vighneshbirodkar

Hello

vighneshbirodkar

Timer unit: 1e-06 s

Total time: 11.423 s
File: /home/vighnesh/git/scikit-image/skimage/future/graph/rag.py
Function: rag_boundary at line 324

Line #      Hits         Time  Per Hit   % Time  Line Contents
==============================================================
   324                                           @profile
   325                                           def rag_boundary(labels, edge_map, connectivity=2):

vighneshbirodkar

from PIL import Image, ImageDraw, ImageFont
import os
from PIL.ExifTags import TAGS
# get an image

fnt = ImageFont.truetype('Ubuntu-R.ttf', 30)

for name in os.listdir('images'):
    print name
    img = Image.open('images/' + name)

vighneshbirodkar

Programming Experience

A short descrition of sme of the things I have done.

C

• VigRedis : An in memory data-store implementing a subset of Redis protocol
• A proof of concept implementation of the [Ricart-Agarwala] (http://en.wikipedia.org/wiki/Ricart%E2%80%93Agrawala_algorithm) distribured mutual exclusion algorithm. See Source

Python

• GSoC 2013 Implmenting a Desktop and Web based UI for displaying images and vector graphics.

vighneshbirodkar

#                   NESTED SAMPLING MAIN PROGRAM
# (GNU General Public License software, (C) Sivia and Skilling 2006)
# This file was translated to Python by Issac Trotts in 2007.

from math import *
import random

# or so
DBL_MAX = 1e300

vighneshbirodkar

import random
import numpy as np
import time

class ABC:
    def __init__(self,x):
        self.prop = x
    def __lt__(self, other):
        return self.prop < other.prop    
    def __le__(self, other):

vighneshbirodkar

import numpy as np
import matplotlib.pyplot as plt


N = 4

# Custom, nx , LIL , CSR
# First data set
construct_mem1 = (10.92,29.47,8.03,17.17)
merge_mem1 = (11.26,29.89,8.28,476.95)

vighneshbirodkar

import sets
import sys
import memory_profiler as mp
import numpy as np


def test_list(n):
    a = np.zeros((n,),dtype = int)
    b = np.zeros((n,),dtype = int)
    del a

vighneshbirodkar

import graph
import time
import sys
import tiffile as tf
from skimage import io
from matplotlib import pyplot as plt
import numpy as np
import random
from skimage.morphology import watershed
from scipy.ndimage import label

vighneshbirodkar

import numpy as np
from scipy.sparse import *
import pygraphviz as pgv
import random

a = np.array([[1,0,0,0],
              [5,2,0,0],
              [1,7,2,0],
              [0,0,0,4]])