Tbx11k Object Detection Yolov8
This model is a Ultralytics YOLOv8m detector fine-tuned on the TBX11K chest X-ray dataset for structural Tuberculosis localization and classification.
Model source
- Kind
- Other
- File size
- 49.7–198 MB
- Version
- vBest
- Updated
- Oct 21, 2026
- Source
- Hugging Face
Source description
TBX11K YOLOv8m — Tuberculosis Detection and Localization
This model is a Ultralytics YOLOv8m detector fine-tuned on the TBX11K chest X-ray dataset for structural Tuberculosis localization and classification.
Labeled Test Set Performance Evaluation
Evaluated on an independent, labeled split extracted cleanly from the validation data stream to prevent zero-label evaluation matrix distortions.
| Metric | Score |
|---|---|
| Test mAP@0.5 | 0.3551 |
| Test mAP@0.5:0.95 | 0.1372 |
Per-class AP@0.5 Breakdown
| Class | AP@0.5 |
|---|---|
| active_tb | 0.5068 |
| latent_tb | 0.2034 |
Class Imbalance Optimization Strategy
- Grayscale-tuned heavier data augmentations (mosaic, spatial scaling, translation, brightness adjustments)
- Unannotated background control files maintained to minimize false positive bounding box proposals
Internal Network Class Configuration Map (0-Indexed)
0: Active TB1: Latent TB (Note: 'Healthy' files carry no boxes and function natively as architectural background signal)
Sources
1 source
Sources
1 sourceVerified Oct 21
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Model artifacts
12 artifacts
Model artifacts
12 artifactsSource excerpts
2 excerpts
Source excerpts
2 excerpts--- license: mit tags: - object-detection - medical - tuberculosis - yolov8 - chest-xray datasets: - tbx11k pipeline_tag: object-detection --- # TBX11K YOLOv8m — Tuberculosis Detection and Localization This model is a Ultralytics YOLOv8m detector fine-tuned on the TBX11K chest X-ray dataset for structural Tuberculosis localization and classification. ## Labeled Test Set Performance Evaluation Evaluated on an independent, labeled split extracted cleanly from the validation data stream to prevent zero-label evaluation matrix distortions. | Metric | Score | |--------|-------| | Test mAP@0.5 | 0.3551 | | Test mAP@0.5:0.95 | 0.1372 | ### Per-class AP@0.5 Breakdown | Class | AP@0.5 | |-------|--------| | active_tb | 0.5068 | | latent_tb | 0.2034 | ## Class Imbalance Optimization Strategy - Grayscale-tuned heavier data augmentations (mosaic, spatial scaling, translation, brightness adjustments) - Unannotated background control files maintained to minimize false positive bounding box proposals ## Internal Network Class Configuration Map (0-Indexed) - `0`: Active TB - `1`: Latent TB *(Note: 'Healthy' files carry no boxes and function natively as architectural background signal)*
Source context: 0 downloads · 0 likes · Pipeline object-detection · Repo nakasiga/tbx11k-object-detection-yolov8
