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

See qatm_pytorch.ipynb

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