kamata1729/QATM_pytorch
Pytorch Implementation of QATM:Quality-Aware Template Matching For Deep Learning
This tool helps you quickly locate specific small images or patterns within a larger image, even if the patterns are slightly different or of varying quality. You provide a large 'sample' image and a collection of 'template' images, and it tells you where each template appears in the sample. This is for anyone who needs to automatically find known objects, logos, or features within visual content.
198 stars. No commits in the last 6 months.
Use this if you need to reliably identify and pinpoint the exact locations of particular visual elements across many images, despite variations in appearance.
Not ideal if you need to detect objects that are not predefined as specific templates or if you're looking for general object recognition rather than precise template matching.
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198
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Language
Jupyter Notebook
License
MIT
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Last pushed
Aug 22, 2023
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