def changeHistogramEqu(self, hist): "linear", "sqrt", "log", "power", "asinh", "histeq" if hist == "linear": self.imageCV = cvSpace.linear(self.internalAstroImg.fitsFile[0].data) if hist == "sqrt": self.imageCV = cvSpace.sqrt(self.internalAstroImg.fitsFile[0].data) if hist == "log": self.imageCV = cvSpace.log(self.internalAstroImg.fitsFile[0].data) if hist == "power": self.imageCV = cvSpace.power(self.internalAstroImg.fitsFile[0].data) if hist == "asinh": self.imageCV = cvSpace.asinh(self.internalAstroImg.fitsFile[0].data) if hist == "histeq": self.imageCV = cvSpace.histeq(self.internalAstroImg.fitsFile[0].data) #this code maybe a method in astroImage NaNs = np.isnan(self.imageCV) self.imageCV[NaNs] = 0 inf = np.isinf(self.imageCV) self.imageCV[inf] = 0 self.internalAstroImg.imageCV = self.imageCV self.internalAstroImg.imageCVOriginal = self.imageCV.copy() self.internalAstroImg.thumb = ImageTk.PhotoImage(Image.fromarray(cv2.resize(self.imageCV, (100, 100)))) self.internalAstroImg.thumbDark = ImageTk.PhotoImage(Image.fromarray(cv2.resize(self.imageCV, (100, 100)))) self.internalAstroImg.thumbDifusse = ImageTk.PhotoImage(Image.fromarray(cv2.resize(self.imageCV, (100, 100)))) self.internalAstroImg.updateImage() self.setCanvas(self.internalAstroImg)
def openImage(self, path):
self.scaleFactor = 1
self.isFlipped = False
self.path = path
splitFilename, splitFileExtension = os.path.splitext(self.path)
self.name = os.path.basename(self.path)
self.isFits = False
self.eqName = ""
print "###########"+self.name
print "Filename "+splitFilename+" FileExtension "+splitFileExtension
if (splitFileExtension ==".fits" or splitFileExtension ==".FITS"):
self.isFits = True
print "Opening FISTS file"
self.fitsFile = fits.open(self.path)
print self.fitsFile.info()
self.imageCV = cvSpace.preEqualizaFits(self.fitsFile[0].data)
#self.imageCV = cvSpace.linear(self.fitsFile[0].data)
#self.imageCV = cvSpace.asinh(self.fitsFile[0].data,0.1)
self.imageCV = cvSpace.sqrt(self.fitsFile[0].data)
self.eqName = "sqrt"
#self.imageCV = cvSpace.log(self.fitsFile[0].data)
NaNs = np.isnan(self.imageCV)
self.imageCV[NaNs] = 0
inf = np.isinf(self.imageCV)
self.imageCV[inf] = 0
#self.imageCV = cvSpace.power(self.fitsFile[0].data, power_index=3)
#self.imageCV = cvSpace.histeq(self.fitsFile[0].data)
#self.imageCV = self.fitsFile[0].data
'''
self.imageCV = self.imageCV.astype(np.uint8)
self.imageCV = cv2.equalizeHist(self.imageCV)
'''
else:
#self.imageCV = cv2.imread(self.path,cv2.IMREAD_GRAYSCALE)
print "Cargando imagen noReal.jpg"
self.imageCV = cv2.imread(self.path, cv2.IMREAD_GRAYSCALE)
print "Image type "+str(type(self.imageCV))
print "Flux (max, min) = ("+str(self.imageCV.min())+", "+str(self.imageCV.max())+")"
self.imageCVOriginal = self.imageCV.copy()
self.thumb = ImageTk.PhotoImage(Image.fromarray(cv2.resize(self.imageCV, (100, 100))))
self.thumbDark = ImageTk.PhotoImage(Image.fromarray(cv2.resize(self.imageCV, (100, 100))))
self.thumbDifusse = ImageTk.PhotoImage(Image.fromarray(cv2.resize(self.imageCV, (100, 100))))
self.updateImage()
