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#for equation 3 | |
\begin{align*} | |
\alpha &= | |
\begin{cases} | |
\tan^{-1}{\frac{|J_{2x}-J_{1x}|}{|J_{2y}-J_{1y}|}} & J_{2y} \neq J_{1y}\\ | |
\pi/2 & J_{2y} = J_{1y} | |
\end{cases} \\ \noalign{\vskip10pt} | |
\beta &= | |
\begin{cases} |
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#Author: Md Mahedi Hasan | |
#Date : 10/02/2019 | |
#Description: Code for character segmentation in image | |
import cv2 | |
import operator | |
import numpy as np | |
from matplotlib import pyplot as plt | |
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# @Author: A Cup of Tea | |
# @Content: Gantt Chart for publishing a magazine within 3 month | |
import plotly.figure_factory as ff | |
df = [dict(Task="Assigning articles to writers", Start='2019-10-05', Finish='2019-10-25'), | |
dict(Task="Knocking Writers", Start='2019-10-05', Finish='2019-10-30'), | |
dict(Task="Collecting Articles", Start='2019-10-15', Finish='2019-11-10'), | |
dict(Task="Initial Review", Start='2019-10-15', Finish='2019-10-30'), | |
dict(Task="Request to Re-write", Start='2019-10-15', Finish='2019-11-15'), |
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#!/bin/bash | |
# Openpose required CMake version >= 3.12 | |
# remove previous verison | |
sudo yum remove cmake | |
# set new version | |
version=3.14 | |
build=6 |
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## Refer to http://caffe.berkeleyvision.org/installation.html | |
# Contributions simplifying and improving our build system are welcome! | |
# cuDNN acceleration switch (uncomment to build with cuDNN). | |
USE_CUDNN := 1 | |
# CPU-only switch (uncomment to build without GPU support). | |
# CPU_ONLY := 1 | |
# uncomment to disable IO dependencies and corresponding data layers |
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#Sample 1 | |
x = c(70, 60, 30, 80, 40, 100, 65, 20, 55, 70, 50) | |
y = c(91, 53, 8, 62, 43, 86, 75, 45, 90, 10, 35) | |
z = c(82, 49, 31, 41, 56, 62, 50, 39, 43, 74, 65) | |
col = c("blue", "black", "green4") | |
x_tick = c(0, 18, 36, 54, 72, 90, 108, 126, 144, 162, 180) | |
#thicker lines | |
par(cex=1.25) |
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setEPS() | |
postscript("example.eps") | |
nm=c(98.45, 97.58, 98.75, 96.92, 99.41) | |
bag=c(56.23, 72.14, 72.73, 85.78, 87.10) | |
coat=c(16.93, 45.45, 41.50, 68.11, 55.13) | |
data=matrix(c(nm,bag,coat), ncol=3) | |
colnames(data)=c("normal", "bag", "coat") | |
rownames(data)=c("GEI+PCA", "SPAE", "GaitGAN", "PTSN", "Proposed") |
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""" | |
@Author: Md Mahedi Hasan | |
""" | |
# python modules | |
import re, random | |
import os, glob | |
from skimage import io, util | |
from scipy import ndarray, ndimage | |
from PIL import Image | |
import PIL |
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#!/bin/bash | |
# This gist preprocess goa dataset of over 543M samples (~94 GB) to around 170M samples with selected column (~6 GB) for research | |
# removing first 8 lines | |
sed -i '1,8d' goa_uniprot_all.gaf | |
# putting NA to missing values | |
sed -i "s/\t\t/\tNA\t/g" goa_uniprot_all.gaf | |
# making string to one single world | |
sed -i 's/ /-/g' goa_uniprot_all.gaf |
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#include <stdio.h> | |
#include <stdint.h> | |
#include <string.h> | |
//#include <stdlib.h> | |
int main(int argc, char* argv[]) | |
{ | |
uint32_t lfsr = 0xACE1ACE1u; | |
unsigned period = 0; |