def on_dectectJointsButton_released(self):
#boneBinaryImage = age_determination.extract_Bones( self.mOrignialXRayImage )
QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
aClass = AgeDetermination()
aClass.setVerbosity( True )
self.mDetectedJoints=aClass.detect_joints_of_interest( self.mOrignialXRayImage )
#self.display_image( joint_marked_image )
QApplication.restoreOverrideCursor()
self.rateJointsButton.enabledChange(True)
def on_dectectJointsButton_released(self):
#boneBinaryImage = age_determination.extract_Bones( self.mOrignialXRayImage )
QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
aClass = AgeDetermination()
aClass.setVerbosity(True)
self.mDetectedJoints = aClass.detect_joints_of_interest(
self.mOrignialXRayImage)
#self.display_image( joint_marked_image )
QApplication.restoreOverrideCursor()
self.rateJointsButton.enabledChange(True)
def on_rateJointsButton_released(self):
QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
if (self.mDetectedJoints!=None):
scoreTable = np.loadtxt('scores/scores.txt')
aClass = AgeDetermination()
aClass.setVerbosity( True )
#[rateSum, okRatings]=aClass.rate_joints(self.mDetectedJoints,scoreTable)
#print "----- FINAL Score is " + str(rateSum) +" with " + str(okRatings)+" found ratings! ------"
print "Final prediction: " + str(aClass.rate_joints(self.mDetectedJoints,scoreTable))
else:
print "Detect joints first!"
QApplication.restoreOverrideCursor()
def on_rateJointsButton_released(self):
QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
if (self.mDetectedJoints != None):
scoreTable = np.loadtxt('scores/scores.txt')
aClass = AgeDetermination()
aClass.setVerbosity(True)
#[rateSum, okRatings]=aClass.rate_joints(self.mDetectedJoints,scoreTable)
#print "----- FINAL Score is " + str(rateSum) +" with " + str(okRatings)+" found ratings! ------"
print "Final prediction: " + str(
aClass.rate_joints(self.mDetectedJoints, scoreTable))
else:
print "Detect joints first!"
QApplication.restoreOverrideCursor()
#> ipython --pylab --deep-reload
import numpy as np
scores = np.loadtxt('../training/scores.txt')
import dicom
(reader, img) = dicom.open_image("../training/Case1.dcm")
from AgeDetermination import AgeDetermination
aClass = AgeDetermination()
aClass.detect_joints_of_interest(img)
# in ipython run ->
# run fromShell.py
#> ipython --pylab --deep-reload
import os
import numpy as np
import dicom
from AgeDetermination import AgeDetermination
from scipy.misc import imsave
#scores = np.loadtxt('../training/scores.txt')
aClass = AgeDetermination()
directory = '../extractedJoints'
if not os.path.exists(directory):
os.makedirs(directory)
#Add numbers of the working studies here:
okImg = [
1, 2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 15, 17, 19, 20, 21, 22, 23, 26, 27,
28, 29, 30, 33
]
for i in okImg:
(reader, img) = dicom.open_image("../training/Case" + str(i) + ".dcm")
fingers = aClass.detect_joints_of_interest(img)
if (len(fingers) == 2):
if (len(fingers['littleFinger']) == 3):
jointNum = 1
for joint in fingers['littleFinger']:
imsave(
#> ipython --pylab --deep-reload
import os
import numpy as np
import dicom
from AgeDetermination import AgeDetermination
from scipy.misc import imsave
import Image
scores = np.loadtxt('../training/scores.txt')
aClass = AgeDetermination()
directory = '../extractedJoints'
if not os.path.exists(directory):
os.makedirs(directory)
#Add numbers of the working studies here:
okImg=[1,3,10,23,28,29,30]
evaluatedFingers = ['littleFinger','middleFinger','thumb']
size=140*33,140
fingerImagesPool=dict()
for finger in evaluatedFingers:
images=list()
fingerImagesPool[finger]=images
imgLF1=Image.new('L',size)
images.append(imgLF1)
#> ipython --pylab --deep-reload
import numpy as np
scores = np.loadtxt('../training/scores.txt')
import dicom
(reader, img) = dicom.open_image("../training/Case1.dcm")
from AgeDetermination import AgeDetermination
aClass = AgeDetermination()
aClass.detect_joints_of_interest(img)
# in ipython run ->
# run fromShell.py
