'''
Created on 23.02.2012
@author: Marcus
'''
from ImageProc import ImageProc
import cv
import os
if __name__ == '__main__':
images = ImageProc.getGrayscaleImages(ImageProc.readFiles("../Bilder/"))
resultImages = []
cannyResultImages = []
stack1 = images[0:31]
stack2 = images[59:65]
stack3 = images[80:85]
stack4 = images[92:102]
intervalls = [stack1, stack2, stack3, stack4]
names = []
for stack in intervalls:
count = 0
resultImage = 0
cannyResultImage = 0
for image in stack:
newCount = ImageProc.countWhitePixels(image, 70)
if (newCount > count):
count = newCount
resultImage = (image, count)
cannyResultImage = (ImageProc.getCanny(image), count)
resultImages.append(resultImage)
cannyResultImages.append(cannyResultImage)
'''
Created on 15.03.2012
@author: Marcus
'''
from ImageProc import ImageProc
import cv
import os
if __name__ == '__main__':
images = ImageProc.getGrayscaleImages(ImageProc.readFiles("../stack/"))
resultImages = []
stack1 = images[57:70]
stack2 = images[71:85]
stack3 = images[86:108]
intervalls = [stack1, stack2, stack3]
partialStacks = []
partialResults = []
partialLaplaceResults = []
for stack in intervalls:
partialStacks.append(ImageProc.buildPartialStacks(stack))
for partialStack in partialStacks[1]:
partialResults.append(ImageProc.findHoughMax(partialStack))
i = 0
print partialResults
for partialResult in partialResults:
partialLaplaceResults.append(ImageProc.getLaplace(partialResult))
resultImage = ImageProc.appendPartialImages(partialResults)
laplaceResultImage = ImageProc.appendPartialImages(partialLaplaceResults)
ImageProc.displayImage(laplaceResultImage, "res")
ImageProc.displayImage(resultImage, "res2")
for i in range(len(self.R_layer)):
y = np.array(
[np.array([1]) if i == el else np.array([0]) for el in y_type])
errors = self.train_neuron(X, y, self.R_layer[i])
#print(errors)
print("Perceptron: training OK")
if __name__ == "__main__":
X = []
y = []
N = 20
for i in range(10):
I = ImageProc(N, "training/%d/" % i)
X += I.get_pictures()
y += [i] * N
P = Perceptron(2000)
start_training = time.time()
P.train_network(X, y)
print("Training complite in %fsec" %
round(time.time() - start_training, 4))
print("\nTesting results:")
N = 25
avg = 0
for i in range(10):
I = ImageProc(N, "testing/%d/" % i)
X = I.get_pictures()
'''
Created on 09.05.2012
@author: Marcus
'''
from ImageProc import ImageProc
if __name__ == '__main__':
template = ImageProc.getGrayscaleImages(ImageProc.getImage(r'Images\template.bmp'))
templateBright = ImageProc.brighten(template)
ImageProc.saveImage(templateBright, r'Images\template_bright.bmp')
image = ImageProc.getGrayscaleImages(ImageProc.getImage(r'Images\templa.png.bmp'))
sample = ImageProc.getGrayscaleImages(ImageProc.getImage(r'Images\Package142.bmp'))
ImageProc.displayImage(sample, 'samp')
ImageProc.displayImage(image, 'inverted')
for i in xrange(0, image.height):
for j in xrange(0, image.width):
if image[i, j] > 50:
image[i, j] = 255
ImageProc.displayImage(image, 'inverted2')
ImageProc.saveImage(image, r'Images\templa_invert4')
'''
Created on 05.05.2012
@author: Marcus
'''
from ImageProc import ImageProc
if __name__ == '__main__':
image = ImageProc.getGrayscaleImages(ImageProc.getImage(r'Images\Package142.bmp'))
resultImage = ImageProc.getGrayscaleImages(ImageProc.getImage(r'Images\Package142.bmp'))
template = ImageProc.getGrayscaleImages(ImageProc.getImage(r'Images\template.bmp'))
res = ImageProc.templateMatching(image, template)
ImageProc.saveImage(res, r'Images\templa.png')
#image = ImageProc.getGrayscaleImages(ImageProc.getImage(r'Images\templa.png.bmp'))
#result = ImageProc.getBinaryImage(ImageProc.invert(image), 155)
#ImageProc.displayImage(result, 'inv')
"""
Created on 05.05.2012
@author: Marcus
"""
from ImageProc import ImageProc
if __name__ == "__main__":
image = ImageProc.getGrayscaleImages(ImageProc.getImage(r"Bilder\Package142.bmp"))
resultImage = ImageProc.getCanny(image)
ImageProc.displayImage(image, "nocanny")
ImageProc.displayImage(resultImage, "canny")
ImageProc.saveImage(resultImage, r"Bilder\canny.png")
'''
Created on 09.03.2012
@author: Marcus
'''
from ImageProc import ImageProc
import cv
import os
if __name__ == '__main__':
images = ImageProc.getGrayscaleImages(ImageProc.readFiles("../Bilder/"))
stack1 = images[0:31]
stack2 = images[59:65]
stack3 = images[80:85]
stack4 = images[92:102]
intervalls = [stack1, stack2, stack3, stack4]
partialStacks = []
partialResults = []
partialCannyResults = []
for stack in intervalls:
partialStacks.append(ImageProc.buildPartialStacks(stack))
for partialStack in partialStacks[2]:
partialResults.append(ImageProc.findHoughMax(partialStack))
i = 0
for partialResult in partialResults:
partialCannyResults.append(ImageProc.getCanny(partialResult))
resultImage = ImageProc.appendPartialImages(partialResults)
cannyResultImage = ImageProc.appendPartialImages(partialCannyResults)
ImageProc.displayImage(cannyResultImage, "res")
ImageProc.displayImage(resultImage, "res2")
'''
Created on 23.02.2012
@author: Marcus
'''
"""
"""
from math import pi
from ImageProc import ImageProc
import cv
import os
if __name__ == '__main__':
images = ImageProc.getGrayscaleImages(ImageProc.readFiles("../Bilder/"))
resultImages = []
cannyResultImages = []
stack1 = images[0:31]
stack2 = images[59:65]
stack3 = images[80:85]
stack4 = images[92:102]
intervalls = [stack1, stack2, stack3, stack4]
lines = []
for stack in intervalls:
max = 0
resultImage = 0
cannyResultImage = 0
for image in stack:
storage = cv.CreateMemStorage(0)
canny = ImageProc.getCanny(image)
lines = cv.HoughLines2(canny, storage, cv.CV_HOUGH_PROBABILISTIC, 1, pi / 180, 50, 75, 10)
if (len(lines) > max):
'''
Created on 04.03.2012
@author: Marcus
'''
import cv
from ImageProc import ImageProc
if __name__ == '__main__':
image = ImageProc.getImage('t1.jpg')
image = ImageProc.getGrayscaleImages(image)
image = ImageProc.transformToRange(image, 0, 4)
dm = [[1, 3], [2, 0]]
image = ImageProc.dither(image, dm)
ImageProc.displayImage(image, 'img')
'''
Created on 10.04.2012
@author: Marcus
'''
from ImageProc import ImageProc
import cv
import os
if __name__ == '__main__':
image = ImageProc.getGrayscaleImages(ImageProc.getImage("hough92.bmp"))
binary = ImageProc.getBinaryImage(image, 30)
d = ImageProc.distanceTransformation(binary)
thres = ImageProc.valueBetweenThresholds(d, 20, 100)
'''Erosion'''
ImageProc.displayImage(d, "d")
ImageProc.displayImage(thres, "thres")
"""value = image[20, 20]
for i in xrange(0, image.height):
for j in xrange(0, image.width):
if (image[i, j] == value):
image[i, j] = 0"""
def main():
# Read images from dir
images = ImageProc.readFiles("Images/")
# The result image
resultImage = ImageProc.getImage(r'Images\Package142.bmp')
# Image6 serves as an example image
image6 = ImageProc.getImage(r'Images\Package142.bmp')
# The template
template = ImageProc.getImage(r'Images\Loetstelle2.bmp')
# Convert the images to grayscale images
grayImages = ImageProc.getGrayscaleImages(images)
# Convert the template to a grayscale image
templateGray = ImageProc.getGrayscaleImages(template)
# Calculate the keypoints and descriptors of the grayscale images
keypointsImages = ImageProc.getKeypoints(grayImages)
# Calculate the keypoints and descriptors of the grayscale template
(keypointsTemplate, descriptorTemplate) = ImageProc.getKeypoints(templateGray)
# Get the matching keypoints in the grayscale images for every keypoint in the grayscale template
matches = ImageProc.filterMatches(ImageProc.getMatches(keypointsImages, (keypointsTemplate, descriptorTemplate)))
print ("Anzahl d. Loetstellen: " + str(len(matches)))
(keypoints6, desc6) = keypointsImages[5]
# Draws the keypoints in the resulting images
keypointsImage1 = ImageProc.drawKeypoints(image6, keypoints6)
keypointsImage2 = ImageProc.drawKeypoints(template, keypointsTemplate)
matchingKeypointsImage = ImageProc.drawKeypoints(resultImage, matches)
ImageProc.safeMatches(matches)
#ImageProc.safeMatches(matches)
# Displays the resulting images
ImageProc.displayImage(ImageProc.getImage(r'Images\Package142.bmp'), 'image')
ImageProc.displayImage(keypointsImage1, 'key1')
ImageProc.displayImage(keypointsImage2, 'key2')
ImageProc.displayImage(matchingKeypointsImage, 'matches')
'''
Created on 09.05.2012
@author: Marcus
'''
from ImageProc import ImageProc
import cv
if __name__ == '__main__':
image = ImageProc.getGrayscaleImages(ImageProc.getImage(r'Images\templa2.bmp'))
'''minima = ImageProc.extractPartialImage(image, 0, 0)'''
minima = ImageProc.countLocalMinima(image)
ImageProc.saveImage(minima, r'Images\minima')
ImageProc.displayImage(minima, 'minima')
'''
Created on 23.02.2012
@author: Marcus
'''
from ImageProc import ImageProc
import cv
import os
"""Gets the picture with the most white pixels in the canny filtered picture"""
if __name__ == '__main__':
images = ImageProc.getGrayscaleImages(ImageProc.readFiles("../Bilder/"))
cannyImages = ImageProc.getCanny(images)
resultImages = []
resultCannyImages = []
stack1 = images[0:31]
stack2 = images[59:65]
stack3 = images[80:85]
stack4 = images[92:102]
intervalls = [stack1, stack2, stack3, stack4]
index = 0
for stack in intervalls:
resultImage = (stack[0], 0)
resultCannyImage = 0
count = 0
for image in stack:
canny = ImageProc.getCanny(image)
newCount = ImageProc.countWhiteCannyPixels(canny)
if (newCount > count):
resultImage = (image, newCount)
resultCannyImage = (canny, newCount)
