---
license: cc-by-4.0
library_name: onnx
pipeline_tag: object-detection
tags: [object-detection, onnx, yolo11, rt-detr, gemstone, quality-control]
---

# GemScan inclusion detectors (ONNX)

YOLO11s and RT-DETR-L fine-tuned to detect inclusions in diamond photos, exported to ONNX
(opset 17, static 1×3×640×640 input, FP32). `manifest.json` lists each file with its
architecture, input size and class names.

Test split (16 images, 117 inclusions):

| Model | Precision | Recall | mAP50 | mAP50-95 |
|---|---:|---:|---:|---:|
| YOLO11s | 0.390 | 0.213 | 0.187 | 0.059 |
| RT-DETR-L | 0.357 | 0.282 | 0.195 | 0.067 |

Trained on [Diamond Inclusion](https://universe.roboflow.com/diamond-classification-data/diamond-inclusion) (CC BY 4.0) by Diamond Classification Data.
Pre/post-processing that reproduces Ultralytics exactly is in `app/inference.py` of the source repository.