def main(): # test case
print('start!!!!!')
ima = ImgIO.ImgIO()
ima.read_image("y.jpg")
sin_r, sin_g, sin_b = sin(ima)
imc = ImgIO.ImgIO()
imc.read_list(sin_r, sin_g, sin_b, "final7.png", ima.width, ima.height)
imc.write_image("final7.png")
def main(): # test case
print('start!!!!!')
ima = ImgIO.ImgIO()
ima.read_image("y.jpg")
pwr_r, pwr_g, pwr_b = pwr(ima, 2)
imc = ImgIO.ImgIO()
imc.read_list(pwr_r, pwr_g, pwr_b, "final5.png", ima.width, ima.height)
imc.write_image("final5.png")
def main(): # test case
print('start!!!!!')
ima = ImgIO.ImgIO()
ima.read_image("y.jpg")
e_r, e_g, e_b = e(ima, 2)
imc = ImgIO.ImgIO()
imc.read_list(e_r, e_g, e_b, "final6.png", ima.width, ima.height)
imc.write_image("final6.png")
def main(): # test case
print('start!!!!!')
ima = ImgIO.ImgIO()
ima.read_image("y.jpg")
log_r, log_g, log_b = log(ima, 2)
imc = ImgIO.ImgIO()
imc.read_list(log_r, log_g, log_b, "final10.png", ima.width, ima.height)
imc.write_image("final10.png")
def main(): # test case
print('start!!!!!')
ima = ImgIO.ImgIO()
ima.read_image("y.jpg")
cos_r, cos_g, cos_b = cos(ima)
imc = ImgIO.ImgIO()
imc.read_list(cos_r, cos_g, cos_b, "final8.png", ima.width, ima.height)
imc.write_image("final8.png")
def main(): # test case
print('start!!!!!')
ima = ImgIO.ImgIO()
imb = ImgIO.ImgIO()
ima.read_image("y.jpg")
imb.read_image("test1.png")
sub_r, sub_g, sub_b = sub(ima, imb)
imc = ImgIO.ImgIO()
imc.read_list(sub_r, sub_g, sub_b, "final2.png", ima.width, ima.height)
imc.write_image("final2.png")
def main(): # test case
print('start!!!!!')
ima = ImgIO.ImgIO()
imb = ImgIO.ImgIO()
ima.read_image("y.jpg")
imb.read_image("test1.png")
add_r, add_g, add_b = add(ima, imb)
imc = ImgIO.ImgIO()
imc.read_list(add_r, add_g, add_b, "final1.png", ima.width, ima.height)
imc.write_image("final1.png")
def main(): # test case
print('start!!!!!')
ima = ImgIO.ImgIO()
imb = ImgIO.ImgIO()
ima.read_image("y.jpg")
imb.read_image("test1.png")
div_r, div_g, div_b = div(ima, imb)
imc = ImgIO.ImgIO()
imc.read_list(div_r, div_g, div_b, "final4.png", ima.width, ima.height)
imc.write_image("final4.png")
def main(): # test case
print('start!!!!!')
ima = ImgIO.ImgIO()
imb = ImgIO.ImgIO()
ima.read_image("y.jpg")
imb.read_image("test1.png")
mult_r, mult_g, mult_b = mult(ima, imb)
imc = ImgIO.ImgIO()
imc.read_list(mult_r, mult_g, mult_b, "final3.png", ima.width, ima.height)
imc.write_image("final3.png")
def main():
#read in all data
print "CHANGE DIR BACK!"
dir=os.listdir('/home/johan/Desktop/tiles')
#temporary 1d array
a=[]
#a=np.ndarray([24,24])
for files in dir:
img=ImgIO.readFile('/home/johan/Desktop/tiles/'+files)
img2=ImgIO.resizeTo50(img)
a.append(img2)
#output a list of all images
return a
import intensity,ImgIO,batchRead,imgutil,cv2.cv as cv,cv2,numpy as np
all=batchRead.main()
#then import the image (already grayscaled)
target=ImgIO.readFile('target3.jpg')
(x,y)=target.shape
#new array:
img=np.ndarray((x,y,50,50),dtype=np.uint8)
map=intensity.toTuple(all)
for i in range(len(target)):
for j in range(len(target[i])):
#print (i,j)
targetedPixel=target[i][j]
tile=intensity.findTile(targetedPixel, map)
#arraywise copying:
print 'procesando pixel:'+str((i,j))
#print tile[m][n]
img[i][j]=tile
g=np.concatenate((img),axis=1)
g=np.concatenate((g),axis=1)
print g.shape
print g
ImgIO.writeImg(g,'/home/johan/Desktop/brian.jpg')
import ImgIO
import intensity
import batchRead
import numpy as np
import random
import cv2
import cv2.cv as cv
import imgutil
#first import all images and the target image
all=batchRead.main()
#then import the image (already grayscaled)
target=ImgIO.readFile('target.jpg')
(x,y)=target.shape
##build a new 4d array
#t=np.ndarray([x,y,50,50], dtype=np.uint8)
#build a new picture:
#this is for grayscale:
newConvertedImage = cv.CreateImage ((x*50, y*50), cv.IPL_DEPTH_8U, 1)
image=imgutil.cv2array(newConvertedImage)
#map=intensity.toMap(all)
map=intensity.toMap(all)
for i in range(len(target)):
for j in range(len(target[i])):
#print (i,j)
def main(str):
#should average be used here?
return int(np.mean(ImgIO.readFile(str)))
