Install visdom on your local system and remote server.
pip3 install visdom
On remote server, do:
import cv2 | |
import json | |
import pandas as pd | |
import numpy as np | |
def convert_to_pandas(content): | |
events = [] | |
for obj in content: | |
for f in obj['frames']: | |
events.append({ |
""" | |
Create train, valid, test iterators for CIFAR-10 [1]. | |
Easily extended to MNIST, CIFAR-100 and Imagenet. | |
[1]: https://discuss.pytorch.org/t/feedback-on-pytorch-for-kaggle-competitions/2252/4 | |
""" | |
import torch | |
import numpy as np |
import glob | |
import os | |
import json | |
class WikiDoc(object): | |
def __init__(self, url, text, id, title): | |
self.url = url | |
self.text = text | |
self.id = id |
from PIL import Image | |
import sys | |
import os | |
import math | |
import numpy as np | |
########################################################################################### | |
# script to generate moving mnist video dataset (frame by frame) as described in | |
# [1] arXiv:1502.04681 - Unsupervised Learning of Video Representations Using LSTMs | |
# Srivastava et al |