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2c0a507994
Add `model_path` parameter in `loadModel()` function. This adds more flexiblity while loading the models. Also, refactor code using standard `os.path.join` which will make sure to join the paths correctly.
100 lines
3.1 KiB
Python
100 lines
3.1 KiB
Python
import os
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from pathlib import Path
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from keras.models import Model, Sequential
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from keras.layers import (
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Input,
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Convolution2D,
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ZeroPadding2D,
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MaxPooling2D,
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Flatten,
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Dense,
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Dropout,
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Activation,
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)
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import gdown
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# ---------------------------------------
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def get_base_model():
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model = Sequential()
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model.add(ZeroPadding2D((1, 1), input_shape=(224, 224, 3)))
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model.add(Convolution2D(64, (3, 3), activation="relu"))
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model.add(ZeroPadding2D((1, 1)))
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model.add(Convolution2D(64, (3, 3), activation="relu"))
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model.add(MaxPooling2D((2, 2), strides=(2, 2)))
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model.add(ZeroPadding2D((1, 1)))
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model.add(Convolution2D(128, (3, 3), activation="relu"))
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model.add(ZeroPadding2D((1, 1)))
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model.add(Convolution2D(128, (3, 3), activation="relu"))
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model.add(MaxPooling2D((2, 2), strides=(2, 2)))
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model.add(ZeroPadding2D((1, 1)))
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model.add(Convolution2D(256, (3, 3), activation="relu"))
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model.add(ZeroPadding2D((1, 1)))
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model.add(Convolution2D(256, (3, 3), activation="relu"))
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model.add(ZeroPadding2D((1, 1)))
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model.add(Convolution2D(256, (3, 3), activation="relu"))
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model.add(MaxPooling2D((2, 2), strides=(2, 2)))
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model.add(ZeroPadding2D((1, 1)))
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model.add(Convolution2D(512, (3, 3), activation="relu"))
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model.add(ZeroPadding2D((1, 1)))
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model.add(Convolution2D(512, (3, 3), activation="relu"))
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model.add(ZeroPadding2D((1, 1)))
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model.add(Convolution2D(512, (3, 3), activation="relu"))
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model.add(MaxPooling2D((2, 2), strides=(2, 2)))
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model.add(ZeroPadding2D((1, 1)))
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model.add(Convolution2D(512, (3, 3), activation="relu"))
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model.add(ZeroPadding2D((1, 1)))
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model.add(Convolution2D(512, (3, 3), activation="relu"))
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model.add(ZeroPadding2D((1, 1)))
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model.add(Convolution2D(512, (3, 3), activation="relu"))
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model.add(MaxPooling2D((2, 2), strides=(2, 2)))
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model.add(Convolution2D(4096, (7, 7), activation="relu"))
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model.add(Dropout(0.5))
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model.add(Convolution2D(4096, (1, 1), activation="relu"))
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model.add(Dropout(0.5))
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model.add(Convolution2D(2622, (1, 1)))
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model.add(Flatten())
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model.add(Activation("softmax"))
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return model
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def loadModel(model_path=""):
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"""
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Args:
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model_path: str
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If provided, this path will be used to load the model from.
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"""
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if model_path:
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assert Path(model_path).exists()
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assert model_path.endswith(".h5")
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else:
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home = Path.home().as_posix()
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model_path = os.path.join(home, ".deepface/weights/vgg_face_weights.h5")
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if not os.path.isfile(model_path):
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print(f"vgg_face_weights.h5 will be downloaded to {model_path}")
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url = "https://drive.google.com/uc?id=1CPSeum3HpopfomUEK1gybeuIVoeJT_Eo"
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gdown.download(url, model_path, quiet=False)
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# -----------------------------------
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print(f"Loading model from {model_path}")
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model = get_base_model()
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model.load_weights(model_path)
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# -----------------------------------
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# TO-DO: why?
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vgg_face_descriptor = Model(
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inputs=model.layers[0].input, outputs=model.layers[-2].output
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)
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return vgg_face_descriptor
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