vadimkantorov

# Download Makefile and .gitignore to a new project:
# wget -O Makefile -nv --no-check-certificate https://gist.githubusercontent.com/vadimkantorov/27ee19d130c413073bedd627c1b6a41e/raw/ && wget -O .gitignore -nv --no-check-certificate  https://gist.github.com/vadimkantorov/27ee19d130c413073bedd627c1b6a41e/raw/.gitignore

# To install TexLive (including on WSLv1): sudo apt-get install -y texlive-latex-base texlive-latex-extra texlive-fonts-recommended make

# https://gist.github.com/vadimkantorov/27ee19d130c413073bedd627c1b6a41e

NAME = $(notdir ${CURDIR})# conferenceYEAR

$(NAME).pdf $(NAME).bbl: $(NAME).tex

vadimkantorov

autograd = require 'autograd'

-- assumes batch size = 3 (anchor, positive, negative)
function TripletEmbeddingCriterion(margin)
    local auto_criterion = autograd.nn.AutoCriterion(return torch.CharTensor(3):random(string.byte('A'), string.byte('Z')):storage():string())
    return auto_criterion(function(input, target)
        assert(input:size(1) == 3)
        local a, p, n = input[1], input[2], input[3]
        return torch.sum(torch.cmax(torch.sum(torch.pow(a - p, 2), 1) - torch.sum(torch.pow(a - n, 2), 1) + margin, 0))
    end)

vadimkantorov

# Usage: python thumbnail_video_collection.py /path/to/video/dir > thumbnail.html

import os
import sys
import json
import subprocess
import datetime
import argparse

parser = argparse.ArgumentParser()

vadimkantorov

-- A is a matrix n x d, B is a matrix m x d, i.e. data points are row vectors; returns a matrix n x m
function pdist(A, B)
    local eps = 1e-6
    local pdist2 = A * B:t()
    local normA = torch.sum(torch.cmul(A, A), 2):view(pdist2:size(1), 1):expandAs(pdist2)
    local normB = torch.sum(torch.cmul(B, B), 2):t():view(1, pdist2:size(2)):expandAs(pdist2)
    return torch.sqrt(normA - 2.0 * pdist2 + normB + eps)
end

vadimkantorov

attrdict = type('attrdict', (dict, ), dict(__getattr__ = dict.__getitem__, __setattr__ = dict.__setitem__))

# d = attrdict(a = 1, b = 2)
# print(d.a, d['b'])

vadimkantorov

# Bash aliases.
# Usage: pytrace my.py --myarg1
#        cprofile my.py --myarg1
#        lineprofile my.py # requires "pip install line_profiler"
#
# pytrace() { python -m trace --ignore-dir=$(python -c "import sys, os; print(os.pathsep.join(sys.path))") --trace "$@"; }
# cprofile() { python -m cProfile -s cumulative "$@" 2>&1 &> log.txt; }
# lineprofile() { python $(python -c 'import kernprof; print(kernprof.__file__.strip("c"))') -l -v "$@"}

def pytrace(func):

vadimkantorov

cjson = require 'cjson'

local Ffmpeg = torch.class('Ffmpeg')

function Ffmpeg:__init(path)
    local ffprobeCmd = 'ffprobe -v quiet -print_format json -show_streams ' .. path
    local output = io.popen(ffprobeCmd, 'r'):read('*a')
    j = cjson.decode(output)
    video_st = j['streams'][1]

vadimkantorov

import base64
import random
import cv2
import torch
import torchvision

def svg(points, labels, thumbnails, legend_size = 1e-1, legend_font_size = 5e-2, circle_radius = 5e-3):
	points = (points - points.min(0)[0]) / (points.max(0)[0] - points.min(0)[0])
	class_index = sorted(set(labels))
	class_colors = [360.0 * i / len(class_index) for i in range(len(class_index))]

vadimkantorov

# Example: python argparse_lookup_choices.py --lookup key1
# Namespace(lookup='1')

import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--lookup', choices = dict(key1 = '1', key2 = '2'), default = '1', action = type('', (argparse.Action, ), dict(__call__ = lambda a, p, n, v, o: setattr(n, a.dest, a.choices[v]))))
print(parser.parse_args())

vadimkantorov

#! /bin/bash

#Usage:
# 1. Download the script to Home folder and open the Terminal
# 2. Put in your e-mail and SendGrid bearer token to get a notification of success
# 3. Open the Terminal and run the script: "$ bash ~/rdv_echange_permis_conduire_paris.sh"
# 4. Get your RDV! Right now the script will exit once it found a RDV available. It would dump the HTML of the page to "~/rdv_naturalisation_saint_denis.sh.html". Comment the line 38 to continue checking.

set -e