Example #1
0
     # Add to list
     fileList.extend(tempFile.readlines())
     tempFile.close()
 # Remove newlines
 fileList = [file[: len(file) - 1] for file in fileList]
 # Grab image size
 image = pl.imread(fileList[0])
 (Y, X) = np.shape(image)
 # Grab total number of frames
 numFrames = len(fileList)
 # Set output filename
 outputFileName = outputFileDir + "depth_0" + str(eyeVal) + ".pvp"
 # Open output file
 outMatFile = open(outputFileName, "wb")
 # Write out header
 writeHeaderFile(outMatFile, (Y, X, numBins), numFrames)
 # Calculate stepSize based on number of bins
 stepSize = float(1) / numBins
 normVal = 1 / (stepSize * sqrt(2 * pi))
 for frameIdx, depthFile in enumerate(fileList):
     print "Creating file", depthFile
     image = pl.imread(depthFile)
     # Make sure the size is the same
     (Ytest, Xtest) = np.shape(image)
     assert Y == Ytest and X == Xtest
     depthMat = np.zeros((Y, X, numBins))
     binImage = np.zeros((Y, X, numBins))
     for bin in range(numBins):
         binupthresh = stepSize * (bin + 1)
         binlowthresh = stepSize * (bin)
         mat1 = image < binupthresh
Example #2
0
    for binRange in range(-numSigma, numSigma+1):
        curBin = bin + binRange
        if curBin < 0 or curBin >= numBins:
            continue
        upthresh = stepSize * (curBin + 1)
        lowthresh = stepSize * (curBin)
        #Calculate cumulative distribution
        #Using center of stepsize
        xVal = lowthresh + (float(upthresh - lowthresh)/2)
        outmat = (normpdf(xVal, idxMat, stepSize)) * binMat[:,:,bin]
        posMat[:, :, curBin] += outmat[:,:]
        #Normalize with mean/std
        matMean = np.mean(posMat)
        matStd = np.std(posMat)
        posMat = (posMat - matMean) * (targetStd/matStd) + targetMean
writeHeaderFile(outMatFile, (Y, X, numBins), 1)
writeData(outMatFile, posMat, 1)
outMatFile.close()





#y, x, z = posMat.nonzero()
#
#fig = plt.figure()
#ax = Axes3D(fig)
#ax.scatter(x, z, -y, zdir = 'z', color = 'r')
#plt.show()

Example #3
0
    for binRange in range(-numSigma, numSigma + 1):
        curBin = bin + binRange
        if curBin < 0 or curBin >= numBins:
            continue
        upthresh = stepSize * (curBin + 1)
        lowthresh = stepSize * (curBin)
        #Calculate cumulative distribution
        #Using center of stepsize
        xVal = lowthresh + (float(upthresh - lowthresh) / 2)
        outmat = (normpdf(xVal, idxMat, stepSize)) * binMat[:, :, bin]
        posMat[:, :, curBin] += outmat[:, :]
        #Normalize with mean/std
        matMean = np.mean(posMat)
        matStd = np.std(posMat)
        posMat = (posMat - matMean) * (targetStd / matStd) + targetMean
writeHeaderFile(outMatFile, (Y, X, numBins), 1)
writeData(outMatFile, posMat, 1)
outMatFile.close()

#y, x, z = posMat.nonzero()
#
#fig = plt.figure()
#ax = Axes3D(fig)
#ax.scatter(x, z, -y, zdir = 'z', color = 'r')
#plt.show()

#Write out header
#only 1 frame
#   writeHeaderFile(outMatFile, (Y, X, numBins), 1)

#for bin in range(numBins):
Example #4
0
     #Add to list
     fileList.extend(tempFile.readlines())
     tempFile.close()
 #Remove newlines
 fileList = [file[:len(file) - 1] for file in fileList]
 #Grab image size
 image = pl.imread(fileList[0])
 (Y, X) = np.shape(image)
 #Grab total number of frames
 numFrames = len(fileList)
 #Set output filename
 outputFileName = outputFileDir + "depth_0" + str(eyeVal) + ".pvp"
 #Open output file
 outMatFile = open(outputFileName, 'wb')
 #Write out header
 writeHeaderFile(outMatFile, (Y, X, numBins), numFrames)
 #Calculate stepSize based on number of bins
 stepSize = float(1) / numBins
 normVal = 1 / (stepSize * sqrt(2 * pi))
 for frameIdx, depthFile in enumerate(fileList):
     print "Creating file", depthFile
     image = pl.imread(depthFile)
     #Make sure the size is the same
     (Ytest, Xtest) = np.shape(image)
     assert (Y == Ytest and X == Xtest)
     depthMat = np.zeros((Y, X, numBins))
     binImage = np.zeros((Y, X, numBins))
     for bin in range(numBins):
         binupthresh = stepSize * (bin + 1)
         binlowthresh = stepSize * (bin)
         mat1 = image < binupthresh