- Add more CNN networks apart from the default MobileNetv3- the new networks added are: EfficientNet and ViT 190 - Allow user to define and plugin their own custom CNN models for encoding generation - an example of how to use this can be seen here: `imagededup/examples/use_custom_model.ipynb` 190 - Make encoding generation quicker and memory-efficient by removal of torch grad calculation 192
🔴 Bug fixes
- Update CNN link in readme to point to MobilenetV3 paper. - Remove 'pretrained' parameter of mobilenetv3 to get rid of deprecation warning and use 'weights' parameter instead. - Some typos.
0.3.1
✨ New features and improvements
- Add optional multiprocessing flags 185 - Add gpu support for CNN encoding generation 179 - Add support for webp images 153
Breaking changes: None
0.3.0
Installation fix - Make package installable by removing tensorflow as a dependency and replacing it with pytorch 173 - Drop support for python 3.6 and python 3.7 173
✨ New features and improvements - Use MobileNetv3 for generating CNN encodings 173 - Introduce a 'recursive' option to generate encodings for images organized in a nested directory structure 104
Breaking changes - Size of CNN encodings is 576 instead of 1024 173 - Since CNN encodings are generated using a different network, the robustness might be different; user might need to change similarity threshold settings 173 - Hashes (all types) may be different from previous versions for a given image 173
0.2.4
🔴 Bug fixes - Fix broken cython brute force in Python 3.8 117 - Close figure after plotting to avoid figure overwrite 111 - Allow encode_image method of cnn to accept 2d arrays 110 - Relax dependencies and update packages 116, 107, 102, 119
0.2.2
✨ New features and improvements - Switched to creating list comprehensions to create lists on demand instead of slower explicit for loops that rely on calling the append function in every iteration. 76 - Used sets for membership tests - Used broadcasting instead of explicit for loops
0.2.1
🔴 Bug fixes - Add Manifest.in so that c files are included in the source distribution 72