def createBlindMatchFeatures(self, stars, featurePointPercentage=0.1, featureNum=8, searchRTimes=2, partitionNum=4):
oiMatch = CrossMatch(self.imgW, self.imgH)
oiData = oiMatch.filterStar(stars)
brightStarOi, darkStarOi = oiMatch.getBright(oiData, featurePointPercentage)
print("bright star number %d"%(brightStarOi.shape[0]))
print("dark star number %d"%(darkStarOi.shape[0]))
'''
tpos = brightStarOi[:,0:2].copy()
tpos[:,0] = tpos[:,0] + 20
self.saveReg(tpos, "data/reg%d.reg"%(stars.shape[0]), radius=4, width=1, color='green')
'''
oiMatch.createRegionIdx(darkStarOi, featureNum)
#oiMatch.statisticRegions()
#print("oiMatch.regSize=%f"%(oiMatch.regSize))
searchRadius = oiMatch.regSize*searchRTimes*10
#print("searchRadius=%f"%(searchRadius))
tXY = []
mchIdxs = []
for i, ts in enumerate(brightStarOi):
x = ts[0]
y = ts[1]
nN = oiMatch.getNearestN(x,y, searchRadius,featureNum)
#print("star %d match %d features"%(i, nN.shape[0]))
if len(nN)==featureNum:
tXY.append((x,y))
mchIdxs.append(nN)
return tXY, mchIdxs
def createBlindMatchFeatures(self,
stars,
featurePoint=160,
featureNum=10,
searchRTimes=2,
partitionNum=4):
oiMatch = CrossMatch()
oiData = oiMatch.filterStar(stars)
brightStarOi, darkStarOi = oiMatch.getBright(oiData, featurePoint)
'''
tpos = brightStarOi[:,0:2].copy()
tpos[:,0] = tpos[:,0] + 20
self.saveReg(tpos, "data/reg%d.reg"%(stars.shape[0]), radius=4, width=1, color='green')
'''
oiMatch.createRegionIdx(darkStarOi, featureNum)
#oiMatch.statisticRegions()
searchRadius = oiMatch.regSize * searchRTimes
tXY = []
mchIdxs = []
for i, ts in enumerate(brightStarOi):
x = ts[0]
y = ts[1]
nN = oiMatch.getNearestN(x, y, searchRadius, featureNum)
if len(nN) == featureNum:
tXY.append((x, y))
mchIdxs.append(nN)
return tXY, mchIdxs
def doAll(srcDir, oiFile, tiFile):
oiMatch = BlindMatch()
tiMatch = BlindMatch()
oiData = np.loadtxt("%s/%s" % (srcDir, oiFile))
tiData = np.loadtxt("%s/%s" % (srcDir, tiFile))
#print("orign")
#print(oiData.shape)
#print(tiData.shape)
tiXY, mchIdxsTi = tiMatch.createBlindMatchFeatures(tiData)
oiXY, mchIdxsOi = oiMatch.createBlindMatchFeatures(oiData)
if len(tiXY) == 0:
print("%s create feature failure" % (tiFile))
elif len(oiXY) == 0:
print("%s create feature failure" % (oiFile))
else:
tarray = np.array(mchIdxsTi)
tDist = tarray[:, :, 2]
tiTree = KDTree(tDist)
totalMatchNum = 0
mchList = []
for i, oIdx in enumerate(mchIdxsOi):
td = oIdx[:, 2]
mchIdx = tiTree.query_ball_point(td, 20)
if len(mchIdx) > 0:
for ii, tidx0 in enumerate(mchIdx):
tdata00 = tarray[tidx0]
dm, isMchOk = oiMatch.blindDistMatch(oIdx, tdata00, 1, 5)
if isMchOk:
#print("query %d KDTree match %d, precisely match %dth with %d point"%(i, len(mchIdx), ii, len(dm)))
#print(dm)
omIdx = dm[:, 0]
tmIdx = dm[:, 1]
oxy01 = oiXY[i]
txy02 = tiXY[tidx0]
totalMatchNum += 1
opos = omIdx[:, 0:2]
tpos = tmIdx[:, 0:2]
oxy1 = np.concatenate([opos, [oxy01]])
txy1 = np.concatenate([tpos, [txy02]])
mchList.append((oxy1, txy1))
'''
ox1 = omIdx[:,0]
oy1 = omIdx[:,1]
tx2 = tmIdx[:,0]
ty2 = tmIdx[:,1]
oiMatch.plotBlindMatch(oxy01[0],oxy01[1],ox1,oy1,txy02[0],txy02[1],tx2,ty2)
'''
break
if len(mchList) > 1:
print("total Match key points %d" % (totalMatchNum))
starOiTi, xshift, yshift, xrotation, yrotation, blindStarNum = tiMatch.posTransPolynomial(
mchList, oiData, 2) # posTransPolynomial posTransPerspective
#print("fitting: xshift=%.2f, yshift=%.2f, xrotation=%.5f, yrotation=%.5f"%(xshift,yshift, xrotation, yrotation))
#print(starOiTi.shape)
mchRadius = 4
starttime = datetime.now()
crossMatch = CrossMatch()
#tiData = crossMatch.filterStar(tiData)
crossMatch.createRegionIdx(tiData)
#crossMatch.statisticRegions()
mchPosPairs, orgPosIdxs = crossMatch.xyMatch(starOiTi, mchRadius)
endtime = datetime.now()
runTime0 = (endtime - starttime).total_seconds() * 1000
#print("********** rematch %s use %d micro seconds"%(oiFile, runTime0))
#print(mchPosPairs.shape)
#print(mchPosPairs[:3])
mchRatios0, oiPosJoin0,tiPosJoin0, mchData0, xshift0,yshift0, xrms0, yrms0 \
= crossMatch.evaluateMatchResult(starOiTi, tiData, mchPosPairs)
#print(mchRatios0)
oiDataMch = oiData[orgPosIdxs]
#print(oiDataMch.shape)
#print(oiDataMch[:3])
oiMchPos = oiDataMch[:, 0:2]
tiMchPos = mchPosPairs[:, 2:4]
starOiTiPsp2 = tiMatch.posTransPerspective2(
oiMchPos, tiMchPos, oiData)
starOiTiPly2 = tiMatch.posTransPolynomial2(oiMchPos, tiMchPos,
oiData, 3)
starttime = datetime.now()
mchPosPairs, orgPosIdxs = crossMatch.xyMatch(starOiTiPsp2, 4)
endtime = datetime.now()
runTime1 = (endtime - starttime).total_seconds() * 1000
#print("********** rematch %s use %d micro seconds"%(oiFile, runTime1))
#print(mchPosPairs.shape)
#print(mchPosPairs[:3])
mchRatios1, oiPosJoin1,tiPosJoin1, mchData1, xshift1,yshift1, xrms1, yrms1 \
= crossMatch.evaluateMatchResult(starOiTiPsp2, tiData, mchPosPairs)
#print(mchRatios1)
starttime = datetime.now()
mchPosPairs, orgPosIdxs = crossMatch.xyMatch(starOiTiPly2, 4)
endtime = datetime.now()
runTime2 = (endtime - starttime).total_seconds() * 1000
#print("********** rematch %s use %d micro seconds"%(oiFile, runTime2))
#print(mchPosPairs.shape)
#print(mchPosPairs[:3])
mchRatios2, oiPosJoin2,tiPosJoin2, mchData2, xshift2,yshift2, xrms2, yrms2 \
= crossMatch.evaluateMatchResult(starOiTiPly2, tiData, mchPosPairs)
#print(mchRatios2)
rstStr = "%s %.2f %.2f %.2f %.2f %d %d "\
"%d %d "\
"%d %d %d %.2f %.2f %.2f %.2f %.2f %d "\
"%d %d %d %.2f %.2f %.2f %.2f %.2f %d "\
"%d %d %d %.2f %.2f %.2f %.2f %.2f %d \n"\
%(oiFile, xshift,yshift, xrotation, yrotation, blindStarNum, totalMatchNum, \
tiData.shape[0], oiData.shape[0], \
oiPosJoin0,tiPosJoin0, mchData0, mchRatios0, xshift0,yshift0, xrms0, yrms0,runTime0,\
oiPosJoin1,tiPosJoin1, mchData1, mchRatios1, xshift1,yshift1, xrms1, yrms1,runTime1,\
oiPosJoin2,tiPosJoin2, mchData2, mchRatios2, xshift2,yshift2, xrms2, yrms2,runTime2)
#print(rstStr)
print([mchData0, mchData1, mchData2])
print([mchRatios0, mchRatios1, mchRatios2])
print([xshift0, xshift1, xshift2])
''' '''
oiDataMch = oiData[orgPosIdxs]
oiDataNch = np.delete(oiData, orgPosIdxs, axis=0)
oiMchPos = oiDataMch[:, 0:2].copy()
oiNchPos = oiDataNch[:, 0:2].copy()
oiMchPos[:, 0] = oiMchPos[:, 0] + 20
oiNchPos[:, 0] = oiNchPos[:, 0] + 20
tiMchPos = mchPosPairs[:, 2:4]
crossMatch1 = CrossMatch()
crossMatch1.createRegionIdx(tiMchPos)
mchPosPairs, orgPosIdxs = crossMatch1.xyMatch(tiData, 1)
#print(tiData.shape)
#print(tiMchPos.shape)
#print(len(orgPosIdxs))
tiDataNch = np.delete(tiData, orgPosIdxs, axis=0)
tiNchPos = tiDataNch[:, 0:2].copy()
tiMchPos[:, 0] = tiMchPos[:, 0] + 20
tiNchPos[:, 0] = tiNchPos[:, 0] + 20
#print(tiNchPos.shape)
tiMatch.saveReg(oiMchPos,
"data/OiMch.reg",
radius=4,
width=1,
color='green')
tiMatch.saveReg(oiNchPos,
"data/OiNch.reg",
radius=5,
width=1,
color='blue')
tiMatch.saveReg(tiMchPos,
"data/TiMch.reg",
radius=4,
width=1,
color='red')
tiMatch.saveReg(tiNchPos,
"data/TiNch.reg",
radius=5,
width=1,
color='yellow')
def doAll(tiPath, tiFile, oiPath, oiFile, oiImgPath, oiImgFile, savePath, origImgName, templateImgName):
#imgW=800
#imgH=800
imgW=2400
imgH=2400
oiMatch = BlindMatch(imgW, imgH)
tiMatch = BlindMatch(imgW, imgH)
oiData = np.loadtxt("%s/%s"%(oiPath, oiFile))
tiData = np.loadtxt("%s/%s"%(tiPath, tiFile))
print("oiData=%d"%(oiData.shape[0]))
print("tiData=%d"%(tiData.shape[0]))
tiXY, mchIdxsTi = tiMatch.createBlindMatchFeatures(tiData)
oiXY, mchIdxsOi = oiMatch.createBlindMatchFeatures(oiData)
#print("mchIdxsTi=%d"%(len(mchIdxsTi)))
#print("mchIdxsOi=%d"%(len(mchIdxsOi)))
'''
tpath = "data/tipos%d.reg"%(len(tiXY))
print(tpath)
tiMatch.saveReg(tiXY, tpath, radius=18, width=3, color='red')
tpath = "data/oipos%d.reg"%(len(oiXY))
print(tpath)
tiMatch.saveReg(oiXY, tpath, radius=18, width=3, color='red')
tfeature = []
for td1 in mchIdxsTi:
for td2 in td1:
tfeature.append([td2[0],td2[1]])
tpath = "data/tifeature%d.reg"%(len(tfeature))
print(tpath)
tiMatch.saveReg(tfeature, tpath, radius=12, width=3, color='green')
tfeature = []
for td1 in mchIdxsOi:
for td2 in td1:
tfeature.append([td2[0],td2[1]])
tpath = "data/oifeature%d.reg"%(len(tfeature))
print(tpath)
tiMatch.saveReg(tfeature, tpath, radius=12, width=3, color='green')
'''
if len(tiXY)==0:
#print("%s create feature failure"%(tiFile))
return (-1,)
elif len(oiXY)==0:
#print("%s create feature failure"%(oiFile))
return (-1,)
else:
tarray = np.array(mchIdxsTi)
tDist = tarray[:,:,2]
tiTree = KDTree(tDist)
totalMatchNum = 0
mchList = []
for i, oIdx in enumerate(mchIdxsOi):
td = oIdx[:,2]
mchIdx = tiTree.query_ball_point(td, 90) #kdTree match
if len(mchIdx)>0:
for ii, tidx0 in enumerate(mchIdx):
tdata00 = tarray[tidx0]
dm, isMchOk = oiMatch.blindDistMatch(oIdx, tdata00, 1, 4) #blind match 8
if isMchOk:
#print("query %d KDTree match %d, precisely match %dth with %d point"%(i, len(mchIdx), ii, len(dm)))
#print(dm)
omIdx = dm[:,0]
tmIdx = dm[:,1]
oxy01 = oiXY[i]
txy02 = tiXY[tidx0]
totalMatchNum += 1
opos = omIdx[:,0:2]
tpos = tmIdx[:,0:2]
oxy1 = np.concatenate([opos,[oxy01]])
txy1 = np.concatenate([tpos,[txy02]])
mchList.append((oxy1,txy1))
'''
ox1 = omIdx[:,0]
oy1 = omIdx[:,1]
tx2 = tmIdx[:,0]
ty2 = tmIdx[:,1]
oiMatch.plotBlindMatch(oxy01[0],oxy01[1],ox1,oy1,txy02[0],txy02[1],tx2,ty2)
'''
break
if len(mchList)>1:
print("total Match key points %d"%(totalMatchNum))
starOiTi, xshift,yshift, xrotation, yrotation, blindStarNum = tiMatch.posTransPolynomial(mchList, oiData, 2) # posTransPolynomial posTransPerspective
print(xshift,yshift, xrotation, yrotation, blindStarNum)
mchRadius = 4
crossMatch = CrossMatch(imgW, imgH)
crossMatch.createRegionIdx(tiData)
mchPosPairs, orgPosIdxs = crossMatch.xyMatch(starOiTi, mchRadius)
oiDataMch = oiData[orgPosIdxs]
''' '''
oiMchPos = oiDataMch[:,0:2]
tiMchPos = mchPosPairs[:,2:4]
starOiTiPly2 = tiMatch.posTransPolynomial2(oiMchPos, tiMchPos, oiData, oiImgFile, oiImgPath, savePath, origImgName, templateImgName, 3)
mchPosPairs, orgPosIdxs = crossMatch.xyMatch(starOiTiPly2, 4)
#print(mchPosPairs.shape)
#print(mchPosPairs[:3])
mchRatios2, oiPosJoin2,tiPosJoin2, mchData2, xshift2,yshift2, xrms2, yrms2 \
= crossMatch.evaluateMatchResult(starOiTiPly2, tiData, mchPosPairs)
#print("mchRatios2, oiPosJoin2,tiPosJoin2, mchData2, xshift2,yshift2, xrms2, yrms2")
#print((mchRatios2, oiPosJoin2,tiPosJoin2, mchData2, xshift2,yshift2, xrms2, yrms2))
return (totalMatchNum, xshift,yshift, xrotation, yrotation, blindStarNum, mchRatios2)
else:
print("blindmatch: no feature point match")
return (0,)
def doAll(tiPath, tiFile, oiPath, oiFile, oiImgPath, oiImgFile, savePath,
origImgName, templateImgName):
oiMatch = BlindMatch()
tiMatch = BlindMatch()
oiData = np.loadtxt("%s/%s" % (oiPath, oiFile))
tiData = np.loadtxt("%s/%s" % (tiPath, tiFile))
tiXY, mchIdxsTi = tiMatch.createBlindMatchFeatures(tiData,
featurePoint=160)
oiXY, mchIdxsOi = oiMatch.createBlindMatchFeatures(oiData,
featurePoint=160)
if len(tiXY) == 0:
#print("%s create feature failure"%(tiFile))
return [
-1,
]
elif len(oiXY) == 0:
#print("%s create feature failure"%(oiFile))
return [
-1,
]
else:
tarray = np.array(mchIdxsTi)
tDist = tarray[:, :, 2]
tiTree = KDTree(tDist)
totalMatchNum = 0
mchList = []
for i, oIdx in enumerate(mchIdxsOi):
td = oIdx[:, 2]
mchIdx = tiTree.query_ball_point(td, 20) #kdTree match
if len(mchIdx) > 0:
for ii, tidx0 in enumerate(mchIdx):
tdata00 = tarray[tidx0]
dm, isMchOk = oiMatch.blindDistMatch(oIdx, tdata00, 1,
5) #blind match
if isMchOk:
#print("query %d KDTree match %d, precisely match %dth with %d point"%(i, len(mchIdx), ii, len(dm)))
#print(dm)
omIdx = dm[:, 0]
tmIdx = dm[:, 1]
oxy01 = oiXY[i]
txy02 = tiXY[tidx0]
totalMatchNum += 1
opos = omIdx[:, 0:2]
tpos = tmIdx[:, 0:2]
oxy1 = np.concatenate([opos, [oxy01]])
txy1 = np.concatenate([tpos, [txy02]])
mchList.append((oxy1, txy1))
break
if len(mchList) > 1:
#print("total Match key points %d"%(totalMatchNum))
starOiTi, xshift, yshift, xrotation, yrotation, blindStarNum = tiMatch.posTransPolynomial(
mchList, oiData, 2) # posTransPolynomial posTransPerspective
mchRadius = 4
crossMatch = CrossMatch()
crossMatch.createRegionIdx(tiData)
mchPosPairs, orgPosIdxs = crossMatch.xyMatch(starOiTi, mchRadius)
oiDataMch = oiData[orgPosIdxs]
oiGoodIdx = crossMatch.getGoodStarIndex(oiDataMch)
oiMchPos = oiDataMch[oiGoodIdx, 0:2]
tiMchPos = mchPosPairs[oiGoodIdx, 2:4]
try:
print("blindmatch oiGoodIdx=%d" % (oiGoodIdx.shape[0]))
starOiTiPly2, t2oX, t2oY = tiMatch.posTransPolynomial2(
oiMchPos, tiMchPos, oiData, oiImgFile, oiImgPath, savePath,
origImgName, templateImgName, 3)
crossMatch = CrossMatch()
crossMatch.createRegionIdx(tiData)
mchPosPairs, orgPosIdxs = crossMatch.xyMatch(starOiTiPly2, 1.5)
#print(mchPosPairs.shape)
#print(mchPosPairs[:3])
mchRatios2, oiPosJoin2,tiPosJoin2, mchData2, xshift2,yshift2, xrms2, yrms2 \
= crossMatch.evaluateMatchResult(starOiTiPly2, tiData, mchPosPairs)
#print("mchRatios2, oiPosJoin2,tiPosJoin2, mchData2, xshift2,yshift2, xrms2, yrms2")
#print((mchRatios2, oiPosJoin2,tiPosJoin2, mchData2, xshift2,yshift2, xrms2, yrms2))
return [
totalMatchNum, xshift, yshift, xrotation, yrotation,
blindStarNum, mchRatios2, oiPosJoin2, tiPosJoin2, mchData2,
xshift2, yshift2, xrms2, yrms2, t2oX, t2oY
]
except Exception as e:
print(str(e))
tstr = traceback.format_exc()
print(tstr)
return [0]
else:
print("blindmatch: no feature point match")
return [0]
def doBlindMatch(srcDir, oiFile, tiFile):
rstStr = ''
oiMatch = BlindMatch()
tiMatch = BlindMatch()
oiData = np.loadtxt("%s/%s" % (srcDir, oiFile))
tiData = np.loadtxt("%s/%s" % (srcDir, tiFile))
dateStr, camName, fwhmMean, fwhmRms, bkgMean, bkgRms = imgStatistic(
oiFile, oiData)
#print("orign")
#print(oiData.shape)
#print(tiData.shape)
try:
tiXY, mchIdxsTi = tiMatch.createBlindMatchFeatures(tiData)
if len(tiXY) == 0:
print("%s create feature failure" % (tiFile))
else:
tarray = np.array(mchIdxsTi)
tDist = tarray[:, :, 2]
tiTree = KDTree(tDist)
starttime = datetime.now()
#createBlindMatchFeatures(self, stars, featurePoint=160, featureNum=10, searchRTimes=2, partitionNum=4)
oiXY, mchIdxsOi = oiMatch.createBlindMatchFeatures(oiData)
if len(mchIdxsOi) == 0:
print("%s searchR %d create feature failure, reuse %d" %
(oiFile, 2, 2 * 2))
oiXY, mchIdxsOi = oiMatch.createBlindMatchFeatures(
oiData, searchRTimes=4)
totalMatchNum = 0
mchList = []
mchRadius = [20, 40, 100]
for mchR in mchRadius:
for i, oIdx in enumerate(mchIdxsOi):
td = oIdx[:, 2]
mchIdx = tiTree.query_ball_point(td, mchR)
if len(mchIdx) > 0:
for ii, tidx0 in enumerate(mchIdx):
tdata00 = tarray[tidx0]
dm, isMchOk = oiMatch.blindDistMatch(
oIdx, tdata00, 1, 5)
if isMchOk:
#print("query %d KDTree match %d, precisely match %dth with %d point"%(i, len(mchIdx), ii, len(dm)))
#print(dm)
omIdx = dm[:, 0]
tmIdx = dm[:, 1]
oxy01 = oiXY[i]
txy02 = tiXY[tidx0]
totalMatchNum += 1
opos = omIdx[:, 0:2]
tpos = tmIdx[:, 0:2]
oxy1 = np.concatenate([opos, [oxy01]])
txy1 = np.concatenate([tpos, [txy02]])
mchList.append((oxy1, txy1))
break
if len(mchList) > 5:
break
elif mchR < 100:
mchList = []
print("%s radius %d matchNum %d" %
(oiFile, mchR, len(mchList)))
endtime = datetime.now()
blindMatchTime = (endtime - starttime).total_seconds() * 1000
if len(mchList) > 1:
#print("total Match key points %d"%(totalMatchNum))
starOiTi, xshift, yshift, xrotation, yrotation, blindStarNum = tiMatch.posTransPolynomial(
mchList, oiData,
2) # posTransPolynomial posTransPerspective
#print("fitting: xshift=%.2f, yshift=%.2f, xrotation=%.5f, yrotation=%.5f"%(xshift,yshift, xrotation, yrotation))
#print(starOiTi.shape)
mchRadius = 4
starttime = datetime.now()
crossMatch = CrossMatch()
#tiData = crossMatch.filterStar(tiData)
crossMatch.createRegionIdx(tiData)
#crossMatch.statisticRegions()
mchPosPairs, orgPosIdxs = crossMatch.xyMatch(
starOiTi, mchRadius)
endtime = datetime.now()
runTime0 = (endtime - starttime).total_seconds() * 1000
mchRatios0, oiPosJoin0,tiPosJoin0, mchData0, xshift0,yshift0, xrms0, yrms0 \
= crossMatch.evaluateMatchResult(starOiTi, tiData, mchPosPairs)
oiDataMch = oiData[orgPosIdxs]
oiMchPos = oiDataMch[:, 0:2]
tiMchPos = mchPosPairs[:, 2:4]
starOiTiPsp2 = tiMatch.posTransPerspective2(
oiMchPos, tiMchPos, oiData)
starOiTiPly23 = tiMatch.posTransPolynomial2(
oiMchPos, tiMchPos, oiData, 3)
starOiTiPly25 = tiMatch.posTransPolynomial2(
oiMchPos, tiMchPos, oiData, 5)
starttime = datetime.now()
mchPosPairs, orgPosIdxs = crossMatch.xyMatch(
starOiTiPsp2, mchRadius)
endtime = datetime.now()
runTime1 = (endtime - starttime).total_seconds() * 1000
mchRatios1, oiPosJoin1,tiPosJoin1, mchData1, xshift1,yshift1, xrms1, yrms1 \
= crossMatch.evaluateMatchResult(starOiTiPsp2, tiData, mchPosPairs)
starttime = datetime.now()
mchPosPairs, orgPosIdxs = crossMatch.xyMatch(
starOiTiPly23, mchRadius)
endtime = datetime.now()
runTime2 = (endtime - starttime).total_seconds() * 1000
mchRatios2, oiPosJoin2,tiPosJoin2, mchData2, xshift2,yshift2, xrms2, yrms2 \
= crossMatch.evaluateMatchResult(starOiTiPly23, tiData, mchPosPairs)
starttime = datetime.now()
mchPosPairs, orgPosIdxs = crossMatch.xyMatch(
starOiTiPly25, mchRadius)
endtime = datetime.now()
runTime3 = (endtime - starttime).total_seconds() * 1000
mchRatios3, oiPosJoin3,tiPosJoin3, mchData3, xshift3,yshift3, xrms3, yrms3 \
= crossMatch.evaluateMatchResult(starOiTiPly25, tiData, mchPosPairs)
rstStr = "%s %.2f %.2f %.2f %.2f %d %d "\
"%d %d "\
"%d %d %d %.2f %.2f %.2f %.2f %.2f %d "\
"%d %d %d %.2f %.2f %.2f %.2f %.2f %d "\
"%d %d %d %.2f %.2f %.2f %.2f %.2f %d "\
"%s %s %.2f %.2f %.2f %.2f %d "\
"%d %d %d %.2f %.2f %.2f %.2f %.2f %d \n"\
%(oiFile, xshift,yshift, xrotation, yrotation, blindStarNum, totalMatchNum, \
tiData.shape[0], oiData.shape[0], \
oiPosJoin0,tiPosJoin0, mchData0, mchRatios0, xshift0,yshift0, xrms0, yrms0,runTime0,\
oiPosJoin1,tiPosJoin1, mchData1, mchRatios1, xshift1,yshift1, xrms1, yrms1,runTime1,\
oiPosJoin2,tiPosJoin2, mchData2, mchRatios2, xshift2,yshift2, xrms2, yrms2,runTime2,\
dateStr, camName, fwhmMean, fwhmRms, bkgMean, bkgRms, blindMatchTime,\
oiPosJoin3,tiPosJoin3, mchData3, mchRatios3, xshift3,yshift3, xrms3, yrms3,runTime3)
#print(rstStr)
except Exception as e:
print("blind match error")
tstr = traceback.format_exc()
print(tstr)
if len(rstStr) == 0:
rstStr = "%s %.2f %.2f %.2f %.2f %d %d "\
"%d %d "\
"%d %d %d %.2f %.2f %.2f %.2f %.2f %d "\
"%d %d %d %.2f %.2f %.2f %.2f %.2f %d "\
"%d %d %d %.2f %.2f %.2f %.2f %.2f %d "\
"%s %s %.2f %.2f %.2f %.2f %d "\
"%d %d %d %.2f %.2f %.2f %.2f %.2f %d \n"\
%(oiFile, 0,0, 0, 0, 0, 0, \
tiData.shape[0], oiData.shape[0], \
0,0, 0, 0, 0,0, 0, 0,0,\
0,0, 0, 0, 0,0, 0, 0,0,\
0,0, 0, 0, 0,0, 0, 0,0,\
dateStr, camName, fwhmMean, fwhmRms, bkgMean, bkgRms, 0,\
0,0, 0, 0, 0,0, 0, 0,0)
return rstStr
def doAll(tiPath, tiFile, oiPath, oiFile, oiImgPath, oiImgFile, savePath):
imgW=800
imgH=800
#imgW=2400
#imgH=2400
oiMatch = BlindMatch(imgW, imgH)
tiMatch = BlindMatch(imgW, imgH)
oiData = np.loadtxt("%s/%s"%(oiPath, oiFile))
tiData = np.loadtxt("%s/%s"%(tiPath, tiFile))
#print("oiData=%d"%(oiData.shape[0]))
#print("tiData=%d"%(tiData.shape[0]))
tiXY, mchIdxsTi = tiMatch.createBlindMatchFeatures(tiData)
oiXY, mchIdxsOi = oiMatch.createBlindMatchFeatures(oiData)
#print("mchIdxsTi=%d"%(len(mchIdxsTi)))
#print("mchIdxsOi=%d"%(len(mchIdxsOi)))
if len(tiXY)==0:
#print("%s create feature failure"%(tiFile))
return (-1,)
elif len(oiXY)==0:
#print("%s create feature failure"%(oiFile))
return (-1,)
else:
tarray = np.array(mchIdxsTi)
tDist = tarray[:,:,2]
tiTree = KDTree(tDist)
totalMatchNum = 0
mchList = []
for i, oIdx in enumerate(mchIdxsOi):
td = oIdx[:,2]
mchIdx = tiTree.query_ball_point(td, 30) #kdTree match
if len(mchIdx)>0:
for ii, tidx0 in enumerate(mchIdx):
tdata00 = tarray[tidx0]
dm, isMchOk = oiMatch.blindDistMatch(oIdx, tdata00, 1, 4) #blind match 8
if isMchOk:
#print("query %d KDTree match %d, precisely match %dth with %d point"%(i, len(mchIdx), ii, len(dm)))
#print(dm)
omIdx = dm[:,0]
tmIdx = dm[:,1]
oxy01 = oiXY[i]
txy02 = tiXY[tidx0]
totalMatchNum += 1
opos = omIdx[:,0:2]
tpos = tmIdx[:,0:2]
oxy1 = np.concatenate([opos,[oxy01]])
txy1 = np.concatenate([tpos,[txy02]])
mchList.append((oxy1,txy1))
'''
ox1 = omIdx[:,0]
oy1 = omIdx[:,1]
tx2 = tmIdx[:,0]
ty2 = tmIdx[:,1]
oiMatch.plotBlindMatch(oxy01[0],oxy01[1],ox1,oy1,txy02[0],txy02[1],tx2,ty2)
'''
break
if len(mchList)>1:
#print("total Match key points %d"%(totalMatchNum))
starOiTi, xshift,yshift, xrotation, yrotation, blindStarNum = tiMatch.posTransPolynomial(mchList, oiData, 2) # posTransPolynomial posTransPerspective
#print(xshift,yshift, xrotation, yrotation, blindStarNum)
mchRadius = 1
crossMatch = CrossMatch(imgW, imgH)
crossMatch.createRegionIdx(tiData)
mchPosPairs, orgPosIdxs = crossMatch.xyMatch(starOiTi, mchRadius)
oiDataMch = oiData[orgPosIdxs]
print("template match %f, observe match %f, obs %d, obsMatch %d"%(mchPosPairs.shape[0]/tiData.shape[0],mchPosPairs.shape[0]/oiData.shape[0], oiData.shape[0], mchPosPairs.shape[0]))
''' '''
oiMchPos = oiDataMch[:,0:2]
tiMchPos = mchPosPairs[:,2:4]
tiMatch.posTransPolynomial2(oiMchPos, tiMchPos, oiData, oiImgFile, oiImgPath, savePath, 3)
else:
print("blindmatch: no feature point match")