def test_cross_ORB(self):
feature_name = self.opts.get('--feature', 'orb-flann')
detector, matcher = init_feature(feature_name)
with Timer('affine simulation detecting'):
kp1, desc1 = ab.affine_detect(detector, self.img1) #ASIFT
with Timer('Feature detecting'):
h, w = self.img2.shape[:2]
mask = np.zeros((h, w), np.uint8)
mask[:] = 255
kp2, desc2 = ab.affine_detect(detector, self.img2) #ASIFT
print('imgQ - %d features, imgT - %d features' % (len(kp1), len(kp2)))
with Timer('matching'):
raw_matches12 = matcher.knnMatch(desc2, trainDescriptors=desc1, k=2) #2
raw_matches21 = matcher.knnMatch(desc1, trainDescriptors=desc2, k=2) #2
p2, p1, kp_pairs = filter_matches_wcross(kp1, kp2, raw_matches12, raw_matches21)
print('matched points T=%d, Q=%d' % (len(p1), len(p2)))
self.assertEqual(len(p1), len(p2), "Not same numbers")
def test_cross_check_same(self):
feature_name = self.opts.get('--feature', 'sift')
detector, matcher = init_feature(feature_name)
with Timer('Feature detecting'):
h, w = self.img1.shape[:2]
mask = np.zeros((h, w), np.uint8)
mask[:] = 255
kp1, desc1 = detector.detectAndCompute(self.img1, mask)
with Timer('Feature detecting'):
h, w = self.img2.shape[:2]
mask = np.zeros((h, w), np.uint8)
mask[:] = 255
kp2, desc2 = detector.detectAndCompute(self.img2, mask)
print('imgQ - %d features, imgT - %d features' % (len(kp1), len(kp2)))
with Timer('matching'):
raw_matches12 = matcher.knnMatch(desc2, trainDescriptors=desc1, k=2) #2
raw_matches21 = matcher.knnMatch(desc1, trainDescriptors=desc2, k=2) #2
p2, p1, kp_pairs = filter_matches_wcross(kp1, kp2, raw_matches12, raw_matches21)
print('matched points T=%d, Q=%d' % (len(p1), len(p2)))
self.assertEqual(len(p1), len(p2), "Not same numbers")
def setUp(self):
""" Set up befor test
Using templates is qr.png
Using input test image is 1.png
Using feature function is SIFT
Using split mesh number is 64
"""
import sys, getopt
opts, args = getopt.getopt(sys.argv[1:], '', ['feature='])
opts = dict(opts)
feature_name = opts.get('--feature', 'sift')
try:
fn1, fn2 = args
except:
import os
dir = os.path.abspath(
os.path.join(os.path.dirname(__file__), os.pardir, os.pardir,
os.pardir))
fn1 = os.path.abspath(
os.path.join(dir, 'data/templates/qrmarker.png'))
fn2 = os.path.abspath(
os.path.join(dir, 'data/templates/qrmarker.png'))
#fn2 = os.path.abspath(os.path.join(dir_path_full, 'data/inputs/unittest/smpl_1.414214_152.735065.png'))
self.img1 = cv2.imread(fn1, 0)
self.img2 = cv2.imread(fn2, 0)
self.detector, self.matcher = init_feature(feature_name)
self.splt_num = 64
if self.img1 is None:
print('Failed to load fn1:', fn1)
sys.exit(1)
if self.img2 is None:
print('Failed to load fn2:', fn2)
sys.exit(1)
if self.detector is None:
print('unknown feature:', feature_name)
sys.exit(1)
def test_module():
import os
import sys
dir = os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir, os.pardir))
fn1 = os.path.abspath(os.path.join(dir, 'data/templates/qrmarker.png'))
fn2 = os.path.abspath(os.path.join(dir, 'data/inputs/unittest/smpl_1.414214_152.735065.png'))
imgQ = cv2.imread(fn1, 0)
imgT = cv2.imread(fn2, 0)
detector, matcher = init_feature('sift')
if imgQ is None:
print('Failed to load fn1:', fn1)
sys.exit(1)
if imgT is None:
print('Failed to load fn2:', fn2)
sys.exit(1)
if detector is None:
print('unknown feature:', feature_name)
sys.exit(1)
template_information = {"_fn": "tmp.png", "_cols": 800, "_rows": 600, "_scols": 8, "_srows": 8, "_nneighbor": 4}
temp_inf = TmpInf(**template_information)
return temp_inf, imgQ, imgT, detector, matcher
opts, args = getopt.getopt(sys.argv[1:], '', ['feature='])
opts = dict(opts)
feature_name = opts.get('--feature', 'sift')
try:
fn1, fn2 = args
except:
import os
dir = os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir, os.pardir))
fn1 = os.path.abspath(os.path.join(dir, 'data/templates/qrmarker.png'))
fn2 = os.path.abspath(os.path.join(dir, 'data/inputs/unittest/smpl_1.414214_152.735065.png'))
imgQ = cv2.imread(fn1, 0)
imgT = cv2.imread(fn2, 0)
detector, matcher = init_feature(feature_name)
if imgQ is None:
print('Failed to load fn1:', fn1)
sys.exit(1)
print("Using Query: {}".format(fn1))
if imgT is None:
print('Failed to load fn2:', fn2)
sys.exit(1)
print("Using Training: {}".format(fn2))
if detector is None:
print('unknown feature:', feature_name)
sys.exit(1)
print('Using :', feature_name)
template_fn, ext = os.path.splitext(os.path.basename(fn1))
visS = draw_matches_for_meshes(imgQ, imgT, Hs=Hs_stable)
cv2.imwrite(myfsys.getf_output(expt_names, 'meshes_stable.png'), visS)
viw = explore_match_for_meshes('affine find_obj', imgQ, imgT, kp_pairs_long_stable, Hs=Hs_stable)
cv2.imwrite(myfsys.getf_output(expt_names, 'meshes_and_keypoints_stable.png'), viw)
return vis, visS, viw
if __name__ == '__main__':
expt_path = myfsys.setup_expt_directory(os.path.basename(__file__))
logging.basicConfig(filename=os.path.join(expt_path, 'log.txt'), level=logging.DEBUG)
a = os.listdir(myfsys.get_dir_full_path_(myfsys.DirNames.TEMPLATES.value))
a.pop(a.index('mesh_label.png'))
detector, matcher = init_feature(emod.Features.SIFT.name)
for template in a:
template_name, ext = template.split('.')
print(template_name)
fn = myfsys.get_template_file_full_path_(template)
imgQ, kpQ, descQ = detect(detector, fn, splt_num=64, simu_type='asift')
#実験は平面のみ
subj_dir = emod.PrefixShapes.PL.value + template_name
testsets = os.listdir(myfsys.get_inputs_dir_full_path(subj_dir))
for testcase in testsets:
print(myfsys.getf_input(subj_dir, testcase))
# fnQ = ('qrmarker.png', 'menko.png', 'nabe.png', 'nabe.png', 'nabe.png')
# dirT = ('unittest', 'crv_menko', 'pics_nabe', 'real-crv_nabe', 'mltf_nabe')
# fnT = ('smpl_1.414214_152.735065.png', 'smpl_2.828427_152.735065.png', 'IMG_1118.JPG', 'my_photo-5.jpg', 'smpl_1.414214_152.735065.png')