def get_split_keypoint_detector(_template_fn, _temp_inf, _detector, _imgQ):
try:
with splta.Timer('Lording pickle'):
splt_kpQ, splt_descQ = splta.affine_load_into_mesh(
_template_fn, _temp_inf.get_splitnum())
except ValueError as e:
print(e.args)
print('If you need to save {} to file as datavase. ¥n' +
' Execute makedb/make_split_combine_featureDB_from_templates.py')
with splta.Timer('Detection and dividing'):
splt_kpQ, splt_descQ = splta.affine_detect_into_mesh(
_detector, _temp_inf.get_splitnum(), _imgQ, simu_param='asift')
return splt_kpQ, splt_descQ
h, w = imgQ.shape[:2]
template_fn, ext = os.path.splitext(os.path.basename(fn1_full))
template_information = {
"_fn": "tmp.png",
"template_img": template_fn,
"_cols": w,
"_rows": h,
"_scols": scols,
"_srows": srows,
"_nneighbor": 4
}
temp_inf = splta.TmpInf(**template_information)
try:
with splta.Timer('Lording pickle'):
splt_kpQ, splt_descQ = splta.affine_load_into_mesh(
template_fn, temp_inf.get_splitnum())
except ValueError as e:
print(e.args)
print('If you need to save {} to file as datavase. ¥n' +
' Execute makedb/make_split_combine_featureDB_from_templates.py')
with splta.Timer('Detection and dividing'):
splt_kpQ, splt_descQ = splta.affine_detect_into_mesh(
detector, temp_inf.get_splitnum(), imgQ, simu_param='asift')
mesh_k_num = splta.np.array([len(keypoints) for keypoints in splt_kpQ
]).reshape(temp_inf.get_mesh_shape())
median = splta.np.nanmedian(mesh_k_num)
fn, ext = os.path.splitext(os.path.basename(fn2_full))
testset_name = os.path.basename(os.path.dirname(fn2_full))
imgT = splta.cv2.imread(fn2_full, 0)