Tzu-Heng Lin lzhbrian

## infinite_dataloader.py
from torch.utils.data import DataLoader


class InfiniteDataLoader(DataLoader):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        # Initialize an iterator over the dataset.
        self.dataset_iterator = super().__iter__()

    def __iter__(self):

## boto3-list-instances.py
import boto3
from termcolor import colored

ec2 = boto3.resource('ec2')

for i in ec2.instances.all():

    print("Id: {0}\tState: {1}\tLaunched: {2}\tRoot Device Name: {3}".format(
        colored(i.id, 'cyan'),
        colored(i.state['Name'], 'green'),

## create_user.sh
for i in $@
do
    # create user
    useradd --gid groupname --home-dir /nvme/$i --create-home --no-user-group --shell /bin/bash $i
    echo $i:$i | chpasswd
    # make folder a data path
    mkdir /data1/$i
    chown $i:groupname /data1/$i
done

## download.py
# this is from
# https://github.com/ox-vgg/vgg_face2/issues/2#issuecomment-461684945

import requests
import getpass
import sys

LOGIN_URL = "http://zeus.robots.ox.ac.uk/vgg_face2/login/"
FILE_URL = "http://zeus.robots.ox.ac.uk/vgg_face2/get_file?fname=vggface2_test.tar.gz"

## gen_video_interpolation.py
"""
Author: lzhbrian (https://lzhbrian.me)
Date: 2020.1.20
Note: mainly modified from: https://github.com/tkarras/progressive_growing_of_gans/blob/master/util_scripts.py#L50
"""

import numpy as np
from PIL import Image
import os
import scipy

## align_face.py
"""
brief: face alignment with FFHQ method (https://github.com/NVlabs/ffhq-dataset)
author: lzhbrian (https://lzhbrian.me)
date: 2020.1.5
note: code is heavily borrowed from
    https://github.com/NVlabs/ffhq-dataset
    http://dlib.net/face_landmark_detection.py.html

requirements:
    apt install cmake

## trim_detectron_model.py
import os
import torch
import argparse
from maskrcnn_benchmark.config import cfg
from maskrcnn_benchmark.utils.c2_model_loading import load_c2_format


def removekey(d, listofkeys):
    r = dict(d)
    for key in listofkeys:

## nasnet_fine_tuning_8clf_0.8850_0.9740.ipynb

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                lzhbrian
                / nasnet_fine_tuning_8clf_0.8850_0.9740.ipynb
            
            
              Created
              April 13, 2018 13:15
                — forked from ypwhs/nasnet_fine_tuning_8clf_0.8850_0.9740.ipynb
            
          
      Sorry, something went wrong. Reload?
      Sorry, we cannot display this file.
      Sorry, this file is invalid so it cannot be displayed.
      
          Viewer requires iframe.
      
    
## upload_img.html
  <script>

    var MAX_WIDTH = 300;
    var MAX_HEIGHT = 400;

    var dataurl_user = null;
    var dataurl_celebrity = null;
    function handleFiles(inputid, imageid_to_show, mode)
    {
      var filesToUpload = document.getElementById(inputid).files;

## resize_img_before_upload.html

<img src="" id="image">
<input id="input" type="file" onchange="handleFiles()">

<script>
    function handleFiles()
    {
        var dataurl = null;
        var filesToUpload = document.getElementById('input').files;
        var file = filesToUpload[0];
	from torch.utils.data import DataLoader


	class InfiniteDataLoader(DataLoader):
	def __init__(self, args, *kwargs):
	super().__init__(args, *kwargs)
	# Initialize an iterator over the dataset.
	self.dataset_iterator = super().__iter__()

	def __iter__(self):
	import boto3
	from termcolor import colored

	ec2 = boto3.resource('ec2')

	for i in ec2.instances.all():

	print("Id: {0}\tState: {1}\tLaunched: {2}\tRoot Device Name: {3}".format(
	colored(i.id, 'cyan'),
	colored(i.state['Name'], 'green'),
	for i in $@
	do
	# create user
	useradd --gid groupname --home-dir /nvme/$i --create-home --no-user-group --shell /bin/bash $i
	echo $i:$i \| chpasswd
	# make folder a data path
	mkdir /data1/$i
	chown $i:groupname /data1/$i
	done
	# this is from
	# https://github.com/ox-vgg/vgg_face2/issues/2#issuecomment-461684945

	import requests
	import getpass
	import sys

	LOGIN_URL = "http://zeus.robots.ox.ac.uk/vgg_face2/login/"
	FILE_URL = "http://zeus.robots.ox.ac.uk/vgg_face2/get_file?fname=vggface2_test.tar.gz"
	"""
	Author: lzhbrian (https://lzhbrian.me)
	Date: 2020.1.20
	Note: mainly modified from: https://github.com/tkarras/progressive_growing_of_gans/blob/master/util_scripts.py#L50
	"""

	import numpy as np
	from PIL import Image
	import os
	import scipy
	"""
	brief: face alignment with FFHQ method (https://github.com/NVlabs/ffhq-dataset)
	author: lzhbrian (https://lzhbrian.me)
	date: 2020.1.5
	note: code is heavily borrowed from
	https://github.com/NVlabs/ffhq-dataset
	http://dlib.net/face_landmark_detection.py.html

	requirements:
	apt install cmake
	import os
	import torch
	import argparse
	from maskrcnn_benchmark.config import cfg
	from maskrcnn_benchmark.utils.c2_model_loading import load_c2_format


	def removekey(d, listofkeys):
	r = dict(d)
	for key in listofkeys:
	<script>

	var MAX_WIDTH = 300;
	var MAX_HEIGHT = 400;

	var dataurl_user = null;
	var dataurl_celebrity = null;
	function handleFiles(inputid, imageid_to_show, mode)
	{
	var filesToUpload = document.getElementById(inputid).files;

	<img src="" id="image">
	<input id="input" type="file" onchange="handleFiles()">

	<script>
	function handleFiles()
	{
	var dataurl = null;
	var filesToUpload = document.getElementById('input').files;
	var file = filesToUpload[0];