Ultralytics Benchmarks
This page provides a summary of the benchmarks gathered for Ultralytics across various datasets.
Playing Cards
The Playing Cards dataset is a custom object detection dataset containing over 1,000 images annotated across 13 card classes (e.g., Ace to King). It focuses on detecting cards in varied orientations and real-world settings. We use this dataset to benchmark Ultralytics models for lightweight, task-specific detection performance.
Table: Ultralytics on Playing Cards - RGB - (640x640) - ONNX - (50 epochs)
| Model | mAP@0.5 | mAP@0.5..0.95 |
|---|---|---|
| ultralytics-yolov8n-640x640-rgb | 0.829 | 0.700 |
Table: Ultralytics on PlayingCards - RGB - (640x640) - TFLite - i.MX 8M Plus
| Model | mAP@0.5 | mAP@0.5..0.95 | Time (ms) |
|---|---|---|---|
| ultralytics-yolov8n-640x640-rgb | 0.809 | 0.671 | 138.13 |
Visit the full Playingcards dataset Benchmark here
Object Detection and Segmentation Metrcis
Table: Ultralytics on CoffeeCup - RGB - (640x640) | ONNX
| Model | mAP@0.5 | mAP@0.5..0.95 | seg-mAP@0.5 | seg-mAP@0.5..0.95 |
|---|---|---|---|---|
| ultralytics-yolov8n-640x640-rgb | 0.993 | 0.991 | 0.993 | 0.982 |
Table: Ultralytics on CoffeeCup - RGB - (640x640) - TFLite - i.MX 8M Plus
| Model | mAP@0.5 | mAP@0.5..0.95 | seg-mAP@0.5 | seg-mAP@0.5..0.95 | Time (ms) |
|---|---|---|---|---|---|
| ultralytics-yolov8n-640x640-rgb | 0.995 | 0.891 | 0.995 | 0.970 | 170.89 |
Segmentation Metrcis
Visit the full Coffee Cup dataset Benchmark here
BDD100K
BDD100K is a large-scale autonomous driving dataset with 100K images annotated for tasks like object detection, lane detection, and segmentation. It features diverse weather, lighting, and geographic conditions. We benchmark Ultralytics models on BDD100K to evaluate performance in real-world driving scenarios.
Table: Ultralytics on BDD100K - RGB - (640x640) - ONNX - (100 epochs)
| Model | mAP@0.5 | mAP@0.5..0.95 |
|---|---|---|
| ultralytics-yolov8n-640x640-rgb | 0.325 | 0.173 |
Table: Ultralytics on BDD100K - RGB - (640x640) - TFLite - i.MX 8M Plus
| Model | mAP@0.5 | mAP@0.5..0.95 | Time (ms) |
|---|---|---|---|
| ultralytics-yolov8n-640x640-rgb | 0.272 | 0.138 | 137.66 |
Visit the full BDD100K dataset Benchmark here
This dataset contains only annotations for person class from original dataset. However, all the images are included during training as negative samples
Table: Ultralytics on COCO People - RGB - (640x640) - ONNX - (100 epochs)
| Model | mAP@0.5 | mAP@0.5..0.95 |
|---|---|---|
| ultralytics-yolov8n-640x640-rgb | 0.620 | 0.410 |
Table: Ultralytics on COCO People - RGB - (640x640) - TFLite - i.MX 8M Plus
| Model | mAP@0.5 | mAP@0.5..0.95 | Time (ms) |
|---|---|---|---|
| ultralytics-yolov8n-640x640-rgb | 0.583 | 0.374 | 137.43 |
Visit the full COCO People dataset Benchmark here
Note
COCO benchmark is coming soon !!!
Note
To see Imagenet metrics visit Ultralytics: Ultralytics ImageNet
BSP Version
i.MX 8M Plus is flashed with NXP Yocto BSP 6.12.