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Merge pull request #1357 from serengil/feat-task-0510-developments
Feat task 0510 developments
This commit is contained in:
Sefik Ilkin Serengil
GitHub
commit
5415407b7c
@ -19,6 +19,40 @@ else:
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logger = Logger()
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# pylint: disable=line-too-long
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WEIGHTS = {
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"facial_recognition": {
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"VGG-Face": "https://github.com/serengil/deepface_models/releases/download/v1.0/vgg_face_weights.h5",
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"Facenet": "https://github.com/serengil/deepface_models/releases/download/v1.0/facenet_weights.h5",
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"Facenet512": "https://github.com/serengil/deepface_models/releases/download/v1.0/facenet512_weights.h5",
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"OpenFace": "https://github.com/serengil/deepface_models/releases/download/v1.0/openface_weights.h5",
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"FbDeepFace": "https://github.com/swghosh/DeepFace/releases/download/weights-vggface2-2d-aligned/VGGFace2_DeepFace_weights_val-0.9034.h5.zip",
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"ArcFace": "https://github.com/serengil/deepface_models/releases/download/v1.0/arcface_weights.h5",
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"DeepID": "https://github.com/serengil/deepface_models/releases/download/v1.0/deepid_keras_weights.h5",
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"SFace": "https://github.com/opencv/opencv_zoo/raw/main/models/face_recognition_sface/face_recognition_sface_2021dec.onnx",
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"GhostFaceNet": "https://github.com/HamadYA/GhostFaceNets/releases/download/v1.2/GhostFaceNet_W1.3_S1_ArcFace.h5",
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"Dlib": "http://dlib.net/files/dlib_face_recognition_resnet_model_v1.dat.bz2",
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},
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"demography": {
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"Age": "https://github.com/serengil/deepface_models/releases/download/v1.0/age_model_weights.h5",
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"Gender": "https://github.com/serengil/deepface_models/releases/download/v1.0/gender_model_weights.h5",
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"Emotion": "https://github.com/serengil/deepface_models/releases/download/v1.0/facial_expression_model_weights.h5",
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"Race": "https://github.com/serengil/deepface_models/releases/download/v1.0/race_model_single_batch.h5",
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},
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"detection": {
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"ssd_model": "https://github.com/opencv/opencv/raw/3.4.0/samples/dnn/face_detector/deploy.prototxt",
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"ssd_weights": "https://github.com/opencv/opencv_3rdparty/raw/dnn_samples_face_detector_20170830/res10_300x300_ssd_iter_140000.caffemodel",
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"yolo": "https://drive.google.com/uc?id=1qcr9DbgsX3ryrz2uU8w4Xm3cOrRywXqb",
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"yunet": "https://github.com/opencv/opencv_zoo/raw/main/models/face_detection_yunet/face_detection_yunet_2023mar.onnx",
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"dlib": "http://dlib.net/files/shape_predictor_5_face_landmarks.dat.bz2",
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"centerface": "https://github.com/Star-Clouds/CenterFace/raw/master/models/onnx/centerface.onnx",
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},
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"spoofing": {
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"MiniFASNetV2": "https://github.com/minivision-ai/Silent-Face-Anti-Spoofing/raw/master/resources/anti_spoof_models/2.7_80x80_MiniFASNetV2.pth",
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"MiniFASNetV1SE": "https://github.com/minivision-ai/Silent-Face-Anti-Spoofing/raw/master/resources/anti_spoof_models/4_0_0_80x80_MiniFASNetV1SE.pth",
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},
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}
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ALLOWED_COMPRESS_TYPES = ["zip", "bz2"]
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@ -95,3 +129,20 @@ def load_model_weights(model: Sequential, weight_file: str) -> Sequential:
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"and copying it to the target folder."
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) from err
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return model
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def retrieve_model_source(model_name: str, task: str) -> str:
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"""
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Find the source url of a given model name
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Args:
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model_name (str): given model name
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Returns:
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weight_url (str): source url of the given model
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"""
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if task not in ["facial_recognition", "detection", "demography", "spoofing"]:
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raise ValueError(f"unimplemented task - {task}")
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source_url = WEIGHTS.get(task, {}).get(model_name)
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if source_url is None:
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raise ValueError(f"Source url cannot be found for given model {task}-{model_name}")
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return source_url
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@ -6,7 +6,7 @@ import numpy as np
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# Notice that all facial detector models must be inherited from this class
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# pylint: disable=unnecessary-pass, too-few-public-methods
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# pylint: disable=unnecessary-pass, too-few-public-methods, too-many-instance-attributes
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class Detector(ABC):
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@abstractmethod
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def detect_faces(self, img: np.ndarray) -> List["FacialAreaRegion"]:
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@ -45,6 +45,7 @@ class FacialAreaRegion:
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confidence (float, optional): Confidence score associated with the face detection.
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Default is None.
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"""
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x: int
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y: int
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w: int
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@ -52,6 +53,9 @@ class FacialAreaRegion:
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left_eye: Optional[Tuple[int, int]] = None
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right_eye: Optional[Tuple[int, int]] = None
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confidence: Optional[float] = None
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nose: Optional[Tuple[int, int]] = None
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mouth_right: Optional[Tuple[int, int]] = None
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mouth_left: Optional[Tuple[int, int]] = None
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@dataclass
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@ -63,7 +67,8 @@ class DetectedFace:
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img (np.ndarray): detected face image as numpy array
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facial_area (FacialAreaRegion): detected face's metadata (e.g. bounding box)
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confidence (float): confidence score for face detection
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"""
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"""
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img: np.ndarray
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facial_area: FacialAreaRegion
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confidence: float
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@ -42,10 +42,19 @@ class RetinaFaceClient(Detector):
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# retinaface sets left and right eyes with respect to the person
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left_eye = identity["landmarks"]["left_eye"]
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right_eye = identity["landmarks"]["right_eye"]
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nose = identity["landmarks"].get("nose")
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mouth_right = identity["landmarks"].get("mouth_right")
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mouth_left = identity["landmarks"].get("mouth_left")
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# eyes are list of float, need to cast them tuple of int
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left_eye = tuple(int(i) for i in left_eye)
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right_eye = tuple(int(i) for i in right_eye)
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if nose is not None:
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nose = tuple(int(i) for i in nose)
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if mouth_right is not None:
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mouth_right = tuple(int(i) for i in mouth_right)
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if mouth_left is not None:
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mouth_left = tuple(int(i) for i in mouth_left)
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confidence = identity["score"]
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@ -57,6 +66,9 @@ class RetinaFaceClient(Detector):
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left_eye=left_eye,
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right_eye=right_eye,
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confidence=confidence,
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nose=nose,
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mouth_left=mouth_left,
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mouth_right=mouth_right,
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)
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resp.append(facial_area)
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@ -140,9 +140,7 @@ def load_model(
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file_name="vgg_face_weights.h5", source_url=url
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)
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model = weight_utils.load_model_weights(
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model=model, weight_file=weight_file
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)
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model = weight_utils.load_model_weights(model=model, weight_file=weight_file)
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# 2622d dimensional model
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# vgg_face_descriptor = Model(inputs=model.layers[0].input, outputs=model.layers[-2].output)
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@ -151,7 +149,6 @@ def load_model(
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# - softmax causes underfitting
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# - added normalization layer to avoid underfitting with euclidean
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# as described here: https://github.com/serengil/deepface/issues/944
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base_model_output = Sequential()
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base_model_output = Flatten()(model.layers[-5].output)
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# keras backend's l2 normalization layer troubles some gpu users (e.g. issue 957, 966)
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# base_model_output = Lambda(lambda x: K.l2_normalize(x, axis=1), name="norm_layer")(
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@ -148,16 +148,26 @@ def extract_faces(
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w = min(width - x - 1, int(current_region.w))
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h = min(height - y - 1, int(current_region.h))
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facial_area = {
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"x": x,
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"y": y,
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"w": w,
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"h": h,
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"left_eye": current_region.left_eye,
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"right_eye": current_region.right_eye,
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}
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# optional nose, mouth_left and mouth_right fields are coming just for retinaface
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if current_region.nose is not None:
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facial_area["nose"] = current_region.nose
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if current_region.mouth_left is not None:
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facial_area["mouth_left"] = current_region.mouth_left
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if current_region.mouth_right is not None:
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facial_area["mouth_right"] = current_region.mouth_right
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resp_obj = {
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"face": current_img,
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"facial_area": {
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"x": x,
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"y": y,
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"w": w,
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"h": h,
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"left_eye": current_region.left_eye,
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"right_eye": current_region.right_eye,
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},
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"facial_area": facial_area,
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"confidence": round(float(current_region.confidence or 0), 2),
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}
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@ -272,6 +282,9 @@ def expand_and_align_face(
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left_eye = facial_area.left_eye
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right_eye = facial_area.right_eye
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confidence = facial_area.confidence
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nose = facial_area.nose
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mouth_left = facial_area.mouth_left
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mouth_right = facial_area.mouth_right
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if expand_percentage > 0:
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# Expand the facial region height and width by the provided percentage
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@ -305,11 +318,26 @@ def expand_and_align_face(
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left_eye = (left_eye[0] - width_border, left_eye[1] - height_border)
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if right_eye is not None:
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right_eye = (right_eye[0] - width_border, right_eye[1] - height_border)
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if nose is not None:
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nose = (nose[0] - width_border, nose[1] - height_border)
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if mouth_left is not None:
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mouth_left = (mouth_left[0] - width_border, mouth_left[1] - height_border)
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if mouth_right is not None:
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mouth_right = (mouth_right[0] - width_border, mouth_right[1] - height_border)
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return DetectedFace(
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img=detected_face,
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facial_area=FacialAreaRegion(
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x=x, y=y, h=h, w=w, confidence=confidence, left_eye=left_eye, right_eye=right_eye
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x=x,
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y=y,
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h=h,
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w=w,
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confidence=confidence,
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left_eye=left_eye,
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right_eye=right_eye,
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nose=nose,
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mouth_left=mouth_left,
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mouth_right=mouth_right,
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),
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confidence=confidence,
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)
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