def Turnover(allbands,allmagnitudes,allcentroids,vb=False):

    # Models need good initial fluxes to avoid wasting time getting these 
    # right. Take a quick look at the data to do this:

    # 1) Get rough idea of object position from wcs of first image - works
    #    OK if all images are the same size and well registered, and the
    #    target is in the center of the field...
    ra, dec = 0.0, 0.0
    for radec in allcentroids: 
        ra += radec.ra
        dec += radec.dec
    ra, dec = ra/len(allcentroids), dec/len(allcentroids)
    centroid = tractor.RaDecPos(ra,dec)
    print "Mean flux-weighted centroid: ",centroid

    # 2) Get rough idea of total object magnitudes from median of images 
    #    in each filter. (Models have non-variable flux, by assumption!)
    bandnames = np.unique(allbands)
    magnitudes = np.zeros(len(bandnames))
    for i,bandname in enumerate(bandnames):
        index = np.where(allbands == bandname)
        magnitudes[i] = np.median(allmagnitudes[index])
    SED = tractor.Mags(order=bandnames, **dict(zip(bandnames,magnitudes)))
    if vb: print "Mean SED: ",SED

    return centroid,SED