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@amoudgl
amoudgl / setup_visdom.md
Last active July 4, 2023 11:27
Setup Visdom on Remote Server

Setup Visdom on Remote Server

Install visdom on your local system and remote server.

pip3 install visdom

On remote server, do:

@cheind
cheind / show_annotations.py
Created February 25, 2018 11:37
BeaverDam dense annotation viewer
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({
@kevinzakka
kevinzakka / data_loader.py
Last active April 19, 2024 23:42
Train, Validation and Test Split for torchvision Datasets
"""
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
@bstriner
bstriner / wikimodel.py
Created March 8, 2017 03:44
Read output from wikiextractor
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