.json文件无法调用获取

复现《deep learning for computer vision with python 》第二本第九章的时候，用alexnet网络跑dogs vs cats 数据集的时候出现bug

import matplotlib

matplotlib.use("Agg")

from config import dogs_vs_cats_config as config
from pyimagesearch.preprocessing import ImageToArrayPreprocessor
from pyimagesearch.preprocessing import SimplePreprocessor
from pyimagesearch.preprocessing import PatchPreprocessor
from pyimagesearch.preprocessing import MeanPreprocessor
from pyimagesearch.callbacks import TrainingMonitor
from pyimagesearch.io import HDF5DatasetGenerator
from pyimagesearch.nn.conv import AlexNet
from keras.preprocessing.image import ImageDataGenerator
from keras.optimizers import Adam
import json
import os

aug = ImageDataGenerator(rotation_range=20, zoom_range=0.15,
                         width_shift_range=0.2, height_shift_range=0.2,
                         shear_range=0.15, horizontal_flip=True,
                         fill_mode="nearest")

means = json.loads(open(config.DATASET_MEAN).read())
sp = SimplePreprocessor(227, 227)
pp = PatchPreprocessor(227, 227)
mp = MeanPreprocessor(means["R"], means["G"], means["B"])
iap = ImageToArrayPreprocessor()

trainGen = HDF5DatasetGenerator(config.TRAIN_HDF5, 128, aug=aug,
                                preprocessors=[pp, mp, iap], classes=2)
valGen = HDF5DatasetGenerator(config.VAL_HDF5, 128,
                              preprocessors=[sp, mp, iap], classes=2)
print("[INFO] compiling model...")
opt = Adam(lr=1e-3)
model = AlexNet.build(width=227, height=227, depth=3,
                      classes=2, reg=0.0002)
model.compile(loss="binary_crossentropy", optimizer=opt,
              metrics=["accuracy"])
path = os.path.sep.join([config.OUTPUT_PATH, "{}.png".format(
    os.getpid())])
callbacks = [TrainingMonitor(path)]

model.fit_generator(trainGen.generator(),
                    steps_per_epoch=trainGen.numImages // 128,
                    validation_data=valGen.generator(),
                    validation_steps=valGen.numImages // 128,
                    epochs=75,
                    max_queue_size=128 * 2,
                    callbacks=callbacks, verbose=1)

print("[INFO] serializing model...")
model.save(config.MODEL_PATH, overwrite=True)

trainGen.close()
valGen.close()

在terminal运行指令之后。报错 [Errno 2] No such file or directory: 'output\dogs_vs_cats_mean.json'。可是这个文件明明就在我的文件架构下面：

是不是因为路径的原因，还是系统的原因（复现的代码是linux系统下，我自己的系统是windows）

将output\dogs_vs_cats_mean.json改为绝对路径呢
可能是工作空间的原因

你可以参考下这篇文章：json文件解析