97 lines
2.4 KiB
Python
97 lines
2.4 KiB
Python
|
# project dependencies
|
||
|
|
from deepface.commons import package_utils, weight_utils
|
||
|
|
from deepface.models.FacialRecognition import FacialRecognition
|
||
|
|
from deepface.commons.logger import Logger
|
||
|
|
|
||
|
|
logger = Logger()
|
||
|
|
|
||
|
|
tf_version = package_utils.get_tf_major_version()
|
||
|
|
|
||
|
|
if tf_version == 1:
|
||
|
|
from keras.models import Model
|
||
|
|
from keras.layers import (
|
||
|
|
Conv2D,
|
||
|
|
Activation,
|
||
|
|
Input,
|
||
|
|
Add,
|
||
|
|
MaxPooling2D,
|
||
|
|
Flatten,
|
||
|
|
Dense,
|
||
|
|
Dropout,
|
||
|
|
)
|
||
|
|
else:
|
||
|
|
from tensorflow.keras.models import Model
|
||
|
|
from tensorflow.keras.layers import (
|
||
|
|
Conv2D,
|
||
|
|
Activation,
|
||
|
|
Input,
|
||
|
|
Add,
|
||
|
|
MaxPooling2D,
|
||
|
|
Flatten,
|
||
|
|
Dense,
|
||
|
|
Dropout,
|
||
|
|
)
|
||
|
|
|
||
|
|
# pylint: disable=line-too-long
|
||
|
|
|
||
|
|
|
||
|
|
# -------------------------------------
|
||
|
|
|
||
|
|
# pylint: disable=too-few-public-methods
|
||
|
|
class DeepIdClient(FacialRecognition):
|
||
|
|
"""
|
||
|
|
DeepId model class
|
||
|
|
"""
|
||
|
|
|
||
|
|
def __init__(self):
|
||
|
|
self.model = load_model()
|
||
|
|
self.model_name = "DeepId"
|
||
|
|
self.input_shape = (47, 55)
|
||
|
|
self.output_shape = 160
|
||
|
|
|
||
|
|
|
||
|
|
def load_model(
|
||
|
|
url="https://github.com/serengil/deepface_models/releases/download/v1.0/deepid_keras_weights.h5",
|
||
|
|
) -> Model:
|
||
|
|
"""
|
||
|
|
Construct DeepId model, download its weights and load
|
||
|
|
"""
|
||
|
|
|
||
|
|
myInput = Input(shape=(55, 47, 3))
|
||
|
|
|
||
|
|
x = Conv2D(20, (4, 4), name="Conv1", activation="relu", input_shape=(55, 47, 3))(myInput)
|
||
|
|
x = MaxPooling2D(pool_size=2, strides=2, name="Pool1")(x)
|
||
|
|
x = Dropout(rate=0.99, name="D1")(x)
|
||
|
|
|
||
|
|
x = Conv2D(40, (3, 3), name="Conv2", activation="relu")(x)
|
||
|
|
x = MaxPooling2D(pool_size=2, strides=2, name="Pool2")(x)
|
||
|
|
x = Dropout(rate=0.99, name="D2")(x)
|
||
|
|
|
||
|
|
x = Conv2D(60, (3, 3), name="Conv3", activation="relu")(x)
|
||
|
|
x = MaxPooling2D(pool_size=2, strides=2, name="Pool3")(x)
|
||
|
|
x = Dropout(rate=0.99, name="D3")(x)
|
||
|
|
|
||
|
|
x1 = Flatten()(x)
|
||
|
|
fc11 = Dense(160, name="fc11")(x1)
|
||
|
|
|
||
|
|
x2 = Conv2D(80, (2, 2), name="Conv4", activation="relu")(x)
|
||
|
|
x2 = Flatten()(x2)
|
||
|
|
fc12 = Dense(160, name="fc12")(x2)
|
||
|
|
|
||
|
|
y = Add()([fc11, fc12])
|
||
|
|
y = Activation("relu", name="deepid")(y)
|
||
|
|
|
||
|
|
model = Model(inputs=[myInput], outputs=y)
|
||
|
|
|
||
|
|
# ---------------------------------
|
||
|
|
|
||
|
|
weight_file = weight_utils.download_weights_if_necessary(
|
||
|
|
file_name="deepid_keras_weights.h5", source_url=url
|
||
|
|
)
|
||
|
|
|
||
|
|
model = weight_utils.load_model_weights(
|
||
|
|
model=model, weight_file=weight_file
|
||
|
|
)
|
||
|
|
|
||
|
|
return model
|