Pytorch Non-Official Implementation of QATM:Quality-Aware Template Matching For Deep Learning
arxiv: https://arxiv.org/abs/1903.07254
original code (tensorflow+keras): https://github.com/cplusx/QATM
Qiita(Japanese): https://qiita.com/kamata1729/items/11fd55992c740526f6fc
Dependencies
- torch(1.0.0)
- torchvision(0.2.1)
- cv2
- seaborn
- sklearn
- pathlib
Usage
or
python qatm.py -s sample/sample1.jpg -t template --cuda
- Add
--cuda
option to use GPU - Add
-s
/--sample_image
to specify sample image
only single sample image can be specified in this present implementation - Add
-t
/--template_images_dir
to specify template image dir
[notice] If neither -s
nor -t
is specified, the demo program will be executed, which is the same as:
python qatm.py -s sample/sample1.jpg -t template
--thresh_csv
and--alpha
option can also be added
Result of Demo
template1_1.png
to template1_4.png
are contained in sample1.jpg
, however, template1_dummy.png
is a dummy and not contained
template1_1.png | template1_2.png | template1_3.png | template1_4.png | template1_dummy.png |
---|---|---|---|---|