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Model 3.1 Release 🎨 πŸ“ πŸ› ⚑ πŸ”§ #44

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merged 23 commits into from
Jun 3, 2024

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🎨 πŸ“ πŸ› ⚑ πŸ”§ Update styles, rename project, remove bad augmentations, add hparam tuner, and update frontend

🎨 Change the style of the buttons so they don't overlap each other and other elements.
πŸ“ Rename project to LesNet (Lesion Net).
πŸ› Remove bad augmentations that affect training data.
⚑ πŸ”§ Add hyperparameter tuner (experiments).
🎨 Update frontend with a new look and feel.
⚑ πŸ”§ Update batch size and learning rate configurations, add data augmenter and improve inference. Changes include:

  • Setting batch size to 256.
  • Updating starting learning rates to 0.001.
  • Adding a data augmenter that does not require downloading all images.
  • Making inference and label improvements.
  • Introducing a new model quantize command.
  • Directory cleanup.
  • adjusting learning rate cooldown to 5 and lr patience to 7 and early stopping to 42 - more aggressive training

- ⬆️ Upgraded to using a larger dataset of 52,379 images across 28 categories to improve model training and accuracy.
- πŸ” Added and removed k-fold splits to optimize dataset utilization and model evaluation.
- πŸ“ Changed model naming to better reflect the updates in version 3.1.
- πŸ”„ Continued simplification of dataset loading methods for increased efficiency.
- πŸ–ΌοΈ Adjusted image processing to use 256x256 resolution, reducing storage and memory usage.
- πŸ“ Implemented resizing before saving images to further conserve storage.
- πŸ› οΈ Fixed and improved image augmentation for better dataset balancing.
- βš–οΈ Adjusted hyperparameters, added class weights, and optimized augmentation settings.
- πŸ”§ Updated system configurations, integrating advanced model architectures like ResNet50 and setting mixed precision policies.
- 🌐 Streamlined UI and data handling for more efficient training processes and model evaluations.
- πŸ“ˆ Enhanced stratified k-fold integration with oversampling for balanced training.
- πŸ› Fixed various bugs across the system and removed outdated class weight calculations.
- 🎨 Expanded prediction capabilities to handle multiple categories and refined the codebase for peak performance.
- πŸ“ Updated README and related documentation to enhance clarity and provide a detailed project roadmap.
# Conflicts:
#	setup.py
#	skinvestigatorai/services/feature_extraction_service.py
#	skinvestigatorai/templates/evaluate.jinja2
#	skinvestigatorai/views/predict_view.py
…ions, add hparam tuner, and update frontend

- 🎨 Change the style of the buttons so they don't overlap each other and other elements.
- πŸ“ Rename project to LesNet (Lesion Net).
- πŸ› Remove bad augmentations that affect training data.
- ⚑ πŸ”§ Add hyperparameter tuner (experiments).
- 🎨 Update frontend with a new look and feel.
- ⚑ πŸ”§ Update batch size and learning rate configurations, add data augmenter and improve inference. Changes include:
Β  - Setting batch size to 256.
Β  - Updating starting learning rates to 0.001.
Β  - Adding a data augmenter that does not require downloading all images.
Β  - Making inference and label improvements.
Β  - Introducing a new model quantize command.
Β  - Directory cleanup.
Β  - adjusting learning rate cooldown to 5 and lr patience to 7 and early stopping to 42 - more aggressive training
@Thomasbehan Thomasbehan added documentation Improvements or additions to documentation enhancement New feature or request Docker Docker Related Deployment Deployment Related dataset Dataset Related labels Jun 3, 2024
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render bot commented Jun 3, 2024

@Thomasbehan Thomasbehan added the bug Something isn't working label Jun 3, 2024
@Thomasbehan Thomasbehan added Security Security Related Model AI Model Related labels Jun 3, 2024
@Thomasbehan Thomasbehan merged commit 603967d into main Jun 3, 2024
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