Yolo26n Question Segmentation

--- library_name: ultralytics pipeline_tag: object-detection license: cc-by-4.0 tags: - yolo - object-detection - document-analysis - pdf - question-segmentation - turkish datasets: - custom base_model: - yolo26n --- # YOLO26N Question Segmentation Smaller release checkpoint that slightly outperforms the YOLO26M release on both held-out test sets. - Task: object detection - Classes: `question` - Input size: `1280` - Base model: `yolo26n` ## Intended use This model is designed to detect question regions in exam booklets, worksheets, and PDF page renders. It works best on dense educational pages with clear question boundaries. ## Release notes This release checkpoint was trained for 50 epochs on the cleaned one-class question detection dataset. ## Test results ### Old held-out test set | Model | Precision | Recall | mAP50 | mAP50-95 | | --- | --- | --- | --- | --- | | YOLO26N Question Segmentation | 0.988 | 0.983 | 0.989 | 0.924 | ### Combined held-out test set | Model | Precision | Recall | mAP50 | mAP50-95 | | --- | --- | --- | --- | --- | | YOLO26N Question Segmentation | 0.991 | 0.988 | 0.993 | 0.962 | ## Usage ```python from ultralytics import YOLO model = YOLO("hf://samil24/yolo26n-question-segmentation") results = model("page.png", imgsz=1280, conf=0.25) ``` ## Included files - `best.pt`: release checkpoint - `metrics_summary.json`: test-set metrics for this release - `confidence_sweep_summary.json`: confidence sweep outputs used during evaluation - `comparison_examples/`: side-by-side qualitative examples ## Data note Some of the training data comes from public Roboflow projects used in earlier versions of this question-segmentation pipeline: 1. **PDF Soru Cikarma** (tanimazsinu): [Link](https://universe.roboflow.com/tanimazsinu/pdf-soru-cikarma-wmwfu) 2. **WholeQuestionDetection** (Gazi University): [Link](https://universe.roboflow.com/gazi-university-gi7lx/wholequestiondetection) 3. **ExamBuddy** (ExamBuddy): [Link](https://universe.roboflow.com/exambuddy/exambuddy) 4. **Questions** (Terry Li): [Link](https://universe.roboflow.com/terry-li/questions-klidd) 5. **Question Parsing from Document** (Sefa): [Link](https://universe.roboflow.com/sefa-8tkmm/question-parsing-from-document) 6. **Question Dedector** (Nur Etinkaya): [Link](https://universe.roboflow.com/nur-etinkaya/question-dedector) 7. **Sorukes** (Sorualgilama): [Link](ht...