Add training pipeline for AE CNN models - #5
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gc9591
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Jun 27, 2026
gc9591
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- Implemented step 0a to compute spectrograms from raw HDF5 signals and save as multichannel TIFFs.
- Created step 1 to generate semantic labels using a trained model.
- Developed step 1a (alternative) to generate semantic labels from pre-computed spectrograms.
- Added step 2a to create COCO dataset from semantic labels.
- Implemented step 2b to convert COCO dataset to YOLO format.
- Established step 3 for training Faster R-CNN and Mask R-CNN models.
- Added training scripts for YOLOv8 detection and segmentation.
- Created step 4 for saving model checkpoints.
- Introduced necessary utility functions and configurations for dataset handling and model training.
- Implemented step 0a to compute spectrograms from raw HDF5 signals and save as multichannel TIFFs. - Created step 1 to generate semantic labels using a trained model. - Developed step 1a (alternative) to generate semantic labels from pre-computed spectrograms. - Added step 2a to create COCO dataset from semantic labels. - Implemented step 2b to convert COCO dataset to YOLO format. - Established step 3 for training Faster R-CNN and Mask R-CNN models. - Added training scripts for YOLOv8 detection and segmentation. - Created step 4 for saving model checkpoints. - Introduced necessary utility functions and configurations for dataset handling and model training.
nathanchenseanwalter
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Jul 8, 2026
Add training pipeline for AE CNN models
nathanchenseanwalter
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Jul 8, 2026
Add training pipeline for AE CNN models
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