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Releases: mantasu/glasses-detector

v1.0.4

12 Sep 21:08

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Patch Notes

  • Fix resize bug identified in #22
  • Update demo.ipynb as Colab now supports Python 3.12
  • Remove deployment protection for tags; trigger doc deployment on release only

v1.0.3

08 May 17:07

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Patch Notes

Allow modifications of inference tensors; identified in #19

v1.0.2

15 Mar 16:26

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Patch Notes

Minor patch for compatibility with Python 3.13. Identified in #17.

v1.0.1

06 Mar 07:10

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Patch Notes

Minor patch to enable automatic weight downloading when using CLI. Also, updated demo.ipynb. Please refer to the major release for all the information.

v1.0.0

06 Mar 05:51

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Glasses Detector v1.0.0

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About

First stable1 release for Glasses Detector. Three tasks are supported for processing images with glasses: classification, detection, and segmentation. This includes glasses types and parts, as well as their shadows and eye-area. For all the available features and examples, please check documentation and notebook.

Note

Pre-trained weights for size large are not available as it seems most medium models perform better (less overfit due to tasks being binary). More experiments need to be conducted before large weights can be released in v1.1.0.

What's New

  • Features
    • Glasses and eye-area detection
    • More categories for each task
    • Better model performance
    • Simpler CLI
  • Architecture
    • New package structure
    • New model architectures
    • Simpler customization process (better inheritance structure)
  • Data
    • More datasets
    • Simpler data processing scripts
    • Kaggle notebooks for sub-tasks
  • Documentation
    • Full documentation of package-specific code
    • Features & examples
    • Fancier documentation page style

Other

As before, although the code for training (e.g., datasets, metrics) is part of PIP package, the actual data processing, training, and model analysis scripts are only available when fully cloning the repository. Please check Data and Running sections for details on how to train/test your own models.

  1. Kind of stable since large weights are missing (technically not but they perform worse than medium)

v0.1.1

08 Jul 08:26

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Changes

Fixed version tag (0.1.0 $\to$ v0.1.0) when the download link of the model weights is created.

v0.1.0

08 Jul 08:05

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Initial Release

This is the initial BETA release of glasses-detector package. The package structure is complete, however, not all the models are trained. In case custom models are preferred, training and testing scripts are fully ready.

The pre-trained weights are available for these models:

  • SunglassesClassifier or sunglasses-classifier
  • FullGlassesSegmenter or full-glasses-segmenter
  • FullSunglassesSegmenter or full-sunglasses-segmenter

Note: for classification, "huge" category of weights is missing. For full glasses segmentation, "medium" category of weights is missing. The other 4 categories of weights for both tasks are available.

Please refer to the documentation page for more details.