def diffImage(self, imgName, tmplParms):
starttime = datetime.now()
resultFlag = True
oImgPre = imgName.split(".")[0]
dateStr = imgName.split('_')[3][:6]
os.system("rm -rf %s/*" % (self.diff))
status = tmplParms[0]
#tmplImgName = tmplParms[1][-1][0]
tmplImgName = tmplParms[1][0][0]
tmplImgPre = tmplImgName.split(".")[0]
if status == '1':
ttmplPath = self.tmplAlignDir
else:
ttmplPath = self.tmplDiffDir
ofitPath = "%s/%s.fit" % (self.doDiffTmpl, tmplImgPre)
if not os.path.exists(ofitPath):
os.system("rm -rf %s/*" % (self.doDiffTmpl))
os.system("cp %s/%s.fit %s/%s.fit" %
(ttmplPath, tmplImgPre, self.doDiffTmpl, tmplImgPre))
os.system("cp %s/%s.cat %s/%s.cat" %
(ttmplPath, tmplImgPre, self.doDiffTmpl, tmplImgPre))
os.system("cp %s/%s_badpix.cat %s/%s_badpix.cat" %
(ttmplPath, tmplImgPre, self.doDiffTmpl, tmplImgPre))
os.system("cp %s/%s.fit %s/ti.fit" %
(self.doDiffTmpl, tmplImgPre, self.diff))
os.system("cp %s/%s.cat %s/ti.cat" %
(self.doDiffTmpl, tmplImgPre, self.diff))
os.system("cp %s/%s_badpix.cat %s/ti_badpix.cat" %
(self.doDiffTmpl, tmplImgPre, self.diff))
os.system("cp %s/%s_align.fit %s/oi.fit" %
(self.alignDir, oImgPre, self.diff))
os.system("cp %s/%s_align.cat %s/oi.cat" %
(self.alignDir, oImgPre, self.diff))
theader = fits.getheader("%s/oi.fit" % (self.diff))
dateObs = theader['DATE-OBS']
timeObs = theader['TIME-OBS']
dtStr = "%sT%s" % (dateObs, timeObs)
objTmpResi, runSuccess = self.tools.runHotpants(
'oi.fit', 'ti.fit', self.diff)
if not runSuccess:
self.log.error("diffImage failure: %s" % (imgName))
return False
fpar = 'sex_diff.par'
#sexConf=['-DETECT_MINAREA','3','-DETECT_THRESH','2.5','-ANALYSIS_THRESH','2.5']
sexConf = [
'-DETECT_MINAREA', '5', '-DETECT_THRESH', '2.5',
'-ANALYSIS_THRESH', '2.5'
]
resiCat, isSuccess = self.tools.runSextractor(objTmpResi, self.diff,
self.diff, fpar, sexConf)
if not isSuccess:
self.log.error("diffImage runSextractor failure")
return isSuccess
mchFile, nmhFile, mchPair = self.tools.runCrossMatch(
self.diff, resiCat, 'oi.cat', 1) #1 and 5
badPix2Path = "%s/%s" % (self.diff, nmhFile)
if os.path.exists(badPix2Path):
badPixProps2 = np.loadtxt(badPix2Path)
else:
badPixProps2 = np.array([])
mchRadius = 10 #15 10
mchFile, nmhFile, mchPair = self.tools.runCrossMatch(
self.diff, mchFile, 'ti.cat', mchRadius)
fotPath = "%s/%s" % (self.diff, mchFile)
if os.path.exists(fotPath):
fotProps = np.loadtxt(fotPath)
else:
fotProps = np.array([])
mchFile, nmhFile, mchPair = self.tools.runCrossMatch(
self.diff, nmhFile, 'ti_badpix.cat', 1) #1 and 5
os.system("cp %s/%s %s/%s_tot.cat" %
(self.diff, nmhFile, self.diffCatDir, oImgPre))
totPath = "%s/%s" % (self.diff, nmhFile)
if os.path.exists(totPath):
totProps = np.loadtxt(totPath)
else:
totProps = np.array([])
badPixPath = "%s/ti_badpix.cat" % (self.diff)
if os.path.exists(badPixPath):
badPixProps = np.loadtxt(badPixPath)
else:
badPixProps = np.array([])
#badPixProps = np.array([])
tstr = "orgBadPix %d, nmBad %d, match %d, noMatch %d" % (
badPixProps.shape[0], badPixProps2.shape[0], fotProps.shape[0],
totProps.shape[0])
self.log.info(tstr)
print(tstr)
#size = self.subImgSize
size = 68
if totProps.shape[0] < 500 and totProps.shape[0] > 0:
wcsPath = "%s/%s.wcs" % (ttmplPath, tmplImgPre)
wcs = WCS(wcsPath)
searchRadius = 0.05
mpQuery = QueryMinorPlanet()
mpQuery.connDb()
totSubImgs, totParms = getWindowImgs(self.diff, 'oi.fit', 'ti.fit',
objTmpResi, totProps, size)
if totParms.shape[0] > 0:
tXY = totParms[:, 0:2]
#tdates = np.repeat(dtStr,tXY.shape[0]).reshape((tXY.shape[0],1))
tRaDec = wcs.all_pix2world(tXY, 1)
totParms = np.concatenate((totParms, tRaDec), axis=1)
mchDis = []
for tpos in tRaDec:
ra = tpos[0]
dec = tpos[1]
tdis, tmag = mpQuery.matchMP(ra, dec, dateStr, dtStr,
searchRadius + 0.001)
mchDis.append([tdis, tmag])
mchDis = np.array(mchDis)
totParms = np.concatenate((totParms, mchDis), axis=1)
totSubImgs1 = totSubImgs[mchDis[:, 0] >= searchRadius]
totParms1 = totParms[mchDis[:, 0] >= searchRadius]
mpSubImgs1 = totSubImgs[mchDis[:, 0] < searchRadius]
mpParms1 = totParms[mchDis[:, 0] < searchRadius]
tstr0 = "%s has %d tot, contain %d minorplanet." % (
imgName, totParms.shape[0], mpParms1.shape[0])
print(tstr0)
self.log.info(tstr0)
if totSubImgs1.shape[0] > 0:
totpath = '%s/%s_totimg.npz' % (self.destDir, oImgPre)
np.savez_compressed(totpath,
imgs=totSubImgs1,
parms=totParms1,
obsUtc=dtStr)
resiImgs = []
for timg in totSubImgs1:
resiImgs.append(timg[2])
preViewPath = "%s/%s_tot.jpg" % (self.subImgViewDir,
oImgPre)
#if not os.path.exists(preViewPath):
psfView = genPSFView(resiImgs)
Image.fromarray(psfView).save(preViewPath)
if mpSubImgs1.shape[0] > 0:
self.sendMsg(tstr0)
totpath = '%s/%s_mpimgt.npz' % (self.destDir, oImgPre)
np.savez_compressed(totpath,
imgs=mpSubImgs1,
parms=mpParms1,
obsUtc=dtStr)
resiImgs = []
for timg in mpSubImgs1:
resiImgs.append(timg[2])
preViewPath = "%s/%s_mpt.jpg" % (self.subImgViewDir,
oImgPre)
#if not os.path.exists(preViewPath):
psfView = genPSFView(resiImgs)
Image.fromarray(psfView).save(preViewPath)
os.system(
"cp %s/%s %s/%s_resi.fit" %
(self.diff, objTmpResi, self.diffImgDir, oImgPre))
os.system("cp %s/%s %s/%s_resi.cat" %
(self.diff, resiCat, self.diffCatDir, oImgPre))
else:
alignImgName = "%s/%s_align.fit" % (self.alignDir, oImgPre)
os.system("rm -rf %s" % (alignImgName))
alignImgName = "%s/%s_align.cat" % (self.alignDir, oImgPre)
os.system("rm -rf %s" % (alignImgName))
alignImgName = "%s/%s.cat" % (self.catDir, oImgPre)
os.system("rm -rf %s" % (alignImgName))
if fotProps.shape[0] > 0 and fotProps.shape[0] < 500:
fotSubImgs, fotParms = getWindowImgs(self.diff, 'oi.fit',
'ti.fit', objTmpResi,
fotProps, size)
if fotParms.shape[0] > 0:
tXY = fotParms[:, 0:2]
#tdates = np.repeat(dtStr,tXY.shape[0]).reshape((tXY.shape[0],1))
tRaDec = wcs.all_pix2world(tXY, 1)
fotParms = np.concatenate((fotParms, tRaDec), axis=1)
if fotSubImgs.shape[0] > 0:
totpath = '%s/%s_fotimg.npz' % (self.destDir, oImgPre)
np.savez_compressed(totpath,
imgs=fotSubImgs,
parms=fotParms,
obsUtc=dtStr)
mpQuery.closeDb()
resultFlag = True
else:
tmsgStr = "%s.fit resi image has %d tot objects, maybe wrong" % (
oImgPre, totProps.shape[0])
self.log.error(tmsgStr)
#self.sendMsg(tmsgStr)
resultFlag = False
endtime = datetime.now()
runTime = (endtime - starttime).seconds
self.log.info("********** image diff total use %d seconds" % (runTime))
return resultFlag
def doClassifyAndUpload(self,
subImgPath,
totFile,
fotFile,
fullImgPath,
newImg,
tmpImg,
resImg,
origName,
serverIP,
prob=0.01,
maxNEllip=0.6,
maxMEllip=0.5,
reverse=False):
self.log.debug("start new thread classifyAndUpload %s" % (origName))
starttime = datetime.now()
self.pbb_threshold = prob
try:
nameBase = origName[:origName.index(".")]
tParms1 = self.doClassifyFile(subImgPath, totFile)
if tParms1.shape[0] > 0:
tParms1 = tParms1[tParms1[:, 6] < maxNEllip]
#tParms1 = tParms1[(tParms1[:,6]<maxMEllip) & (tParms1[:,17]>=prob)]
if tParms1.shape[0] > 0:
tflags1 = np.ones((tParms1.shape[0], 1)) #OT FLAG
tParms1 = np.concatenate((tParms1, tflags1), axis=1)
tParms2 = self.doClassifyFile(subImgPath, fotFile)
if tParms2.shape[0] > 0:
tParms2 = tParms2[(tParms2[:, 6] < maxMEllip)
& (tParms2[:, 17] >= prob)]
if tParms2.shape[0] > 0:
tflags2 = np.zeros((tParms2.shape[0], 1)) #OT FLAG
tParms2 = np.concatenate((tParms2, tflags2), axis=1)
if tParms1.shape[0] > 0 and tParms2.shape[0] > 0 and tParms2.shape[
0] < 50:
tParms = np.concatenate((tParms1, tParms2), axis=0)
elif tParms1.shape[0] > 0:
tParms = tParms1
elif tParms2.shape[0] > 0 and tParms2.shape[0] < 25:
tParms = tParms2
else:
tParms = np.array([])
if tParms.shape[0] > 0:
tSubImgs, tParms = getWindowImgs(fullImgPath, newImg, tmpImg,
resImg, tParms, 100)
if tParms.shape[0] > 0:
self.log.info(
"after classified, %s total get %d sub images" %
(origName, tSubImgs.shape[0]))
i = 1
timgNames = []
for timg in tSubImgs:
objWid, tmpWid, resiWid = timg[0], timg[1], timg[2]
objWidz = zscale_image(objWid)
tmpWidz = zscale_image(tmpWid)
resiWidz = zscale_image(resiWid)
objWidz = scipy.ndimage.zoom(objWidz, 2, order=0)
tmpWidz = scipy.ndimage.zoom(tmpWidz, 2, order=0)
resiWidz = scipy.ndimage.zoom(resiWidz, 2, order=0)
objWidz = objWidz.reshape(objWidz.shape[0],
objWidz.shape[1],
1).repeat(3, 2)
tmpWidz = tmpWidz.reshape(tmpWidz.shape[0],
tmpWidz.shape[1],
1).repeat(3, 2)
resiWidz = resiWidz.reshape(resiWidz.shape[0],
resiWidz.shape[1],
1).repeat(3, 2)
shift00 = 3
cv2.circle(objWidz,
(int(objWidz.shape[0] / 2) - shift00,
int(objWidz.shape[1] / 2) - shift00),
10, (0, 255, 0),
thickness=2)
cv2.circle(tmpWidz,
(int(tmpWidz.shape[0] / 2) - shift00,
int(tmpWidz.shape[1] / 2) - shift00),
10, (0, 255, 0),
thickness=2)
cv2.circle(resiWidz,
(int(resiWidz.shape[0] / 2) - shift00,
int(resiWidz.shape[1] / 2) - shift00),
10, (0, 255, 0),
thickness=2)
spaceLine = np.ones(
(objWidz.shape[0], 5), dtype=np.uint8) * 255
spaceLine = spaceLine.reshape(spaceLine.shape[0],
spaceLine.shape[1],
1).repeat(3, 2)
sub2Con = np.concatenate(
(objWidz, spaceLine, tmpWidz, spaceLine, resiWidz),
axis=1)
tImgName = "%s_%05d.jpg" % (nameBase, i)
timgNames.append(tImgName)
savePath = "%s/%s" % (fullImgPath, tImgName)
Image.fromarray(sub2Con).save(savePath)
i = i + 1
catName = tImgName = "%s.cat" % (nameBase)
catPath = "%s/%s" % (fullImgPath, catName)
fp0 = open(catPath, 'w')
#fp0.write(self.theader)
i = 0
for td in tParms:
tstr = "%.4f,%.4f,%.2f,%.2f,%.2f,%.3f,%.3f,%.3f,%.2f,%.2f,%d,%.4f,%.4f,%.4f,%.4f,%f,%f,%.3f,%d,%s\n"%\
(td[0],td[1],td[2],td[3],td[4],td[5],td[6],td[7],td[8],td[9],td[10],td[11],td[12],td[13],
td[14],td[15],td[16],td[17],td[18], timgNames[i])
fp0.write(tstr)
i = i + 1
fp0.close()
self.doUpload(fullImgPath, [catName], 'diffot1', serverIP)
self.doUpload(fullImgPath, timgNames, 'diffot1img',
serverIP)
if tParms.shape[0] == 0:
self.log.info("after classified, no OT candidate left")
if tParms2.shape[0] >= 50:
self.log.error(
"too more matched OT candidate, skip upload matched to db: after classified, %s total get %d matchend sub images"
% (origName, tParms2.shape[0]))
os.system("rm -rf %s" % (fullImgPath))
except Exception as e:
self.log.error('classifyAndUpload error')
self.log.error(str(e))
tstr = traceback.format_exc()
self.log.error(tstr)
endtime = datetime.now()
runTime = (endtime - starttime).seconds
self.log.info("********** classifyAndUpload %s use %d seconds" %
(origName, runTime))
def doClassifyAndUpload(self,
subImgPath,
totFile,
fotFile,
fullImgPath,
newImg,
tmpImg,
resImg,
origName,
serverIP,
runName,
skyName,
tcatParm,
prob=0.0000001,
maxNEllip=0.6,
maxMEllip=0.5,
reverse=False):
self.log.info("start new thread classifyAndUpload %s" % (origName))
print("start new thread classifyAndUpload %s" % (origName))
minFwhm = 1.5
maxFwhm = 3.0
starttime = datetime.now()
self.pbb_threshold = prob
try:
nameBase = origName[:origName.index(".")]
dateStr = nameBase.split('_')[3][:6]
camName = nameBase[:4]
cmbNum = 5
#tidx = nameBase.index('_c')+2
#cmbNum = nameBase[tidx:tidx+3] #'G021_tom_objt_190109T13531492_c005.fit'
crossTaskName = "%s_%s_%s_C%03d" % (dateStr, camName, skyName,
cmbNum)
if runName != 'p1':
crossTaskName = "%s_%s" % (crossTaskName, runName)
#self.log.info("crossTaskName %s"%(crossTaskName))
#print("crossTaskName %s"%(crossTaskName))
tParms1t = np.array([])
tParms2t = np.array([])
tParms1, obsUtc1 = self.doClassifyFile(subImgPath, totFile)
#print("doClassifyAndUpload 001")
if tParms1.shape[0] > 0:
tParms1t = tParms1[(tParms1[:, 6] < maxNEllip)
& (tParms1[:, 9] < maxFwhm) &
(tParms1[:, 9] > minFwhm)]
#tParms1t = tParms1[(tParms1[:,6]<maxMEllip) & (tParms1[:,15]>=prob)]
if tParms1t.shape[0] > 0:
tflags1t = np.ones((tParms1t.shape[0], 1)) #OT FLAG
tParms1t = np.concatenate((tParms1t, tflags1t), axis=1)
#print("doClassifyAndUpload 002")
tParms2, obsUtc2 = self.doClassifyFile(subImgPath, fotFile)
if tParms2.shape[0] > 0:
#tParms2t = tParms2[(tParms2[:,6]<maxMEllip) & (tParms2[:,15]>=prob)&(tParms2[:,9]<maxFwhm)&(tParms2[:,9]>minFwhm)]
tParms2t = tParms2[(tParms2[:, 6] < maxMEllip)
& (tParms2[:, 9] < maxFwhm) &
(tParms2[:, 9] > minFwhm)]
if tParms2t.shape[0] > 0:
tflags2t = np.zeros((tParms2t.shape[0], 1)) #OT FLAG
tParms2t = np.concatenate((tParms2t, tflags2t), axis=1)
'''
tParms3t = np.array([])
badotFile = fotFile.replace('fotimg', 'badimg2')
tParms3, obsUtc3 = self.doClassifyFile(subImgPath, badotFile)
if tParms3.shape[0]>0:
tParms3t = tParms3[(tParms3[:,6]<maxMEllip) & (tParms3[:,15]>=prob)]
if tParms3t.shape[0]>0:
tflags3t = np.zeros((tParms3t.shape[0],1)) #OT FLAG
tParms3t = np.concatenate((tParms3t, tflags3t), axis=1)
'''
print("classify result: %d tot(%d), %d fot(%d)" %
(tParms1t.shape[0], tParms1.shape[0], tParms2t.shape[0],
tParms2.shape[0]))
#print("doClassifyAndUpload 003")
if tParms1t.shape[0] > 0 and tParms1t.shape[
0] < 100 and tParms2t.shape[0] > 0 and tParms2t.shape[
0] < 100:
tParms = np.concatenate((tParms1t, tParms2t), axis=0)
elif tParms1t.shape[0] > 0 and tParms1t.shape[0] < 100:
tParms = tParms1t
elif tParms2t.shape[0] > 0 and tParms2t.shape[0] < 100:
tParms = tParms2t
else:
tParms = np.array([])
#print("doClassifyAndUpload 004")
if tParms.shape[0] == 0:
#print("doClassifyAndUpload 005")
self.log.info("after classified, no OT candidate left")
elif tParms.shape[0] > 0:
#print("doClassifyAndUpload 006")
tSubImgs, tParms = getWindowImgs(fullImgPath, newImg, tmpImg,
resImg, tParms, 100)
if tParms.shape[0] > 0:
self.log.info(
"after classified, %s total get %d sub images" %
(origName, tSubImgs.shape[0]))
#print("after classified, %s total get %d sub images"%(origName, tSubImgs.shape[0]))
i = 1
timgNames = []
for timg in tSubImgs:
objWid, tmpWid, resiWid = timg[0], timg[1], timg[2]
objWidz = zscale_image(objWid)
tmpWidz = zscale_image(tmpWid)
resiWidz = zscale_image(resiWid)
objWidz = scipy.ndimage.zoom(objWidz, 2, order=0)
tmpWidz = scipy.ndimage.zoom(tmpWidz, 2, order=0)
resiWidz = scipy.ndimage.zoom(resiWidz, 2, order=0)
objWidz = objWidz.reshape(objWidz.shape[0],
objWidz.shape[1],
1).repeat(3, 2)
tmpWidz = tmpWidz.reshape(tmpWidz.shape[0],
tmpWidz.shape[1],
1).repeat(3, 2)
resiWidz = resiWidz.reshape(resiWidz.shape[0],
resiWidz.shape[1],
1).repeat(3, 2)
shift00 = 3
cv2.circle(objWidz,
(int(objWidz.shape[0] / 2) - shift00,
int(objWidz.shape[1] / 2) - shift00),
10, (0, 255, 0),
thickness=2)
cv2.circle(tmpWidz,
(int(tmpWidz.shape[0] / 2) - shift00,
int(tmpWidz.shape[1] / 2) - shift00),
10, (0, 255, 0),
thickness=2)
cv2.circle(resiWidz,
(int(resiWidz.shape[0] / 2) - shift00,
int(resiWidz.shape[1] / 2) - shift00),
10, (0, 255, 0),
thickness=2)
spaceLine = np.ones(
(objWidz.shape[0], 5), dtype=np.uint8) * 255
spaceLine = spaceLine.reshape(spaceLine.shape[0],
spaceLine.shape[1],
1).repeat(3, 2)
sub2Con = np.concatenate(
(objWidz, spaceLine, tmpWidz, spaceLine, resiWidz),
axis=1)
tstrs = tmpImg.split(
'_') #G044_mon_objt_190128T10264248.fit
if len(tstrs) == 4:
tmpDateTime = tstrs[3]
cv2.putText(
sub2Con, #numpy array on which text is written
tmpDateTime[:tmpDateTime.index('.')], #text
(objWidz.shape[1] + 25, objWidz.shape[0] -
10), #position at which writing has to start
cv2.FONT_HERSHEY_SIMPLEX, #font family
0.5, #font size
(0, 255, 0), #font color
2)
tImgName = "%s_%05d.jpg" % (nameBase, i)
timgNames.append(tImgName)
savePath = "%s/%s" % (fullImgPath, tImgName)
Image.fromarray(sub2Con).save(savePath)
i = i + 1
catName = tImgName = "%s.cat" % (nameBase)
catPath = "%s/%s" % (fullImgPath, catName)
fp0 = open(catPath, 'w')
fp0.write(self.theader2)
t2oX = tcatParm[-2]
t2oY = tcatParm[-1]
tx = tParms[:, 0]
ty = tParms[:, 1]
ox = t2oX(tx, ty)
oy = t2oY(tx, ty)
i = 0
for td in tParms:
#print(td)
#print(td[15])
tstr = self.catFormate%\
(ox[i],oy[i],td[2],td[3],td[4],td[5],td[6],td[7],td[8],td[9],td[10],td[11],td[12],td[13],
td[14],td[15],td[16], timgNames[i], obsUtc1, td[0],td[1])
fp0.write(tstr)
i = i + 1
fp0.close()
self.doUpload(fullImgPath, [catName], 'crossOTList',
serverIP, crossTaskName)
self.doUpload(fullImgPath, timgNames, 'crossOTStamp',
serverIP, crossTaskName)
if tParms1.shape[0] >= 100 or tParms2.shape[0] >= 100:
self.log.error(
"too more unmatched or matched OT candidate, skip upload matched to db: after classified, %s total get %d matchend sub images"
% (origName, tParms2.shape[0]))
os.system("rm -rf %s" % (fullImgPath))
except Exception as e:
self.log.error('classifyAndUpload error')
self.log.error(str(e))
tstr = traceback.format_exc()
self.log.error(tstr)
endtime = datetime.now()
runTime = (endtime - starttime).seconds
self.log.info("********** classifyAndUpload %s use %d seconds" %
(origName, runTime))
def diff(self, srcDir, destDir, tmpFit, objFits, reverse=False):
try:
if not os.path.exists(destDir):
os.system("mkdir -p %s" % (destDir))
self.regImg2DB(srcDir, tmpFit)
os.system("rm -rf %s/*" % (self.templateDir))
os.system("cp %s/%s %s/%s" %
(srcDir, tmpFit, self.templateDir, self.templateImg))
self.makeTemplate()
for i, imgName in enumerate(objFits):
starttime = datetime.now()
self.log.info("diff %d: %s" % (i, imgName))
self.regImg2DB(srcDir, imgName)
os.system("rm -rf %s/*" % (self.tmpDir))
imgpre = imgName.split(".")[0]
tobjFitsFullPath = "%s/%s.fit" % (srcDir, imgpre)
if not os.path.exists(tobjFitsFullPath):
self.log.error("%s.fit not exist, stop" % (imgpre))
break
if os.path.exists("%s/diffResi/%s.fit" % (destDir, imgpre)):
self.log.info("%s.fit already diffed, skip" % (imgpre))
continue
os.system("cp %s/%s.fit %s/%s" %
(srcDir, imgpre, self.tmpDir, self.objectImg))
os.system("cp %s/%s %s/%s" %
(self.templateDir, self.templateImg, self.tmpDir,
self.templateImg))
os.system("cp %s/%s %s/%s" % (self.templateDir, self.badPixCat,
self.tmpDir, self.badPixCat))
self.objTmpResi, runSuccess = self.tools.runHotpants(
self.objectImg, self.templateImg, self.tmpDir)
if not runSuccess:
self.log.info("%s.fit diff error..." % (imgpre))
continue
if reverse:
os.system("cp %s/%s %s/diffResi/%s_r.fit" %
(self.tmpDir, self.objTmpResi, destDir, imgpre))
else:
os.system("cp %s/%s %s/diffResi/%s.fit" %
(self.tmpDir, self.objTmpResi, destDir, imgpre))
tgrid = 4
tsize = 500
tzoom = 2
timg = getThumbnail(self.tmpDir,
self.objTmpResi,
stampSize=(tsize, tsize),
grid=(tgrid, tgrid),
innerSpace=1)
timg = scipy.ndimage.zoom(timg, tzoom, order=0)
if reverse:
preViewPath = "%s/preview/%s_resi_r.jpg" % (destDir,
imgpre)
else:
preViewPath = "%s/preview/%s_resi.jpg" % (destDir, imgpre)
Image.fromarray(timg).save(preViewPath)
fpar = 'sex_diff.par'
sexConf = [
'-DETECT_MINAREA', '3', '-DETECT_THRESH', '2.5',
'-ANALYSIS_THRESH', '2.5'
]
self.objectImgCat = self.tools.runSextractor(
self.objectImg, self.tmpDir, self.tmpDir, fpar, sexConf)
resiCat = self.tools.runSextractor(self.objTmpResi,
self.tmpDir, self.tmpDir,
fpar, sexConf)
mchFile, nmhFile, mchPair = self.tools.runCrossMatch(
self.tmpDir, resiCat, self.objectImgCat, 1) #1 and 5
badPixProps2 = np.loadtxt("%s/%s" % (self.tmpDir, nmhFile))
mchFile, nmhFile, mchPair = self.tools.runCrossMatch(
self.tmpDir, mchFile, self.badPixCat, 1) #1 and 5
badPixProps = np.loadtxt("%s/%s" %
(self.tmpDir, self.badPixCat))
resiCatTrans = self.getRaDec(nmhFile)
objProps = np.loadtxt("%s/%s" % (self.tmpDir, resiCatTrans))
tstr = "%s, resi objs %d, orgBadPix %d, nmBad %d" % (
imgName, objProps.shape[0], badPixProps.shape[0],
badPixProps2.shape[0])
self.log.info(tstr)
#size = self.subImgSize
size = 68
if objProps.shape[0] < 20000 and objProps.shape[0] > 0:
totSubImgs, totParms = getWindowImgs(
self.tmpDir, self.objectImg, self.templateImg,
self.objTmpResi, objProps, size)
if totParms.shape[0] > 0:
if reverse:
fotpath = '%s/subImgs/%s_r.npz' % (destDir, imgpre)
else:
fotpath = '%s/subImgs/%s.npz' % (destDir, imgpre)
np.savez_compressed(fotpath,
imgs=totSubImgs,
parms=totParms)
self.classifyAndUpload(destDir,
imgName,
reverse=reverse)
endtime = datetime.now()
runTime = (endtime - starttime).seconds
self.log.info("diff: %s use %d seconds" % (imgName, runTime))
#break
except Exception as e:
print(str(e))
tstr = traceback.format_exc()
print(tstr)
def diffImage(self):
starttime = datetime.now()
resultFlag = True
oImgPre = self.origObjectImg[:self.origObjectImg.index(".")]
os.system("cp %s/%s %s/%s" % (self.templateDir, self.templateImg,
self.tmpDir, self.templateImg))
os.system(
"cp %s/%s %s/%s" %
(self.templateDir, self.badPixCat, self.tmpDir, self.badPixCat))
os.system("cp %s/%s %s/%s" % (self.templateDir, self.templateImgCat,
self.tmpDir, self.templateImgCat))
#self.newImageName = self.tools.imageAlign(self.tmpDir, self.objectImg, self.transHG)
self.objTmpResi, runSuccess = self.tools.runHotpants(
self.newImageName, self.templateImg, self.tmpDir)
if not runSuccess:
return False
os.system("cp %s/%s %s/%s.fit" %
(self.tmpDir, self.objTmpResi, self.resiFitsDir, oImgPre))
tgrid = 1
tsize = 4096
tzoom = 1
timg = getThumbnail(self.tmpDir,
self.objTmpResi,
stampSize=(tsize, tsize),
grid=(tgrid, tgrid),
innerSpace=1)
#timg = scipy.ndimage.zoom(timg, tzoom, order=0)
preViewPath = "%s/%s_resi.jpg" % (self.origPreViewDir, oImgPre)
Image.fromarray(timg).save(preViewPath)
'''
return
'''
fpar = 'sex_diff.par'
sexConf = [
'-DETECT_MINAREA', '3', '-DETECT_THRESH', '2.5',
'-ANALYSIS_THRESH', '2.5'
]
resiCat = self.tools.runSextractor(self.objTmpResi, self.tmpDir,
self.tmpDir, fpar, sexConf)
mchFile, nmhFile, mchPair = self.tools.runCrossMatch(
self.tmpDir, resiCat, self.objectImgCatTrans, 1) #1 and 5
badPixProps2 = np.loadtxt("%s/%s" % (self.tmpDir, nmhFile))
tdata1 = np.loadtxt("%s/%s" % (self.tmpDir, mchFile))
tdata2 = np.loadtxt("%s/%s" % (self.tmpDir, self.objectImgCatTrans))
tIdx1 = np.loadtxt("%s/%s" % (self.tmpDir, mchPair)).astype(np.int)
tIdx1 = tIdx1 - 1
origData = tdata2[tIdx1[:, 1]]
if origData.shape[0] == tdata1.shape[0]:
outCatName = "%s_orgpos.cat" % (mchFile[:mchFile.index(".")])
outCatPath = "%s/%s" % (self.tmpDir, outCatName)
tstr = ""
i = 0
for td in tdata1:
tstr += "%.4f %.4f %.2f %.2f %.2f %.3f %.3f %.3f %.2f %.2f %d %.4f %.4f %.4f %.4f\n"%\
(td[0],td[1],td[2],td[3],td[4],td[5],td[6],td[7],td[8],td[9],td[10],origData[i][11], origData[i][12], origData[i][13], origData[i][14])
i = i + 1
fp0 = open(outCatPath, 'w')
fp0.write(tstr)
fp0.close()
mchFile = outCatName
else:
self.log.error("add orig pos error")
'''
self.tools.runSelfMatch(self.tmpDir, resiCat, 1) #debug: get ds9 reg file
tdata = np.loadtxt("%s/%s"%(self.tmpDir, resiCat))
self.log.info("resi image star %d"%(tdata.shape[0]))
'''
''' '''
mchRadius = 15 #15 10
mchFile, nmhFile, mchPair = self.tools.runCrossMatch(
self.tmpDir, mchFile, self.templateImgCat, mchRadius)
fotProps = np.loadtxt("%s/%s" % (self.tmpDir, mchFile))
mchFile, nmhFile, mchPair = self.tools.runCrossMatch(
self.tmpDir, nmhFile, self.badPixCat, 1) #1 and 5
os.system("cp %s/%s %s/%s" %
(self.tmpDir, nmhFile, self.resiCatDir, "%s.cat" %
(oImgPre)))
totProps = np.loadtxt("%s/%s" % (self.tmpDir, nmhFile))
#badPixProps = np.loadtxt("%s/%s"%(self.tmpDir, self.badPixCat))
badPixProps = np.array([])
tstr = "orgBadPix %d, nmBad %d, match %d, noMatch %d" % (
badPixProps.shape[0], badPixProps2.shape[0], fotProps.shape[0],
totProps.shape[0])
self.log.info(tstr)
#size = self.subImgSize
size = 68
if totProps.shape[0] < 500 and totProps.shape[0] > 0:
totSubImgs, totParms = getWindowImgs(self.tmpDir,
self.newImageName,
self.templateImg,
self.objTmpResi, totProps,
size)
if totParms.shape[0] > 0:
tXY = totParms[:, 0:2]
tRaDec = self.wcs.all_pix2world(tXY, 1)
totParms = np.concatenate((totParms, tRaDec), axis=1)
fotpath = '%s/%s_totimg.npz' % (self.destDir, oImgPre)
np.savez_compressed(fotpath, imgs=totSubImgs, parms=totParms)
resiImgs = []
for timg in totSubImgs:
resiImgs.append(timg[2])
preViewPath = "%s/%s_tot.jpg" % (self.preViewDir, oImgPre)
#if not os.path.exists(preViewPath):
psfView = genPSFView(resiImgs)
Image.fromarray(psfView).save(preViewPath)
if fotProps.shape[0] > 0 and fotProps.shape[0] < 2000:
fotSubImgs, fotParms = getWindowImgs(self.tmpDir,
self.newImageName,
self.templateImg,
self.objTmpResi, fotProps,
size)
if fotParms.shape[0] > 0:
tXY = fotParms[:, 0:2]
tRaDec = self.wcs.all_pix2world(tXY, 1)
fotParms = np.concatenate((fotParms, tRaDec), axis=1)
fotpath = '%s/%s_fotimg.npz' % (self.destDir, oImgPre)
np.savez_compressed(fotpath,
imgs=fotSubImgs,
parms=fotParms)
'''
if badPixProps.shape[0]>0:
badSubImgs, badParms = getWindowImgs(self.tmpDir, self.newImageName, self.templateImg, self.objTmpResi, badPixProps, size)
if badParms.shape[0]>0:
fotpath = '%s/%s_badimg.npz'%(self.destDir, oImgPre)
np.savez_compressed(fotpath, imgs=badSubImgs, parms=badParms)
if badPixProps2.shape[0]>0:
badSubImgs, badParms = getWindowImgs(self.tmpDir, self.newImageName, self.templateImg, self.objTmpResi, badPixProps2, size)
if badParms.shape[0]>0:
fotpath = '%s/%s_badimg2.npz'%(self.destDir, oImgPre)
np.savez_compressed(fotpath, imgs=badSubImgs, parms=badParms)
'''
resultFlag = True
else:
tmsgStr = "%s.fit resi image has %d tot objects, maybe wrong" % (
oImgPre, totProps.shape[0])
self.log.error(tmsgStr)
#self.sendMsg(tmsgStr)
resultFlag = False
'''
tgrid = 4
tsize = 500
tzoom = 1
timg = getThumbnail(self.tmpDir, self.objTmpResi, stampSize=(tsize,tsize), grid=(tgrid, tgrid), innerSpace = 1)
#timg = scipy.ndimage.zoom(timg, tzoom, order=0)
preViewPath = "%s/%s_resi.jpg"%(self.origPreViewDir, oImgPre)
Image.fromarray(timg).save(preViewPath)
'''
'''
timg = getThumbnail(self.tmpDir, self.newImageName, stampSize=(tsize,tsize), grid=(tgrid, tgrid), innerSpace = 1)
timg = scipy.ndimage.zoom(timg, tzoom, order=0)
preViewPath = "%s/%s_obj.jpg"%(self.origPreViewDir, oImgPre)
Image.fromarray(timg).save(preViewPath)
timg = getThumbnail(self.tmpDir, self.templateImg, stampSize=(tsize,tsize), grid=(tgrid, tgrid), innerSpace = 1)
timg = scipy.ndimage.zoom(timg, tzoom, order=0)
preViewPath = "%s/%s_tmp.jpg"%(self.origPreViewDir, oImgPre)
Image.fromarray(timg).save(preViewPath)
'''
endtime = datetime.now()
runTime = (endtime - starttime).seconds
self.log.info("********** image diff total use %d seconds" % (runTime))
return resultFlag
def diffImage(self, imgName, tmplParms):
starttime = datetime.now()
resultFlag = True
oImgPre = imgName.split(".")[0]
os.system("rm -rf %s/*" % (self.diff))
status = tmplParms[0]
#tmplImgName = tmplParms[1][-1][0]
tmplImgName = tmplParms[1][0][0]
tmplImgPre = tmplImgName.split(".")[0]
if status == '1':
ttmplPath = self.tmplAlignDir
else:
ttmplPath = self.tmplDiffDir
ofitPath = "%s/%s.fit" % (self.doDiffTmpl, tmplImgPre)
if not os.path.exists(ofitPath):
os.system("rm -rf %s/*" % (self.doDiffTmpl))
os.system("cp %s/%s.fit %s/%s.fit" %
(ttmplPath, tmplImgPre, self.doDiffTmpl, tmplImgPre))
os.system("cp %s/%s.cat %s/%s.cat" %
(ttmplPath, tmplImgPre, self.doDiffTmpl, tmplImgPre))
os.system("cp %s/%s_badpix.cat %s/%s_badpix.cat" %
(ttmplPath, tmplImgPre, self.doDiffTmpl, tmplImgPre))
os.system("cp %s/%s.fit %s/ti.fit" %
(self.doDiffTmpl, tmplImgPre, self.diff))
os.system("cp %s/%s.cat %s/ti.cat" %
(self.doDiffTmpl, tmplImgPre, self.diff))
os.system("cp %s/%s_badpix.cat %s/ti_badpix.cat" %
(self.doDiffTmpl, tmplImgPre, self.diff))
os.system("cp %s/%s.fit %s/oi.fit" % (self.cmbDir, oImgPre, self.diff))
os.system("cp %s/%s.cat %s/oi.cat" %
(self.cmbCatDir, oImgPre, self.diff))
theader = fits.getheader("%s/oi.fit" % (self.diff))
dateObs = theader['DATE-OBS']
timeObs = theader['TIME-OBS']
dtStr = "%sT%s" % (dateObs, timeObs)
objTmpResi, runSuccess = self.tools.runHotpants(
'oi.fit', 'ti.fit', self.diff)
if not runSuccess:
self.log.error("diffImage failure: %s" % (imgName))
return False
fpar = 'sex_diff.par'
#sexConf=['-DETECT_MINAREA','3','-DETECT_THRESH','2.5','-ANALYSIS_THRESH','2.5']
sexConf = [
'-DETECT_MINAREA', '5', '-DETECT_THRESH', '2.5',
'-ANALYSIS_THRESH', '2.5'
]
resiCat, isSuccess = self.tools.runSextractor(objTmpResi, self.diff,
self.diff, fpar, sexConf)
if not isSuccess:
self.log.error("diffImage runSextractor failure")
return isSuccess
os.system("cp %s/%s %s/%s_resi.fit" %
(self.diff, objTmpResi, self.diffImgDir, oImgPre))
os.system("cp %s/%s %s/%s_resi.cat" %
(self.diff, resiCat, self.diffCatDir, oImgPre))
mchFile, nmhFile, mchPair = self.tools.runCrossMatch(
self.diff, resiCat, 'oi.cat', 1) #1 and 5
badPix2Path = "%s/%s" % (self.diff, nmhFile)
if os.path.exists(badPix2Path):
badPixProps2 = np.loadtxt(badPix2Path)
else:
badPixProps2 = np.array([])
mchRadius = 15 #15 10
mchFile, nmhFile, mchPair = self.tools.runCrossMatch(
self.diff, mchFile, 'ti.cat', mchRadius)
fotPath = "%s/%s" % (self.diff, mchFile)
if os.path.exists(fotPath):
fotProps = np.loadtxt(fotPath)
else:
fotProps = np.array([])
mchFile, nmhFile, mchPair = self.tools.runCrossMatch(
self.diff, nmhFile, 'ti_badpix.cat', 1) #1 and 5
os.system("cp %s/%s %s/%s_tot.cat" %
(self.diff, nmhFile, self.diffCatDir, oImgPre))
totPath = "%s/%s" % (self.diff, nmhFile)
if os.path.exists(totPath):
totProps = np.loadtxt(totPath)
else:
totProps = np.array([])
badPixPath = "%s/ti_badpix.cat" % (self.diff)
if os.path.exists(badPixPath):
badPixProps = np.loadtxt(badPixPath)
else:
badPixProps = np.array([])
#badPixProps = np.array([])
tstr = "orgBadPix %d, nmBad %d, match %d, noMatch %d" % (
badPixProps.shape[0], badPixProps2.shape[0], fotProps.shape[0],
totProps.shape[0])
self.log.info(tstr)
print(tstr)
#size = self.subImgSize
size = 68
if totProps.shape[0] < 500 and totProps.shape[0] > 0:
wcsPath = "%s/%s.wcs" % (ttmplPath, tmplImgPre)
wcs = WCS(wcsPath)
totSubImgs, totParms = getWindowImgs(self.diff, 'oi.fit', 'ti.fit',
objTmpResi, totProps, size)
if totParms.shape[0] > 0:
tXY = totParms[:, 0:2]
#tdates = np.repeat(dtStr,tXY.shape[0]).reshape((tXY.shape[0],1))
tRaDec = wcs.all_pix2world(tXY, 1)
totParms = np.concatenate((totParms, tRaDec), axis=1)
fotpath = '%s/%s_totimg.npz' % (self.destDir, oImgPre)
np.savez_compressed(fotpath,
imgs=totSubImgs,
parms=totParms,
obsUtc=dtStr)
resiImgs = []
for timg in totSubImgs:
resiImgs.append(timg[2])
preViewPath = "%s/%s_tot.jpg" % (self.subImgViewDir, oImgPre)
#if not os.path.exists(preViewPath):
psfView = genPSFView(resiImgs)
Image.fromarray(psfView).save(preViewPath)
if fotProps.shape[0] > 0 and fotProps.shape[0] < 3000:
fotSubImgs, fotParms = getWindowImgs(self.diff, 'oi.fit',
'ti.fit', objTmpResi,
fotProps, size)
if fotParms.shape[0] > 0:
tXY = fotParms[:, 0:2]
#tdates = np.repeat(dtStr,tXY.shape[0]).reshape((tXY.shape[0],1))
tRaDec = wcs.all_pix2world(tXY, 1)
fotParms = np.concatenate((fotParms, tRaDec), axis=1)
fotpath = '%s/%s_fotimg.npz' % (self.destDir, oImgPre)
np.savez_compressed(fotpath,
imgs=fotSubImgs,
parms=fotParms,
obsUtc=dtStr)
'''
if badPixProps.shape[0]>0:
badSubImgs, badParms = getWindowImgs(self.diff, 'oi.fit', 'ti.fit', objTmpResi, badPixProps, size)
if badParms.shape[0]>0:
fotpath = '%s/%s_badimg.npz'%(self.destDir, oImgPre)
np.savez_compressed(fotpath, imgs=badSubImgs, parms=badParms)
if badPixProps2.shape[0]>0:
badSubImgs, badParms = getWindowImgs(self.diff, 'oi.fit', 'ti.fit', objTmpResi, badPixProps2, size)
if badParms.shape[0]>0:
tXY = badParms[:,0:2]
tRaDec = wcs.all_pix2world(tXY, 1)
badParms = np.concatenate((badParms, tRaDec), axis=1)
fotpath = '%s/%s_badimg2.npz'%(self.destDir, oImgPre)
np.savez_compressed(fotpath, imgs=badSubImgs, parms=badParms, obsUtc=dtStr)
'''
resultFlag = True
else:
tmsgStr = "%s.fit resi image has %d tot objects, maybe wrong" % (
oImgPre, totProps.shape[0])
self.log.error(tmsgStr)
#self.sendMsg(tmsgStr)
resultFlag = False
''' '''
tgrid = 4
tsize = 500
tzoom = 1
timg = getThumbnail(self.diff,
objTmpResi,
stampSize=(tsize, tsize),
grid=(tgrid, tgrid),
innerSpace=1)
timg = scipy.ndimage.zoom(timg, tzoom, order=0)
preViewPath = "%s/%s_resi.jpg" % (self.origPreViewDir, oImgPre)
Image.fromarray(timg).save(preViewPath)
'''
'''
timg = getThumbnail(self.diff,
'oi.fit',
stampSize=(tsize, tsize),
grid=(tgrid, tgrid),
innerSpace=1)
timg = scipy.ndimage.zoom(timg, tzoom, order=0)
preViewPath = "%s/%s_obj.jpg" % (self.origPreViewDir, oImgPre)
Image.fromarray(timg).save(preViewPath)
timg = getThumbnail(self.diff,
'ti.fit',
stampSize=(tsize, tsize),
grid=(tgrid, tgrid),
innerSpace=1)
timg = scipy.ndimage.zoom(timg, tzoom, order=0)
preViewPath = "%s/%s_tmp.jpg" % (self.origPreViewDir, oImgPre)
Image.fromarray(timg).save(preViewPath)
endtime = datetime.now()
runTime = (endtime - starttime).seconds
self.log.info("********** image diff total use %d seconds" % (runTime))
return resultFlag
def diffImage(self):
starttime = datetime.now()
resultFlag = True
oImgPre = self.origObjectImg[:self.origObjectImg.index(".")]
os.system("cp %s/%s %s/%s" % (self.templateDir, self.templateImg,
self.tmpDir, self.templateImg))
os.system(
"cp %s/%s %s/%s" %
(self.templateDir, self.badPixCat, self.tmpDir, self.badPixCat))
os.system("cp %s/%s %s/%s" % (self.templateDir, self.templateImgCat,
self.tmpDir, self.templateImgCat))
#self.newImageName = self.tools.imageAlign(self.tmpDir, self.objectImg, self.transHG)
self.objTmpResi = self.tools.runHotpants(self.newImageName,
self.templateImg, self.tmpDir)
fpar = 'sex_diff.par'
sexConf = [
'-DETECT_MINAREA', '3', '-DETECT_THRESH', '2.5',
'-ANALYSIS_THRESH', '2.5'
]
resiCat = self.tools.runSextractor(self.objTmpResi, self.tmpDir,
self.tmpDir, fpar, sexConf)
'''
self.tools.runSelfMatch(self.tmpDir, resiCat, 1) #debug: get ds9 reg file
tdata = np.loadtxt("%s/%s"%(self.tmpDir, resiCat))
self.log.info("resi image star %d"%(tdata.shape[0]))
'''
''' '''
mchRadius = 15 #15 10
mchFile, nmhFile, mchPair = self.tools.runCrossMatch(
self.tmpDir, resiCat, self.templateImgCat, mchRadius)
fotProps = np.loadtxt("%s/%s" % (self.tmpDir, mchFile))
mchFile, nmhFile, mchPair = self.tools.runCrossMatch(
self.tmpDir, nmhFile, self.badPixCat, 1) #1 and 5
os.system("cp %s/%s %s/%s" %
(self.tmpDir, nmhFile, self.resiCatDir, "%s.cat" %
(oImgPre)))
totProps = np.loadtxt("%s/%s" % (self.tmpDir, nmhFile))
#badPixProps = np.loadtxt("%s/%s"%(self.tmpDir, mchFile))
badPixProps = np.loadtxt("%s/%s" % (self.tmpDir, self.badPixCat))
tstr = "badPix %d, match %d, noMatch %d" % (
badPixProps.shape[0], fotProps.shape[0], totProps.shape[0])
self.log.info(tstr)
size = self.subImgSize
if totProps.shape[0] < 500 and totProps.shape[0] > 0:
totSubImgs, totParms = getWindowImgs(self.tmpDir,
self.newImageName,
self.templateImg,
self.objTmpResi, totProps,
size)
tXY = totParms[:, 0:2]
tRaDec = self.wcs.all_pix2world(tXY, 1)
totParms = np.concatenate((totParms, tRaDec), axis=1)
fotpath = '%s/%s_totimg.npz' % (self.destDir, oImgPre)
np.savez_compressed(fotpath, imgs=totSubImgs, parms=totParms)
resiImgs = []
for timg in totSubImgs:
resiImgs.append(timg[2])
preViewPath = "%s/%s_tot.jpg" % (self.preViewDir, oImgPre)
#if not os.path.exists(preViewPath):
psfView = genPSFView(resiImgs)
Image.fromarray(psfView).save(preViewPath)
if fotProps.shape[0] > 0 and fotProps.shape[0] < 2000:
fotSubImgs, fotParms = getWindowImgs(self.tmpDir,
self.newImageName,
self.templateImg,
self.objTmpResi, fotProps,
size)
tXY = fotParms[:, 0:2]
tRaDec = self.wcs.all_pix2world(tXY, 1)
fotParms = np.concatenate((fotParms, tRaDec), axis=1)
fotpath = '%s/%s_fotimg.npz' % (self.destDir, oImgPre)
np.savez_compressed(fotpath, imgs=fotSubImgs, parms=fotParms)
if badPixProps.shape[0] > 0:
badSubImgs, badParms = getWindowImgs(self.tmpDir,
self.newImageName,
self.templateImg,
self.objTmpResi,
badPixProps, size)
fotpath = '%s/%s_badimg.npz' % (self.destDir, oImgPre)
np.savez_compressed(fotpath, imgs=badSubImgs, parms=badParms)
resultFlag = True
else:
tmsgStr = "%s.fit resi image has %d tot objects, maybe wrong" % (
oImgPre, totProps.shape[0])
self.log.error(tmsgStr)
self.tools.sendTriggerMsg(tmsgStr)
resultFlag = False
tgrid = 4
tsize = 500
tzoom = 1
timg = getThumbnail(self.tmpDir,
self.objTmpResi,
stampSize=(tsize, tsize),
grid=(tgrid, tgrid),
innerSpace=1)
#timg = scipy.ndimage.zoom(timg, tzoom, order=0)
preViewPath = "%s/%s_resi.jpg" % (self.origPreViewDir, oImgPre)
Image.fromarray(timg).save(preViewPath)
'''
timg = getThumbnail(self.tmpDir, self.newImageName, stampSize=(tsize,tsize), grid=(tgrid, tgrid), innerSpace = 1)
timg = scipy.ndimage.zoom(timg, tzoom, order=0)
preViewPath = "%s/%s_obj.jpg"%(self.origPreViewDir, oImgPre)
Image.fromarray(timg).save(preViewPath)
timg = getThumbnail(self.tmpDir, self.templateImg, stampSize=(tsize,tsize), grid=(tgrid, tgrid), innerSpace = 1)
timg = scipy.ndimage.zoom(timg, tzoom, order=0)
preViewPath = "%s/%s_tmp.jpg"%(self.origPreViewDir, oImgPre)
Image.fromarray(timg).save(preViewPath)
'''
endtime = datetime.now()
runTime = (endtime - starttime).seconds
self.log.info("********** image diff total use %d seconds" % (runTime))
return resultFlag
