def main():
# モデルの読み込み
model = MODEL.L.Classifier(MODEL.CIFAR10_cifer())
chainer.serializers.load_npz("model_final", model)
# データの読み込み
images, labels = chainer.datasets.get_cifar10()[1]._datasets
# table 作成
create_AE_file('AE.h5', model, images, labels, r=0.001, n_threads=32)
# 評価
df = evaluate_AE('AE.h5', model, epsilon=0.01, n_threads=32)
# 書き出し
df.to_csv('AE.csv')
import chainer
from chainer import cuda, Function, gradient_check, report, training, utils, Variable
from chainer import datasets, iterators, optimizers, serializers
from chainer import Link, Chain, ChainList
import chainer.functions as F
import chainer.links as L
from chainer.training import extensions
import matplotlib.pyplot as plt
import cv2
import pandas as pd
import MODEL #CIFAR10_cifer()
from skimage import io
#モデルの読み込み
model = MODEL.L.Classifier(MODEL.CIFAR10_cifer())
serializers.load_npz("model_final", model)
def Print_Label(num):
label = [
'airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog',
'horse', 'ship', 'truck'
]
#print("Label->{}".format(label[num]))
return label[num]
#ニューロンを一覧で表示する
def MELMEL(data, num=10):
#print("number : neuron")
