gistfile1.py

        #cluster overlapping template matches 
        finalfs = FeatureSet()
        finalfs.append(fs[0])
        for f in fs:
            match = False
            for f2 in finalfs:
                if( f2.overlaps(f) ): #if they overlap
                    f2.consume(f) #merge them
                    match = True
                    break
            if( not match ):
                finalfs.append(f)
        for f in finalfs: #rescale the resulting clusters to fit the template size
            f.rescale(template_image.width,template_image.height)
        fs = finalfs
#             spread = 0.2*clusters  # search +/- 20% of guess
#             bestk = 0
#             best = 0
#             bestc = []
#             for k in range(clusters-spread,clusters+spread):
#                 result = scv.kmeans(fs.coordinates(),k) #do the kmeans and maximize the fit
#                 if( result[1] > best ):
#                     best = result[1] 
#                     bestk = k
#                     bestc = result[0]
#             print bestk
#             [bestc,derp] = scv.kmeans2(fs.coordinates(),bestk,iter=100,minit='points')
#             fs = FeatureSet()
#             for centroid in bestc:
#                 fs.append(TemplateMatch(self,template_image.getBitmap(), centroid, 1))