visualization.py

# -*- coding: utf-8 -*-
"""
Created on Sat Feb 09 21:32:57 2019

@author: Illusion
"""
import numpy as np
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten, Activation
from keras.layers import Convolution2D, MaxPooling2D
from keras.optimizers import SGD
from keras import backend as K
from quiver_engine import server  
K.set_image_dim_ordering('th')


model = Sequential()
model.add(Convolution2D(32, kernel_size=(3, 3),padding='same',input_shape=(3 , 100, 100)))
model.add(Activation('relu'))
model.add(Convolution2D(32, (3, 3)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))

model.add(Convolution2D(64,(3, 3), padding='same'))
model.add(Activation('relu'))
model.add(Convolution2D(64, (3, 3)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))

model.add(Flatten())
model.add(Dense(512))
model.add(Activation('relu'))
model.add(Dropout(0.5))
model.add(Dense(5))
model.add(Activation('sigmoid'))


# let's train the model using SGD + momentum ----------------------------------
sgd = SGD(lr=0.001, decay=1e-6, momentum=0.9, nesterov=False)

model.compile(loss='binary_crossentropy', optimizer=sgd, metrics=['accuracy'])
model.load_weights("weights.hdf5")

server.launch(model,input_folder='./',temp_folder='./filters')