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try: import simplejson as json | |
except ImportError: import json | |
import os | |
import urllib, urlparse | |
import glob | |
import numpy as np | |
import Image | |
from itertools import combinations | |
import simplejson as json |
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imlist=[] | |
for infile in glob.glob( os.path.join(path, '*.jpg') ): | |
imlist.append(infile) | |
imlist=np.sort(imlist) | |
features = np.zeros([len(imlist),512]) | |
for i,f in enumerate(imlist): | |
im = np.array(Image.open(f)) | |
h, edges = np.histogramdd(im.reshape(-1,3),8,normed=True, range=[(0,255),(0,255),(0,255)]) |
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def get_alpha_shape(infile,radius): | |
command = "%s -A -aa %s -r -m10000000 -oN -oFpoints < %s" % (hull_path, str(radius), infile) | |
print >> sys.stderr, "Running command: %s" % command | |
retcode = subprocess.call(command, shell=True) | |
results_file = open("points-alf") | |
results_file.next() | |
results_indices = [[int(i) for i in line.rstrip().split()] for line in results_file] | |
results_file.close() | |
return results_indices |
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hull_path = "./hull" | |
infile='C.txt' | |
with open(infile, 'w') as f: | |
np.savetxt(f, C.T, delimiter=' ', fmt="%0.7f %0.7f\n") | |
radius=1 | |
indices = get_alpha_shape(infile,radius) | |
alpha=C.T[indices] | |
plot(C[0],C[1],'.'), plot(alpha[1:].T[0],alpha[1:].T[1],'r') | |
savefig("C_radius="+str(radius)+".png") |
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import numpy as np | |
from scipy.cluster.vq import kmeans,vq | |
from pylab import * | |
def patchwork(data,numsegs,numclass): | |
# computing K-Means with K = numsegs | |
centroids,_ = kmeans(data,numsegs) | |
# assign each sample to a cluster | |
idx,_ = vq(data,centroids) | |
# loop through number of classes |
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CC = gcc | |
AR = ar | |
OBJS = hull.o ch.o io.o rand.o pointops.o fg.o | |
HDRS = hull.h points.h pointsites.h stormacs.h | |
SRC = hull.c ch.c io.c rand.c pointops.c fg.c | |
PROG = hull | |
BINDIR = /usr/bin | |
LIBDIR = /usr/lib64 # or just /usr/lib on a 32 bit machine? | |
LIB = $(LIBDIR)/lib$(PROG).a |
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s = urlread('http://s1270.photobucket.com/albums/SERVERNAME/YOURUSERNAME/YOURALBUMNAME/?start=all'); | |
indices = regexp(s,'pbthumburl='); | |
for k=1:length(indices) | |
tmp=strtrim(s(indices(k):indices(k)+100)); | |
tmp=tmp(regexp(tmp,'"','once')+1:end); | |
tmp=tmp(1:regexp(tmp,'"','once')-1); | |
system(['wget ',tmp(1:regexp(tmp,'th_')-1),tmp(regexp(tmp,'th_')+3:end)]); | |
end |
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function P = bwconvhull_alt(BW) | |
% usage: P is a binary image wherein the convex hull of objects are returned, BW is the input binary image | |
% P= bwconvhull_alt(BW); | |
warning off all | |
s=regionprops(logical(BW),'ConvexImage','BoundingBox'); | |
P=zeros(size(BW)); | |
for no=1:length(s) | |
P(s(no).BoundingBox(2):s(no).BoundingBox(2)+s(no).BoundingBox(4)-1,... |
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addpath(genpath('~/googleearth')) | |
dat=importdata('myFile.csv'); | |
maps=dat.textdata(:,2); | |
prices=dat.data; | |
for i=1:size(maps,1) | |
address=char(maps(i,:)); | |
address=address(regexp(address,'loc')+3:end); |
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function [lat,lon] = geocode(address) | |
fid=fopen('test.py','wt'); | |
fprintf(fid,'%s\n','from pygeocoder import Geocoder'); | |
fprintf(fid,'%s\n',['results = Geocoder.geocode(''',deblank(address),''')']); | |
fprintf(fid,'%s\n','print results[0].coordinates'); | |
fclose(fid); | |
[stat1,stat2]=system('python test.py'); | |
stat2=deblank(stat2); |