请注意,这与时间转换无关,而与转换JSON / C#类型有关
我需要序列化和反序列化具有属性DateTimeOffset的对象,但是序列化时她的值需要以毫秒为单位;反序列化时,再次将其转换为DateTimeOffset。 我到了这一点:
methods: {
getTagNames: (tags) => {
return tags.map(tag => tag.name)
}
}
但是我现在不知道如何在毫秒内进行序列化。有人可以帮我吗?
答案 0 :(得分:1)
使用method from this answer,我们可以获得相应的Unix毫秒纪元:
import os
import cv2
import keras
import numpy as np
from keras.models import load_model
new_model = load_model('/path/to/mymodel.h5')
test_dir = '/path/to/test-set'
test_imgs = ['/path/to/test-set/{}'.format(i) for i in os.listdir(test_dir)]
def read_and_process_image(list_of_images):
X = []
for image in list_of_images:
img = cv2.imread(image, cv2.IMREAD_COLOR)
X.append(cv2.resize(cv2.cvtColor(img, cv2.COLOR_BGR2RGB),
(299, 299), interpolation=cv2.INTER_CUBIC))
return X
X_test = read_and_process_image(test_imgs)
x = np.array(X_test)
test_datagent = ImageDataGenerator(rescale=1./255)
class_names = ['neg','pos']
i = 100
plt.figure(figsize=(30,20))
for batch in test_datagent.flow(x, batch_size=1):
pred = new_model.predict(batch)
for j in range(len(batch)):
plt.subplot(100, 1, i+1)
plt.title(class_names[np.argmax(pred[j])])
imgplot = plt.imshow(batch[0])
plt.imsave(('/path/to/output/ {}.jpg'.format(
class_names[np.argmax(pred[j])] + str(i))), batch[j])
i -=1
if i == -1:
break
然后您只需要编写值:
var valueDto = (DateTimeOffset)(DateTime)value;
var milliseconds = (valueDto).ToUnixTimeMilliseconds();
结合起来,我们得到:
writer.WriteValue(milliseconds);