def detect(detector, fn, splt_num=64, simu_type="default"):
full_fn = myfsys.get_template_file_full_path_(fn)
img = read_image(full_fn)
cv2.imshow('hoge', img)
with Timer('Detection with [ ' + simu_type + ' ]'):
splt_kp, splt_desc = spltA.affine_detect_into_mesh(detector, splt_num, img, simu_param=simu_type)
return img, splt_kp, splt_desc
def expt_meshdtct_perf_spltASIFT(column_num = 8, row_num = 8, template_f = 'qrmarker.png'):
split_num = column_num * row_num
template_fn = myfsys.get_template_file_full_path_(template_f)
detector, matcher = init_feature(emod.Features.SIFT)
imgQ, s_kpQ, s_descQ = split_asift_detect(detector, template_fn, split_num=split_num)
keyargs = {'prefix_shape': emod.PrefixShapes.PL.value, 'template_fn': template_fn}
testset_full_path = myfsys.get_dir_full_path_testset('cgs', **keyargs)
print(testset_full_path)
testcase_fns = os.listdir(testset_full_path)
testcase_fns.sort()
print(testcase_fns)
results = []
for input_fns in testcase_fns:
calculate_each_mesh(column_num, detector, input_fns, matcher, results, row_num, s_descQ, s_kpQ)
logging.getLogger('my_file_path_manager').setLevel(level=logging.DEBUG)
logging.getLogger('my_file_path_manager').addHandler(timeRotationHandler)
logging.getLogger('my_file_path_manager').addHandler(consoleHandler)
logger.info(__doc__.format(os.path.basename(__file__)))
a = myfsys.make_list_template_filename()
a = emod.only(a, 'glass.png')
detector, matcher = init_feature(emod.Features.SIFT.name)
column_num = 8
row_num = 8
split_num = column_num * row_num
expt_name = os.path.basename(expt_path)
for template_fn in a:
logger.info('Template:{}'.format(template_fn))
# global s_kpQ, s_descQ, testset_full_path
template_full_fn = myfsys.get_template_file_full_path_(template_fn)
# imgQ, s_kpQ, s_descQ = split_asift_detect(detector, template_full_fn, split_num=split_num)
keyargs = {'prefix_shape': emod.PrefixShapes.PL.value, 'template_fn': template_fn}
testset_full_path = myfsys.get_dir_full_path_testset('cgs', **keyargs)
testset_name = os.path.basename(testset_full_path)
logger.debug('testset_name is {}'.format(testset_name))
logger.info('Test Set:{}'.format(testset_name))
output_dir = myfsys.setup_output_directory(expt_name, testset_name, 'npfiles')
testcase_fns = os.listdir(testset_full_path)
testcase_fns.sort()
print(testcase_fns)
# dictionary = exam(testset_full_path, s_kpQ, s_descQ)
# np.savez_compressed(os.path.join(expt_path, testset_name), **dictionary)
# result_collection = np.load(os.path.join(expt_path, testset_name+'.npz'))
timeRotationHandler)
logging.getLogger('commons.my_file_path_manager').addHandler(
consoleHandler)
logger.info(__doc__.format(os.path.basename(__file__)))
import sys, getopt
opts, args = getopt.getopt(sys.argv[1:], '', ['feature='])
opts = dict(opts)
feature_name = opts.get('--feature', 'sift')
try:
fn1, fn2, column_num, row_num = args
except:
dir = os.path.abspath(
os.path.join(os.path.dirname(__file__), os.pardir, os.pardir))
fn1 = myfsys.get_template_file_full_path_('qrmarker.png')
fn2 = os.path.abspath(
os.path.join(dir, 'data/inputs/cgs/pl_qrmarker/288_010-350.png'))
column_num = 8
row_num = 8
detector, matcher = init_feature(feature_name)
if detector is None:
logger.info('unknown feature:{}'.format(feature_name))
sys.exit(1)
split_num = column_num * row_num
img_q, splt_kp_q, splt_desc_q = split_asift_detect(detector, fn1,
split_num)
def asfit():
pass
if __name__ == '__main__':
expt_path = setup_expt_directory()
logging.basicConfig(filename=os.path.join(expt_path, 'log.txt'),
level=logging.DEBUG)
logger.info(__doc__.format(os.path.basename(__file__)))
a = os.listdir(myfsys.get_dir_full_path_(DirNames.TEMPLATES.value))
a.pop(a.index('mesh_label.png'))
detector, matcher = init_feature(Features.SIFT.name)
for testcase in a:
logger.info(testcase + 'の場合')
fn = myfsys.get_template_file_full_path_(testcase)
imgQ, kpQ, descQ = asift_detect(detector, fn)
imgT, kpT, descT = asift_detect(detector, fn)
logger.info('imgQ - %d features, imgT - %d features' %
(len(kpQ), len(kpT)))
with Timer('matching'):
pQ, pT, pairs = match_with_cross(matcher, descQ, kpQ, descT, kpT)
if len(pQ) >= 4:
H, status = cv2.findHomography(pQ, pT, cv2.RANSAC, 5.0)
logger.info('%d / %d inliers/matched' %
(np.sum(status), len(status)))
# do not draw outliers (there will be a lot of them)
pairs = [kpp for kpp, flag in zip(pairs, status) if flag]
else:
H, status = None, None
logger.info(
