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model_define.py
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model_define.py
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from keras.models import Sequential
from keras.layers import Conv2D, MaxPooling2D
from keras.layers import Activation, Dropout, Flatten, Dense
def create_model_v1():
keras_model = Sequential()
keras_model.add(Conv2D(32, (3, 3), input_shape=(256,256,3)))
keras_model.add(Activation('relu'))
keras_model.add(MaxPooling2D(pool_size=(2, 2)))
keras_model.add(Conv2D(32, (3, 3)))
keras_model.add(Activation('relu'))
keras_model.add(MaxPooling2D(pool_size=(2, 2)))
keras_model.add(Conv2D(64, (3, 3)))
keras_model.add(Activation('relu'))
keras_model.add(MaxPooling2D(pool_size=(2, 2)))
keras_model.add(Flatten())
keras_model.add(Dense(64))
keras_model.add(Activation('relu'))
keras_model.add(Dropout(0.5))
keras_model.add(Dense(3)) #3 classes
keras_model.add(Activation('softmax'))
return keras_model
def create_model_v2():
keras_model = Sequential()
keras_model.add(Conv2D(64, (3, 3), input_shape=(256,256,3)))
keras_model.add(Activation('relu'))
keras_model.add(MaxPooling2D(pool_size=(2, 2)))
keras_model.add(Conv2D(64, (3, 3)))
keras_model.add(Activation('relu'))
keras_model.add(MaxPooling2D(pool_size=(2, 2)))
keras_model.add(Conv2D(64, (3, 3)))
keras_model.add(Activation('relu'))
keras_model.add(MaxPooling2D(pool_size=(2, 2)))
keras_model.add(Flatten())
keras_model.add(Dense(256,activation='relu'))
keras_model.add(Dropout(0.5))
keras_model.add(Dense(256,activation='relu'))
keras_model.add(Dropout(0.5))
keras_model.add(Dense(3, activation='softmax')) #3 classes
return keras_model
def create_model_v3():
keras_model = Sequential()
keras_model.add(Conv2D(64, (3, 3), input_shape=(256,256,3)))
keras_model.add(Activation('relu'))
keras_model.add(MaxPooling2D(pool_size=(2, 2)))
keras_model.add(Conv2D(64, (3, 3)))
keras_model.add(Activation('relu'))
keras_model.add(MaxPooling2D(pool_size=(2, 2)))
keras_model.add(Conv2D(64, (3, 3)))
keras_model.add(Activation('relu'))
keras_model.add(MaxPooling2D(pool_size=(2, 2)))
keras_model.add(Conv2D(64, (3, 3)))
keras_model.add(Activation('relu'))
keras_model.add(MaxPooling2D(pool_size=(2, 2)))
keras_model.add(Flatten())
keras_model.add(Dense(64,activation='relu'))
keras_model.add(Dropout(0.5))
keras_model.add(Dense(3, activation='softmax')) #3 classes
return keras_model