ilyakava’s gists

ilyakava / ima_image_links

Created March 5, 2015 21:15

Ima images links

ilyakava / cube.cu

Created April 9, 2015 23:14

	#include <stdio.h>

	__global__ void cube(float * d_out, float * d_in){
	// Todo: Fill in this function
	int idx = threadIdx.x;
	float f = d_in[idx];
	d_out[idx] = f * f * f;
	}

	int main(int argc, char ** argv) {

ilyakava / opencv.sh

Last active August 29, 2015 14:18

	# On: Ubuntu 14.10 (Utopic Unicorn), used with opencv 2.4.11 and cuda-7.0 for Quadro NVS 510
	# Also successfuly tested On: Ubuntu 14.10 (Utopic Unicorn), used with opencv 3.0.0 and cuda-7.0 for Tesla K40c
	set -o errexit

	echo "Removing any pre-installed ffmpeg and x264"
	sudo apt-get -qq remove ffmpeg x264 libx264-dev libavcodec-dev libavformat-dev libavdevice-dev libavutil-dev
	echo "Installing ffmpeg from source"
	sudo apt-get -qq install git
	git clone git://source.ffmpeg.org/ffmpeg.git
	cd ffmpeg

ilyakava / test.cpp

Created April 12, 2015 19:02

	#include "opencv2/core/core_c.h"
	#include "opencv2/core/core.hpp"
	#include "opencv2/flann/miniflann.hpp"
	#include "opencv2/imgproc/imgproc_c.h"
	#include "opencv2/imgproc/imgproc.hpp"
	#include "opencv2/video/video.hpp"
	#include "opencv2/features2d/features2d.hpp"
	#include "opencv2/objdetect/objdetect.hpp"
	#include "opencv2/calib3d/calib3d.hpp"
	#include "opencv2/ml/ml.hpp"

ilyakava / logistic_sgd.py

Last active August 29, 2015 14:20

	"""
	This tutorial introduces logistic regression using Theano and stochastic
	gradient descent.

	Logistic regression is a probabilistic, linear classifier. It is parametrized
	by a weight matrix :math:`W` and a bias vector :math:`b`. Classification is
	done by projecting data points onto a set of hyperplanes, the distance to
	which is used to determine a class membership probability.

	Mathematically, this can be written as:

ilyakava / mlp.py

Last active August 29, 2015 14:21

	"""
	This tutorial introduces the multilayer perceptron using Theano.

	A multilayer perceptron is a logistic regressor where
	instead of feeding the input to the logistic regression you insert a
	intermediate layer, called the hidden layer, that has a nonlinear
	activation function (usually tanh or sigmoid) . One can use many such
	hidden layers making the architecture deep. The tutorial will also tackle
	the problem of MNIST digit classification.

ilyakava / time.cu

Created July 30, 2015 21:49

	#include <stdio.h>
	#include <stdlib.h>

	#define BLOCK_WIDTH 1000

	void print_array(int *array, int size)
	{
	printf("{ ");
	for (int i = 0; i < size; i++) { printf("%d ", array[i]); }
	printf("}\n");

ilyakava / epub.sh

Created August 2, 2015 12:02

Input an arg of a file of a list of links, get an output.epub of all those webpages concatenated

	#!/bin/bash

	COUNT=1

	for link in $(cat $1)
	do
	wget -O - -o /dev/null $link \| iconv -f iso8859-1 -t utf-8 > $COUNT.html
	COUNT=$(echo $COUNT + 1 \|bc)
	done

ilyakava / imagenet_for_nn.sh

Last active August 29, 2015 14:27

	# assumes the images have been downloaded from imagenet and are named:
	# bird.tar car.tar circle.tar flower.tar horse.tar house.tar mountain.tar tree.tar woman.tar

	TAGS=( car tree circle house mountain bird flower horse woman )
	# total=7577
	LIMS=( 738 797 836 839 849 853 856 895 914 )
	# list contents of tarballs and shave off file extension
	for tag in "${TAGS[@]}"; do tar -tf $tag.tar \| sed 's/.JPEG$//' > $tag.txt; done

	# append my chosen class numbers for each class (hand is the missing #2)

ilyakava / occlusion_heatmap.py

Last active October 1, 2015 20:38

	import matplotlib
	matplotlib.use('Agg')
	from skimage.io import imread
	matplotlib.rcParams.update({'font.size': 2})
	import matplotlib.pyplot as plt
	from mpl_toolkits.axes_grid1 import AxesGrid

	import sys
	import numpy as np
	import scipy.ndimage as nd

Ilya Kavalerov ilyakava