def matchAllImagesFlann(c,conn):
c.execute('SELECT * FROM images')
images =c.fetchall()
#print images
numimg = 0
for image1 in images:
if numimg%50==0:
print numimg
imageId1 = image1[0]
imageURL1 = image1[1]
subNumImg = 0
print imageId1
for image2 in images:
if subNumImg%50==0:
print str(image1) +':' + str(subNumImg)
imageId2 = image2[0]
imageURL2 = image1[1]
#print dirm.rootDirectory + imageURL
try:
kp1, des1 = surfHandlerP.reteriveSurfVals(imageId1,c)
kp2, des2 = surfHandlerP.reteriveSurfVals(imageId2,c)
matches,numMatches, meanDistance, matchesAT,numMatchesAT, meanDistanceAT = surf.flannMatcher(kp1, des1, kp2, des2)
store(imageId1, imageId2, matches, numMatches, meanDistance, matchesAT,numMatchesAT, meanDistanceAT,c,conn)
except Exception, e:
print "unable to process image "+imageId1 + ", " + imageId2
print str(e)
subNumImg = subNumImg + 1
numimg = numimg +1
def bow(c, con):
# create BFMatcher object
bf = cv2.BFMatcher(cv2.NORM_L2, crossCheck=True)
c.execute('SELECT * FROM images')
images = c.fetchall()
images = images[:5]
#print images
numimg = 0
for image1 in images:
if numimg % 50 == 0:
print 'processed so far:' + str(numimg)
imageId1 = image1[0]
imageURL1 = image1[1]
kp1, des1 = surfHandlerP.reteriveSurfVals(imageId1, c)
bf.add(des1)
numimg = numimg + 1
bf.train()
print len(bf.getTrainDescriptors())
imageId2 = images[3][0]
kp2, des2 = surfHandlerP.reteriveSurfVals(imageId2, c)
print len(des2)
matches = bf.match(des2)
print len(matches)
print matches[16]
match = matches[1650]
print match.distance, match.trainIdx, match.queryIdx, match.imgIdx
matchesA = [0, 0, 0, 0, 0, 0, 0]
def bowKn(c,con):
# FLANN parameters
FLANN_INDEX_KDTREE = 0
index_params = dict(algorithm = FLANN_INDEX_KDTREE, trees = 5)
search_params = dict(checks=50) # or pass empty dictionary
flann = cv2.FlannBasedMatcher(index_params,search_params)
c.execute('SELECT * FROM images')
images =c.fetchall()
images = images[:5]
#print images
numimg = 0
for image1 in images:
if numimg%50==0:
print 'processed so far:' + str(numimg)
imageId1 = image1[0]
imageURL1 = image1[1]
kp1, des1 = surfHandlerP.reteriveSurfVals(imageId1,c)
flann.add([des1])
numimg = numimg + 1
flann.train()
print len(flann.getTrainDescriptors())
imageId2 = images[3][0]
kp2, des2 = surfHandlerP.reteriveSurfVals(imageId2,c)
print len(des2)
matches = flann.knnMatch(des2,k=2)
print len(matches)
print matches[16]
match = matches[1650]
print match.distance, match.trainIdx, match.queryIdx, match.imgIdx
matchesA = [0,0,0,0,0,0,0]
def bowKn(c, con):
# FLANN parameters
FLANN_INDEX_KDTREE = 0
index_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=5)
search_params = dict(checks=50) # or pass empty dictionary
flann = cv2.FlannBasedMatcher(index_params, search_params)
c.execute('SELECT * FROM images')
images = c.fetchall()
images = images[:5]
#print images
numimg = 0
for image1 in images:
if numimg % 50 == 0:
print 'processed so far:' + str(numimg)
imageId1 = image1[0]
imageURL1 = image1[1]
kp1, des1 = surfHandlerP.reteriveSurfVals(imageId1, c)
flann.add([des1])
numimg = numimg + 1
flann.train()
print len(flann.getTrainDescriptors())
imageId2 = images[3][0]
kp2, des2 = surfHandlerP.reteriveSurfVals(imageId2, c)
print len(des2)
matches = flann.knnMatch(des2, k=2)
print len(matches)
print matches[16]
match = matches[1650]
print match.distance, match.trainIdx, match.queryIdx, match.imgIdx
matchesA = [0, 0, 0, 0, 0, 0, 0]
def bow(c,con):
# create BFMatcher object
bf = cv2.BFMatcher(cv2.NORM_L2, crossCheck=True)
c.execute('SELECT * FROM images')
images =c.fetchall()
images = images[:5]
#print images
numimg = 0
for image1 in images:
if numimg%50==0:
print 'processed so far:' + str(numimg)
imageId1 = image1[0]
imageURL1 = image1[1]
kp1, des1 = surfHandlerP.reteriveSurfVals(imageId1,c)
bf.add(des1)
numimg = numimg + 1
bf.train()
print len(bf.getTrainDescriptors())
imageId2 = images[3][0]
kp2, des2 = surfHandlerP.reteriveSurfVals(imageId2,c)
print len(des2)
matches = bf.match(des2)
print len(matches)
print matches[16]
match = matches[1650]
print match.distance, match.trainIdx, match.queryIdx, match.imgIdx
matchesA = [0,0,0,0,0,0,0]
def matchAllImages(c, conn):
c.execute('SELECT * FROM images')
images = c.fetchall()
#print images
numimg = 0
for image1 in images:
if numimg % 50 == 0:
print numimg
imageId1 = image1[0]
imageURL1 = image1[1]
subNumImg = 0
print imageId1
for image2 in images:
if subNumImg % 50 == 0:
print str(image1) + ':' + str(subNumImg)
imageId2 = image2[0]
imageURL2 = image1[1]
#print dirm.rootDirectory + imageURL
try:
kp1, des1 = surfHandlerP.reteriveSurfVals(imageId1, c)
kp2, des2 = surfHandlerP.reteriveSurfVals(imageId2, c)
matches, numMatches, meanDistance, matchesAT, numMatchesAT, meanDistanceAT = surf.bfMatch(
kp1, des1, kp2, des2)
store(imageId1, imageId2, matches, numMatches, meanDistance,
matchesAT, numMatchesAT, meanDistanceAT, c, conn)
except Exception, e:
print "unable to process image " + imageId1 + ", " + imageId2
print str(e)
subNumImg = subNumImg + 1
numimg = numimg + 1
