def extract_dir(inputdir, outputdir, options):
if (inputdir[-1] == "/"):
inputdir = inputdir[:-1]
if (outputdir[-1] == "/"):
outputdir = outputdir[:-1]
ct = CurvePoint()
sc = CntSC()
das = CntDAS()
agl = CntAngle()
allfile = os.listdir(inputdir)
to_file = options.ter
start_file = options.start
if (to_file == -1):
to_file = len(allfile)
if (to_file > len(allfile)):
to_file = len(allfile)
if (start_file < 0):
start_file = 0
for i in range(start_file, to_file):
f = allfile[i]
inputfile = inputdir + "/"+ f
outputfile = outputdir + "/" + f
ct.LoadCont(inputfile)
for c in ct.allselected:
if (options.shapecontext):
sc.ExtractFeature(c)
if (options.angle):
agl.ExtractFeature(c, 0)
if (options.das):
das.ExtractFeature(c, 0)
ct.Save(outputfile)
def main():
ct = CurvePoint()
sc = CntSC()
usage = "%prog [options] <pointfile>"
version = "%prog 0.2\nLongbin Chen, [email protected]"
oparser = optparse.OptionParser(usage=usage, version=version)
oparser.add_option('-o',
'--output',
dest='output',
default=None,
help='output file')
(options, args) = oparser.parse_args(sys.argv)
if len(args) != 2:
oparser.parse_args([sys.argv[0], "--help"])
sys.exit(1)
ct.LoadCont(args[1])
allkeys = []
for c in ct.allselected:
allkeys = allkeys + c
sc.ExtractFeature(allkeys)
if (options.output):
ct.Save(options.output)
def extract_file(input, output, options):
ct = CurvePoint()
sc = CntSC()
das = CntDAS()
agl = CntAngle()
ct.LoadCont(input)
for c in ct.allselected:
if (options.shapecontext):
sc.ExtractFeature(c)
if (options.angle):
agl.ExtractFeature(c, 0)
if (options.das):
das.ExtractFeature(c, 0)
ct.Save(output)
def main():
ct1 = CurvePoint()
ct2 = CurvePoint()
sc = CntSC()
ang = CntAngle()
usage = "%prog [options] <imgfile1> <imgfile2>"
version = "%prog 0.2\nLongbin Chen, [email protected]"
oparser = optparse.OptionParser(usage=usage, version=version)
oparser.add_option('-d', '--display', action="store_true", dest = 'display', default = False, help = 'display the image')
oparser.add_option('-n', '--number', dest = 'num', type="int", default = 200 , help = 'the number of feature points')
oparser.add_option('-s', '--save', dest = 'save', default = None, help = 'save the img file')
oparser.add_option('-o', '--output', dest = 'output', default = None, help = 'output file')
(options, args) = oparser.parse_args(sys.argv)
if len(args) != 3:
oparser.parse_args([sys.argv[0], "--help"])
sys.exit(1)
ct1.GetContour(args[1], options.num)
allkeys = []
for c in ct1.allselected:
allkeys = allkeys + c
sc.ExtractFeature(allkeys)
ang.ExtractFeature(allkeys,0);
allkeys = []
ct2.GetContour(args[2], options.num)
for c in ct2.allselected:
allkeys = allkeys + c
sc.ExtractFeature(allkeys)
ang.ExtractFeature(allkeys,0);
sumscore = []
matcher = SmithWaterman()
ct1.bDrawNumber = 0
ct2.bDrawNumber = 0
if (options.display):
ct1.DrawKeyPoints()
ct2.DrawKeyPoints()
myfont = cv.cvInitFont(cv.CV_FONT_HERSHEY_SIMPLEX, 0.5, 0.5)
idx = -1
putoriginal(args[1], ct1.drawimg)
putoriginal(args[2], ct2.drawimg)
cv.cvNot(ct1.drawimg, ct1.drawimg)
cv.cvNot(ct2.drawimg, ct2.drawimg)
for c1 in ct1.allselected:
idx += 1
cscore = -100000000
cpt1 = getdata(c1)
bX = []
bY = []
bestcurve = None
for c2 in ct2.allselected:
cpt2 = getdata(c2)
cost,align,X,Y = matcher.Align(cpt1, cpt2)
normalized_score = cost - log10(len(c2) + 1) * 1000
print len(c1), len(c2),cost, normalized_score, cscore
if (normalized_score > cscore):
cscore = normalized_score
bX = X[:]
bY = Y[:]
bestcurve = c2
if (options.display):
ptcount = 0
for i in range(len(bX)):
xi = bX[i]
yi = bY[i]
#if (xi == -1):
#cv.cvDrawCircle(ct2.drawimg, cv.cvPoint(int(bestcurve[yi].x), int(bestcurve[yi].y)),4, cv.cvScalar(255,0,0,0))
#cv.cvPutText(ct2.drawimg, 'O', cv.cvPoint(int(c2[yi].x), int(c2[yi].y)), myfont, cv.cvScalar(255, 0, 0,0))
#if (yi == -1):
#cv.cvDrawCircle(ct1.drawimg, cv.cvPoint(int(c1[xi].x), int(c1[xi].y)),4, cv.cvScalar(255,0,0,0))
#cv.cvPutText(ct1.drawimg, 'O', cv.cvPoint(int(c1[xi].x), int(c1[xi].y)), myfont, cv.cvScalar(255, 0, 0,0))
if (xi != -1 and yi != -1):
ptcount += 1
cv.cvDrawCircle(ct1.drawimg, cv.cvPoint(int(c1[xi].x), int(c1[xi].y)),2, clrs[idx])
cv.cvPutText(ct1.drawimg, str(ptcount), cv.cvPoint(int(c1[xi].x), int(c1[xi].y)), myfont, clrs[idx])
cv.cvDrawCircle(ct2.drawimg, cv.cvPoint(int(bestcurve[yi].x), int(bestcurve[yi].y)),2, clrs[idx])
cv.cvPutText(ct2.drawimg, str(ptcount), cv.cvPoint(int(bestcurve[yi].x), int(bestcurve[yi].y)), myfont, clrs[idx])
sumscore.append(cscore)
print sumscore
if (options.display):
highgui.cvNamedWindow ("contour1", 1)
highgui.cvNamedWindow ("contour2", 1)
highgui.cvShowImage ("contour1", ct1.drawimg)
highgui.cvShowImage ("contour2", ct2.drawimg)
highgui.cvWaitKey (0)
if (options.save):
mergeimg = mergeimage_83(ct1.drawimg, ct2.drawimg)
highgui.cvSaveImage("_sw_result.bmp", mergeimg)
def main():
ct1 = CurvePoint()
ct2 = CurvePoint()
agl = CntAngle()
sc = CntSC()
try:
opts, args = getopt.getopt(sys.argv[1:], "ho:dn:es", ["help", "output=", "draw", "num=", "even", "save"])
except getopt.GetoptError:
usage()
sys.exit(2)
output = None
bDraw = 0
bSave = 0
bOriginal = 0
npoint = 100
for o, a in opts:
if o == "-v":
ct1.verbose = 1
ct2.verbose = 1
if o in ("-h", "--help"):
usage()
sys.exit()
if o in ("-o", "--output"):
output = a
if o in ("-d", "--draw"):
bDraw = 1
if o in ("-s", "--save"):
bSave = 1
if o in ("-r", "--original"):
bOriginal = 1
if o in ("-n", "--num"):
npoint = string.atoi(a)
if o in ("-e", "--even"):
ct1.bEven = 1
ct2.bEven = 1
if (len(args)) != 2:
usage()
sys.exit(2)
ct1.GetContour(args[0], npoint)
allkeys = []
for c in ct1.allselected:
# agl.ExtractFeature(c, ct1.drawimg)
allkeys = allkeys + c
sc.ExtractFeature(allkeys)
allkeys = []
ct2.GetContour(args[1], npoint)
for c in ct2.allselected:
# agl.ExtractFeature(c, ct2.drawimg)
allkeys = allkeys + c
sc.ExtractFeature(allkeys)
sumscore = []
matcher = SmithWaterman()
ct1.bDrawNumber = 0
ct2.bDrawNumber = 0
if bDraw:
ct1.DrawKeyPoints()
ct2.DrawKeyPoints()
myfont = cv.cvInitFont(cv.CV_FONT_HERSHEY_SIMPLEX, 0.5, 0.5)
idx = -1
putoriginal(args[0], ct1.drawimg)
putoriginal(args[1], ct2.drawimg)
cv.cvNot(ct1.drawimg, ct1.drawimg)
cv.cvNot(ct2.drawimg, ct2.drawimg)
for c1 in ct1.allselected:
idx += 1
cscore = -100000000
cpt1 = getdata(c1)
bX = []
bY = []
bestcurve = None
for c2 in ct2.allselected:
cpt2 = getdata(c2)
cost, align, X, Y = matcher.Align(cpt1, cpt2)
normalized_score = cost - log10(len(c2) + 1) * 1000
print len(c1), len(c2), cost, normalized_score, cscore
if normalized_score > cscore:
cscore = normalized_score
bX = X[:]
bY = Y[:]
bestcurve = c2
if bDraw:
ptcount = 0
for i in range(len(bX)):
xi = bX[i]
yi = bY[i]
# if (xi == -1):
# cv.cvDrawCircle(ct2.drawimg, cv.cvPoint(int(bestcurve[yi].x), int(bestcurve[yi].y)),4, cv.cvScalar(255,0,0,0))
# cv.cvPutText(ct2.drawimg, 'O', cv.cvPoint(int(c2[yi].x), int(c2[yi].y)), myfont, cv.cvScalar(255, 0, 0,0))
# if (yi == -1):
# cv.cvDrawCircle(ct1.drawimg, cv.cvPoint(int(c1[xi].x), int(c1[xi].y)),4, cv.cvScalar(255,0,0,0))
# cv.cvPutText(ct1.drawimg, 'O', cv.cvPoint(int(c1[xi].x), int(c1[xi].y)), myfont, cv.cvScalar(255, 0, 0,0))
if xi != -1 and yi != -1:
ptcount += 1
cv.cvDrawCircle(ct1.drawimg, cv.cvPoint(int(c1[xi].x), int(c1[xi].y)), 2, clrs[idx])
cv.cvPutText(ct1.drawimg, str(ptcount), cv.cvPoint(int(c1[xi].x), int(c1[xi].y)), myfont, clrs[idx])
cv.cvDrawCircle(ct2.drawimg, cv.cvPoint(int(bestcurve[yi].x), int(bestcurve[yi].y)), 2, clrs[idx])
cv.cvPutText(
ct2.drawimg,
str(ptcount),
cv.cvPoint(int(bestcurve[yi].x), int(bestcurve[yi].y)),
myfont,
clrs[idx],
)
sumscore.append(cscore)
print sumscore
if bDraw:
highgui.cvNamedWindow("contour1", 1)
highgui.cvNamedWindow("contour2", 1)
highgui.cvShowImage("contour1", ct1.drawimg)
highgui.cvShowImage("contour2", ct2.drawimg)
highgui.cvWaitKey(0)
if bSave:
mergeimg = mergeimage_83(ct1.drawimg, ct2.drawimg)
highgui.cvSaveImage("_sw_result.bmp", mergeimg)
def main():
ct1 = CurvePoint()
ct2 = CurvePoint()
sc = CntSC()
ang = CntAngle()
usage = "%prog [options] <imgfile1> <imgfile2>"
version = "%prog 0.2\nLongbin Chen, [email protected]"
oparser = optparse.OptionParser(usage=usage, version=version)
oparser.add_option('-d',
'--display',
action="store_true",
dest='display',
default=False,
help='display the image')
oparser.add_option('-n',
'--number',
dest='num',
type="int",
default=200,
help='the number of feature points')
oparser.add_option('-s',
'--save',
dest='save',
default=None,
help='save the img file')
oparser.add_option('-o',
'--output',
dest='output',
default=None,
help='output file')
(options, args) = oparser.parse_args(sys.argv)
if len(args) != 3:
oparser.parse_args([sys.argv[0], "--help"])
sys.exit(1)
ct1.GetContour(args[1], options.num)
allkeys = []
for c in ct1.allselected:
allkeys = allkeys + c
sc.ExtractFeature(allkeys)
ang.ExtractFeature(allkeys, 0)
allkeys = []
ct2.GetContour(args[2], options.num)
for c in ct2.allselected:
allkeys = allkeys + c
sc.ExtractFeature(allkeys)
ang.ExtractFeature(allkeys, 0)
sumscore = []
matcher = SmithWaterman()
ct1.bDrawNumber = 0
ct2.bDrawNumber = 0
if (options.display):
ct1.DrawKeyPoints()
ct2.DrawKeyPoints()
myfont = cv.cvInitFont(cv.CV_FONT_HERSHEY_SIMPLEX, 0.5, 0.5)
idx = -1
putoriginal(args[1], ct1.drawimg)
putoriginal(args[2], ct2.drawimg)
cv.cvNot(ct1.drawimg, ct1.drawimg)
cv.cvNot(ct2.drawimg, ct2.drawimg)
for c1 in ct1.allselected:
idx += 1
cscore = -100000000
cpt1 = getdata(c1)
bX = []
bY = []
bestcurve = None
for c2 in ct2.allselected:
cpt2 = getdata(c2)
cost, align, X, Y = matcher.Align(cpt1, cpt2)
normalized_score = cost - log10(len(c2) + 1) * 1000
print len(c1), len(c2), cost, normalized_score, cscore
if (normalized_score > cscore):
cscore = normalized_score
bX = X[:]
bY = Y[:]
bestcurve = c2
if (options.display):
ptcount = 0
for i in range(len(bX)):
xi = bX[i]
yi = bY[i]
#if (xi == -1):
#cv.cvDrawCircle(ct2.drawimg, cv.cvPoint(int(bestcurve[yi].x), int(bestcurve[yi].y)),4, cv.cvScalar(255,0,0,0))
#cv.cvPutText(ct2.drawimg, 'O', cv.cvPoint(int(c2[yi].x), int(c2[yi].y)), myfont, cv.cvScalar(255, 0, 0,0))
#if (yi == -1):
#cv.cvDrawCircle(ct1.drawimg, cv.cvPoint(int(c1[xi].x), int(c1[xi].y)),4, cv.cvScalar(255,0,0,0))
#cv.cvPutText(ct1.drawimg, 'O', cv.cvPoint(int(c1[xi].x), int(c1[xi].y)), myfont, cv.cvScalar(255, 0, 0,0))
if (xi != -1 and yi != -1):
ptcount += 1
cv.cvDrawCircle(ct1.drawimg,
cv.cvPoint(int(c1[xi].x), int(c1[xi].y)),
2, clrs[idx])
cv.cvPutText(ct1.drawimg, str(ptcount),
cv.cvPoint(int(c1[xi].x), int(c1[xi].y)),
myfont, clrs[idx])
cv.cvDrawCircle(
ct2.drawimg,
cv.cvPoint(int(bestcurve[yi].x), int(bestcurve[yi].y)),
2, clrs[idx])
cv.cvPutText(
ct2.drawimg, str(ptcount),
cv.cvPoint(int(bestcurve[yi].x), int(bestcurve[yi].y)),
myfont, clrs[idx])
sumscore.append(cscore)
print sumscore
if (options.display):
highgui.cvNamedWindow("contour1", 1)
highgui.cvNamedWindow("contour2", 1)
highgui.cvShowImage("contour1", ct1.drawimg)
highgui.cvShowImage("contour2", ct2.drawimg)
highgui.cvWaitKey(0)
if (options.save):
mergeimg = mergeimage_83(ct1.drawimg, ct2.drawimg)
highgui.cvSaveImage("_sw_result.bmp", mergeimg)
