82 lines
2.1 KiB
Python
82 lines
2.1 KiB
Python
import os
|
|
import gdown
|
|
import tensorflow as tf
|
|
from deepface.commons import functions
|
|
|
|
tf_version = int(tf.__version__.split(".", maxsplit=1)[0])
|
|
|
|
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
|
|
|
|
|
|
# -------------------------------------
|
|
|
|
|
|
def loadModel(
|
|
url="https://github.com/serengil/deepface_models/releases/download/v1.0/deepid_keras_weights.h5",
|
|
):
|
|
|
|
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)
|
|
|
|
# ---------------------------------
|
|
|
|
home = functions.get_deepface_home()
|
|
|
|
if os.path.isfile(home + "/.deepface/weights/deepid_keras_weights.h5") != True:
|
|
print("deepid_keras_weights.h5 will be downloaded...")
|
|
|
|
output = home + "/.deepface/weights/deepid_keras_weights.h5"
|
|
gdown.download(url, output, quiet=False)
|
|
|
|
model.load_weights(home + "/.deepface/weights/deepid_keras_weights.h5")
|
|
|
|
return model
|