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YAML Metadata Warning:The task_categories "medical-imaging" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
Opth Project 1
This repository backs up the datasets, model checkpoints, experiment outputs, figures, manifests, and code snapshot used for Project 1: clinician-confirmed online adaptation for retinal diabetic retinopathy classification.
Contents
datasets/: archived fundus datasets used in the experiments.annotations/: IDRiD lesion/structure annotations for future lesion-click and attention-guided adaptation experiments.manifests/: labels and source/target split metadata.models/: trained ResNet50 checkpoints and validation metadata.results/: online adaptation summaries and bootstrap outputs.figures/: generated paper tables and plots.configs/: label mapping and source-target matrix.code/: OAIMS/classification code snapshot used for the experiments.docs/: study notes, paper planning logs, and dataset notes.
Primary Task
Referable diabetic retinopathy detection from fundus images, with grade 0/1 mapped to non-referable and grade 2/3/4 mapped to referable.
Intended Use
This backup is intended for research reproducibility and migration of the project across machines. The dataset archives are provided with attribution to the original data sources. Users are responsible for complying with each source dataset's license and terms.
Restore
Example:
tar -xf datasets/aptos2019.tar -C ./restored_datasets/
mkdir -p ./restored_datasets/eyepacs_augmented_resized_V2
tar -xf datasets/eyepacs_augmented_resized_v2_clean.tar -C ./restored_datasets/eyepacs_augmented_resized_V2/
See dataset_inventory.tsv, manifest_summary.tsv, and checksums.sha256 for file inventory and verification.
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