def matching_correction(self, image, image2):
'''
Computes keypoints for two images and try to align image2 on image1
'''
#computing keypoints matching
s = sift.SiftPlan(template=image, devicetype="gpu")
kp1 = s.keypoints(image)
kp2 = s.keypoints(image2) #image2 and image must have the same size
m = sift.MatchPlan(devicetype="GPU")
matching = m.match(kp2, kp1)
N = matching.shape[0]
#solving normals equations for least square fit
X = numpy.zeros((2 * N, 6))
X[::2, 2:] = 1, 0, 0, 0
X[::2, 0] = matching.x[:, 0]
X[::2, 1] = matching.y[:, 0]
X[1::2, 0:3] = 0, 0, 0
X[1::2, 3] = matching.x[:, 0]
X[1::2, 4] = matching.y[:, 0]
X[1::2, 5] = 1
y = numpy.zeros((2 * N, 1))
y[::2, 0] = matching.x[:, 1]
y[1::2, 0] = matching.y[:, 1]
#A = numpy.dot(X.transpose(),X)
#sol = numpy.dot(numpy.linalg.inv(A),numpy.dot(X.transpose(),y))
sol = numpy.dot(numpy.linalg.pinv(X), y)
MSE = numpy.linalg.norm(y - numpy.dot(
X, sol))**2 / N #value of the sum of residuals at "sol"
return sol, MSE
def __init__(self, fname, devicetype=None, device=None, context=None):
self.image_rgb = scipy.misc.imread(fname)
self.image_bw = 0.299 * self.image_rgb[:, :,
0] + 0.587 * self.image_rgb[:, :,
1] + 0.114 * self.image_rgb[:, :,
2]
if feature:
self._sift_cpp = feature.SiftAlignment()
self._sift_ocl = sift.SiftPlan(template=self.image_rgb,
device=device,
devicetype=devicetype,
context=context)
self.kp_cpp = numpy.empty(0)
self.kp_ocl = numpy.empty(0)
if SHOW_FIGURES == True:
self.fig = pylab.figure()
self.sp1 = self.fig.add_subplot(1, 2, 1)
self.im1 = self.sp1.imshow(self.image_rgb)
self.sp1.set_title("OpenCL: %s keypoint" % self.kp_ocl.size)
self.sp2 = self.fig.add_subplot(1, 2, 2)
self.im2 = self.sp2.imshow(self.image_bw, cmap="gray")
self.sp2.set_title("C++: %s keypoint" % self.kp_cpp.size)
self.fig.show()
self.timing_cpp = None
self.timing_ocl = None
self.speedups = numpy.zeros((1, 3), dtype=numpy.float32)
def __init__(self, filename=None, devicetype=None, device=None, context=None, profile=False):
if filename and os.path.exists(filename):
self.filename = filename
else:
self.filename = utilstest.UtilsTest.getimage("wikipedia/commons/9/94/Esrf_grenoble.jpg")
try:
self.image_rgb = scipy.misc.imread(self.filename)
except:
import fabio
self.image_rgb = fabio.open(self.filename).data
if self.image_rgb.ndim != 2:
self.image_bw = 0.299 * self.image_rgb[:, :, 0] + 0.587 * self.image_rgb[:, :, 1] + 0.114 * self.image_rgb[:, :, 2]
else: self.image_bw = self.image_rgb
if feature:
self._sift_cpp = feature.SiftAlignment()
self._sift_ocl = sift.SiftPlan(template=self.image_rgb, device=device, devicetype=devicetype, context=context, profile=profile)
self.ctx = self._sift_ocl.ctx
self.kp_cpp = numpy.empty(0)
self.kp_ocl = numpy.empty(0)
self.fig = pylab.figure()
self.sp1 = self.fig.add_subplot(1, 2, 1)
self.im1 = self.sp1.imshow(self.image_rgb)
self.sp1.set_title("OpenCL: %s keypoint" % self.kp_ocl.size)
self.sp2 = self.fig.add_subplot(1, 2, 2)
self.im2 = self.sp2.imshow(self.image_bw, cmap="gray")
self.sp2.set_title("C++: %s keypoint" % self.kp_cpp.size)
self.fig.show()
self.timing_cpp = None
self.timing_ocl = None
def __init__(self,
filename=None,
devicetype=None,
device=None,
profile=False):
if filename and os.path.exists(filename):
self.filename = filename
else:
self.filename = "Esrf_grenoble.jpg"
data = urllib2.urlopen(
"http://upload.wikimedia.org/wikipedia/commons/9/94/Esrf_grenoble.jpg"
).read()
open(self.filename, "wb").write(data)
self.image_rgb = scipy.misc.imread(self.filename)
if self.image_rgb.ndim != 2:
self.image_bw = 0.299 * self.image_rgb[:, :,
0] + 0.587 * self.image_rgb[:, :,
1] + 0.114 * self.image_rgb[:, :,
2]
else:
self.image_bw = self.image_rgb
if feature:
self._sift_cpp = feature.SiftAlignment()
self._sift_ocl = sift.SiftPlan(template=self.image_rgb,
device=device,
devicetype=devicetype,
profile=profile)
self.kp_cpp = numpy.empty(0)
self.kp_ocl = numpy.empty(0)
self.fig = pylab.figure()
self.sp1 = self.fig.add_subplot(1, 2, 1)
self.sp2 = self.fig.add_subplot(1, 2, 2)
#elf.sp3 = self.fig.add_subplot(1, 2, 3)
#elf.sp4 = self.fig.add_subplot(1, 2, 4)
self.im1 = self.sp1.imshow(self.image_rgb)
self.sp1.set_title("OpenCL: %s keypoint" % self.kp_ocl.size)
self.im2 = self.sp2.imshow(self.image_bw, cmap="gray")
self.sp2.set_title("C++: %s keypoint" % self.kp_cpp.size)
self.fig.show()
self.timing_cpp = None
self.timing_ocl = None
img2 = fabio.open(sys.argv[2]).data
except:
logger.error("Unable to read input images")
else:
img1 = scipy.misc.lena()
img2 = scipy.ndimage.rotate(img1, 10, reshape=False)
'''
img1 = scipy.misc.imread("../test_images/fruit_bowl.png")
tmp = scipy.misc.imread("../test_images/banana.png")
img2 = numpy.zeros_like(img1)
img2 = img2 + 255
d0 = (img1.shape[0] - tmp.shape[0])/2
d1 = (img1.shape[1] - tmp.shape[1])/2
img2[d0:-d0,d1:-d1-1] = numpy.copy(tmp)
'''
plan = sift.SiftPlan(template=img1, devicetype="cpu")
kp1 = plan.keypoints(img1)
kp2 = plan.keypoints(img2)
print("Keypoints for img1: %i\t img2: %i" % (kp1.size, kp2.size))
fig = pylab.figure()
sp1 = fig.add_subplot(122)
sp2 = fig.add_subplot(121)
im1 = sp1.imshow(img1)
im2 = sp2.imshow(img2)
#match = feature.sift_match(kp1, kp2)
mp = sift.MatchPlan(devicetype="cpu")
matching = mp.match(kp1, kp2)
print("After matching keeping %i" % matching.shape[0])
dx = matching[:, 1].x - matching[:, 0].x
dy = matching[:, 1].y - matching[:, 0].y
dangle = matching[:, 1].angle - matching[:, 0].angle
#here = os.path.dirname(os.path.abspath(__file__))
#there = os.path.join(here, "..", "build")
#lib = [os.path.abspath(os.path.join(there, i)) for i in os.listdir(there) if "lib" in i][0]
#sys.path.insert(0, lib)
import sift_pyocl as sift
import numpy
import scipy.misc
#
try:
lena = scipy.misc.imread(sys.argv[1])
except:
try:
import fabio
lena = fabio.open(sys.argv[1]).data
except:
lena = scipy.misc.lena()
logger.info("Using image lena from scipy")
else:
logger.info("Using image %s read with FabIO" % sys.argv[1])
else:
logger.info("Using image %s read with SciPy" % sys.argv[1])
s = sift.SiftPlan(template=lena, profile=True, context=utilstest.ctx)
kp = s.keypoints(lena)
print kp[:10]
if utilstest.args and not os.path.isfile(utilstest.args[0]):
s.log_profile(utilstest.args[0])
else:
s.log_profile()
import pylab
lena2 = scipy.misc.lena()
#shape = lena2.shape
#lena2 = scipy.misc.imread("../aerial.tiff") #for other tests
#filename = "/users/kieffer/Pictures/2010-01-22/11h59m14-Canon_DIGITAL_IXUS_850_IS-Pano21.jpg"
#shape = 1001, 1599
#lena2 = scipy.misc.imread(filename)#, flatten=True)
#shape = lena2.shape
#lena = numpy.ascontiguousarray(lena2[:shape[0], 0:shape[1], :])
lena = lena2
print lena.shape
# lena[:] = 0
# lena[100:110, 100:110] = 255
s = sift.SiftPlan(template=lena,
profile=True,
max_workgroup_size=128,
device=(1, 0))
kpg = s.keypoints(lena)
#except (Exception, pyopencl.RuntimeError) as error:
# print error
# s.log_profile()
# sys.exit(0)
kp = numpy.empty((kpg.size, 4), dtype=numpy.float32)
kp[:, 0] = kpg.x
kp[:, 1] = kpg.y
kp[:, 2] = kpg.scale
kp[:, 3] = kpg.angle
#print "Non infinite", numpy.isfinite(kpg.angle).sum()
s.log_profile()
fig = pylab.figure()
sp1 = fig.add_subplot(1, 2, 1)