
 
-            if result.boxes is None or result.keypoints is None:
+            if result.boxes is None:
                 continue
 
             # Extract the bounding box and the confidence
             x, y, w, h = result.boxes.xywh.tolist()[0]
             confidence = result.boxes.conf.tolist()[0]
 
+            right_eye = None
+            left_eye = None
+
+            # yolo-facev8 is detecting eyes through keypoints,
+            # while for v11 keypoints are always None
+            if result.keypoints is not None:
                 # right_eye_conf = result.keypoints.conf[0][0]
                 # left_eye_conf = result.keypoints.conf[0][1]
                 right_eye = result.keypoints.xy[0][0].tolist()
@@ -98,3 +120,23 @@ class YoloClient(Detector):
             resp.append(facial_area)
 
         return resp
+
+
+class YoloDetectorClientV8n(YoloDetectorClient):
+    def __init__(self):
+        super().__init__(YoloModel.V8N)
+
+
+class YoloDetectorClientV11n(YoloDetectorClient):
+    def __init__(self):
+        super().__init__(YoloModel.V11N)
+
+
+class YoloDetectorClientV11s(YoloDetectorClient):
+    def __init__(self):
+        super().__init__(YoloModel.V11S)
+
+
+class YoloDetectorClientV11m(YoloDetectorClient):
+    def __init__(self):
+        super().__init__(YoloModel.V11M)

deepface/modules/demography.py

@@ -35,8 +35,8 @@ def analyze(
             Set to False to avoid the exception for low-resolution images (default is True).
 
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m',
-            (default is opencv).
+            'centerface' or 'skip' (default is opencv).
 
         distance_metric (string): Metric for measuring similarity. Options: 'cosine',
             'euclidean', 'euclidean_l2' (default is cosine).

deepface/modules/detection.py

@@ -38,8 +38,8 @@ def extract_faces(
             as a string, numpy array (BGR), or base64 encoded images.
 
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m',
-            (default is opencv)
+            'centerface' or 'skip' (default is opencv)
 
         enforce_detection (boolean): If no face is detected in an image, raise an exception.
             Default is True. Set to False to avoid the exception for low-resolution images.

deepface/modules/modeling.py

@@ -11,7 +11,7 @@ from deepface.models.facial_recognition import (
     SFace,
     Dlib,
     Facenet,
-    GhostFaceNet,
+    GhostFaceNet
 )
 from deepface.models.face_detection import (
     FastMtCnn,
@@ -21,7 +21,7 @@ from deepface.models.face_detection import (
     Dlib as DlibDetector,
     RetinaFace,
     Ssd,
-    Yolo,
+    Yolo as YoloFaceDetector,
     YuNet,
     CenterFace,
 )
@@ -36,10 +36,10 @@ def build_model(task: str, model_name: str) -> Any:
         task (str): facial_recognition, facial_attribute, face_detector, spoofing
         model_name (str): model identifier
             - VGG-Face, Facenet, Facenet512, OpenFace, DeepFace, DeepID, Dlib,
-                ArcFace, SFace, GhostFaceNet for face recognition
+                ArcFace, SFace and GhostFaceNet for face recognition
             - Age, Gender, Emotion, Race for facial attributes
-            - opencv, mtcnn, ssd, dlib, retinaface, mediapipe, yolov8, yunet,
+            - opencv, mtcnn, ssd, dlib, retinaface, mediapipe, yolov8, 'yolov11n',
-                fastmtcnn or centerface for face detectors
+                'yolov11s', 'yolov11m', yunet, fastmtcnn or centerface for face detectors
             - Fasnet for spoofing
     Returns:
             built model class
@@ -59,7 +59,7 @@ def build_model(task: str, model_name: str) -> Any:
             "Dlib": Dlib.DlibClient,
             "ArcFace": ArcFace.ArcFaceClient,
             "SFace": SFace.SFaceClient,
-            "GhostFaceNet": GhostFaceNet.GhostFaceNetClient,
+            "GhostFaceNet": GhostFaceNet.GhostFaceNetClient
         },
         "spoofing": {
             "Fasnet": FasNet.Fasnet,
@@ -77,7 +77,10 @@ def build_model(task: str, model_name: str) -> Any:
             "dlib": DlibDetector.DlibClient,
             "retinaface": RetinaFace.RetinaFaceClient,
             "mediapipe": MediaPipe.MediaPipeClient,
-            "yolov8": Yolo.YoloClient,
+            "yolov8": YoloFaceDetector.YoloDetectorClientV8n,
+            "yolov11n": YoloFaceDetector.YoloDetectorClientV11n,
+            "yolov11s": YoloFaceDetector.YoloDetectorClientV11s,
+            "yolov11m": YoloFaceDetector.YoloDetectorClientV11m,
             "yunet": YuNet.YuNetClient,
             "fastmtcnn": FastMtCnn.FastMtCnnClient,
             "centerface": CenterFace.CenterFaceClient,

deepface/modules/recognition.py

@@ -54,7 +54,8 @@ def find(
             Default is True. Set to False to avoid the exception for low-resolution images.
 
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'.
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8','yolov11n', 'yolov11s',
+            'yolov11m', 'centerface' or 'skip'.
 
         align (boolean): Perform alignment based on the eye positions.
 
@@ -483,7 +484,8 @@ def find_batched(
             Default is True. Set to False to avoid the exception for low-resolution images.
 
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'.
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s',
+            'yolov11m', 'centerface' or 'skip'.
 
         align (boolean): Perform alignment based on the eye positions.
 

deepface/modules/representation.py

@@ -36,7 +36,8 @@ def represent(
             Default is True. Set to False to avoid the exception for low-resolution images.
 
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'.
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s',
+            'yolov11m', 'centerface' or 'skip'.
 
         align (boolean): Perform alignment based on the eye positions.
 

deepface/modules/streaming.py

@@ -42,11 +42,11 @@ def analysis(
             in the database will be considered in the decision-making process.
 
         model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512,
-            OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face).
+            OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face)
 
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m',
-            (default is opencv).
+            'centerface' or 'skip' (default is opencv).
 
         distance_metric (string): Metric for measuring similarity. Options: 'cosine',
             'euclidean', 'euclidean_l2' (default is cosine).
@@ -192,8 +192,8 @@ def search_identity(
         model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512,
             OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face).
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m',
-            (default is opencv).
+            'centerface' or 'skip' (default is opencv).
         distance_metric (string): Metric for measuring similarity. Options: 'cosine',
             'euclidean', 'euclidean_l2' (default is cosine).
     Returns:
@@ -374,8 +374,8 @@ def grab_facial_areas(
     Args:
         img (np.ndarray): image itself
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m',
-            (default is opencv).
+            'centerface' or 'skip' (default is opencv).
         threshold (int): threshold for facial area, discard smaller ones
     Returns
         result (list): list of tuple with x, y, w and h coordinates
@@ -443,8 +443,8 @@ def perform_facial_recognition(
         db_path (string): Path to the folder containing image files. All detected faces
             in the database will be considered in the decision-making process.
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s',
-            (default is opencv).
+            'yolov11m', 'centerface' or 'skip' (default is opencv).
         distance_metric (string): Metric for measuring similarity. Options: 'cosine',
             'euclidean', 'euclidean_l2' (default is cosine).
         model_name (str): Model for face recognition. Options: VGG-Face, Facenet, Facenet512,

deepface/modules/verification.py

@@ -47,8 +47,8 @@ def verify(
             OpenFace, DeepFace, DeepID, Dlib, ArcFace, SFace and GhostFaceNet (default is VGG-Face).
 
         detector_backend (string): face detector backend. Options: 'opencv', 'retinaface',
-            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'centerface' or 'skip'
+            'mtcnn', 'ssd', 'dlib', 'mediapipe', 'yolov8', 'yolov11n', 'yolov11s', 'yolov11m',
-            (default is opencv)
+            'centerface' or 'skip' (default is opencv)
 
         distance_metric (string): Metric for measuring similarity. Options: 'cosine',
             'euclidean', 'euclidean_l2' (default is cosine).

tests/visual-test.py

@@ -21,7 +21,7 @@ model_names = [
     "Dlib",
     "ArcFace",
     "SFace",
-    "GhostFaceNet",
+    "GhostFaceNet"
 ]
 
 detector_backends = [
@@ -34,6 +34,9 @@ detector_backends = [
     "retinaface",
     "yunet",
     "yolov8",
+    "yolov11n",
+    "yolov11s",
+    "yolov11m",
     "centerface",
 ]