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Yolo26n Question Segmentation

Smaller release checkpoint that slightly outperforms the YOLO26M release on both held-out test sets.

Sourcehuggingface.co/samil24/yolo26n-question-segmentation/tree/d04b607683dff130297cea6fd9b0e96a85f48869
KindOtherVersionRevision d04b607

Model source

Kind
Other
File size
5.22 MB
Version
vRevision d04b607
Updated
Sep 16, 2026
Downloads
7
Tasks
Object detection
Source
Hugging Face

Source description

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

ModelPrecisionRecallmAP50mAP50-95
YOLO26N Question Segmentation0.9880.9830.9890.924

Combined held-out test set

ModelPrecisionRecallmAP50mAP50-95
YOLO26N Question Segmentation0.9910.9880.9930.962

Usage

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
  2. WholeQuestionDetection (Gazi University): Link
  3. ExamBuddy (ExamBuddy): Link
  4. Questions (Terry Li): Link
  5. Question Parsing from Document (Sefa): Link
  6. Question Dedector (Nur Etinkaya): Link
  7. Sorukes (Sorualgilama): Link
  8. Question Detection (Cognizen): Link
  9. Questions2 (Fiver): Link
  10. Question-New (Question): Link

License

This release is published under CC-BY-4.0.

Sources

1 source
Hugging FacePrimaryVersion d04b607683dff130297cea6fd9b0e96a85f48869
huggingface.co/samil24/yolo26n-question-segmentation/tree/d04b607683dff130297cea6fd9b0e96a85f48869

Verified Sep 16

Model artifacts

1 artifact

best.pt

pt · 5.22 MB · SHA-256 2cdd0d47695b…f964 · Hugging Face

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Source excerpts

2 excerpts
ReadmeSep 16huggingface.co/samil24/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...

NoteSep 16huggingface.co/samil24/yolo26n-question-segmentation

Source context: 7 downloads · 0 likes · Pipeline object-detection · Library ultralytics · Repo samil24/yolo26n-question-segmentation