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)))