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import os
import zipfile
import gdown
from deepface.commons import package_utils, folder_utils
from deepface.models.FacialRecognition import FacialRecognition
from deepface.commons import logger as log
logger = log.get_singletonish_logger()
# --------------------------------
# dependency configuration
tf_major = package_utils.get_tf_major_version()
tf_minor = package_utils.get_tf_minor_version()
if tf_major == 1:
from keras.models import Model, Sequential
from keras.layers import (
Convolution2D,
MaxPooling2D,
Flatten,
Dense,
Dropout,
)
else:
from tensorflow.keras.models import Model, Sequential
from tensorflow.keras.layers import (
Convolution2D,
MaxPooling2D,
Flatten,
Dense,
Dropout,
)
# -------------------------------------
# pylint: disable=line-too-long, too-few-public-methods
class DeepFaceClient(FacialRecognition):
"""
Fb's DeepFace model class
"""
def __init__(self):
# DeepFace requires tf 2.12 or less
if tf_major == 2 and tf_minor > 12:
# Ref: https://github.com/serengil/deepface/pull/1079
raise ValueError(
"DeepFace model requires LocallyConnected2D but it is no longer supported"
f" after tf 2.12 but you have {tf_major}.{tf_minor}. You need to downgrade your tf."
)
self.model = load_model()
self.model_name = "DeepFace"
self.input_shape = (152, 152)
self.output_shape = 4096
def load_model(
url="https://github.com/swghosh/DeepFace/releases/download/weights-vggface2-2d-aligned/VGGFace2_DeepFace_weights_val-0.9034.h5.zip",
) -> Model:
"""
Construct DeepFace model, download its weights and load
"""
# we have some checks for this dependency in the init of client
# putting this in global causes library initialization
if tf_major == 1:
from keras.layers import LocallyConnected2D
else:
from tensorflow.keras.layers import LocallyConnected2D
base_model = Sequential()
base_model.add(
Convolution2D(32, (11, 11), activation="relu", name="C1", input_shape=(152, 152, 3))
)
base_model.add(MaxPooling2D(pool_size=3, strides=2, padding="same", name="M2"))
base_model.add(Convolution2D(16, (9, 9), activation="relu", name="C3"))
base_model.add(LocallyConnected2D(16, (9, 9), activation="relu", name="L4"))
base_model.add(LocallyConnected2D(16, (7, 7), strides=2, activation="relu", name="L5"))
base_model.add(LocallyConnected2D(16, (5, 5), activation="relu", name="L6"))
base_model.add(Flatten(name="F0"))
base_model.add(Dense(4096, activation="relu", name="F7"))
base_model.add(Dropout(rate=0.5, name="D0"))
base_model.add(Dense(8631, activation="softmax", name="F8"))
# ---------------------------------
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...")
output = home + "/.deepface/weights/VGGFace2_DeepFace_weights_val-0.9034.h5.zip"
gdown.download(url, output, quiet=False)
# unzip VGGFace2_DeepFace_weights_val-0.9034.h5.zip
with zipfile.ZipFile(output, "r") as zip_ref:
zip_ref.extractall(home + "/.deepface/weights/")
base_model.load_weights(home + "/.deepface/weights/VGGFace2_DeepFace_weights_val-0.9034.h5")
# drop F8 and D0. F7 is the representation layer.
deepface_model = Model(inputs=base_model.layers[0].input, outputs=base_model.layers[-3].output)
return deepface_model
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