Instructions to use maco018/billboard-detection-Yolo11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use maco018/billboard-detection-Yolo11 with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("maco018/billboard-detection-Yolo11", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -22,11 +22,11 @@ This model was created with 100 epochs using CUDA 12.4 and Pytorch 2.6.0.
|
|
| 22 |
|
| 23 |
| Model | Precision (Epoch) | Recall (Epoch) | mAP50 (Epoch) | mAP50-95 (Epoch) |
|
| 24 |
| ----- | ----------------- | -------------- | ------------- | ---------------- |
|
| 25 |
-
|
|
| 26 |
-
|
|
| 27 |
-
|
|
| 28 |
-
|
|
| 29 |
-
|
|
| 30 |
|
| 31 |
|
| 32 |
Further results can be found in [Results Folder](https://huggingface.co/maco018/billboard-detection-Yolo11/tree/main/results).
|
|
|
|
| 22 |
|
| 23 |
| Model | Precision (Epoch) | Recall (Epoch) | mAP50 (Epoch) | mAP50-95 (Epoch) |
|
| 24 |
| ----- | ----------------- | -------------- | ------------- | ---------------- |
|
| 25 |
+
| YOLO_11n | 0.73613 (epoch: 66) | 0.67308 (epoch: 88) | 0.70351 (epoch: 87) | 0.43033 (epoch: 80) |
|
| 26 |
+
| YOLO_11s| 0.7225 (epoch: 98) | 0.67735 (epoch: 81) | 0.70855 (epoch: 76) | 0.43518 (epoch: 77) |
|
| 27 |
+
| YOLO_11m| 0.73249 (epoch: 80) | 0.6745 (epoch: 73) | 0.71053 (epoch: 87) | 0.43404 (epoch: 62) |
|
| 28 |
+
| YOLO_11l | 0.74729 (epoch: 98) | 0.68174 (epoch: 49) | 0.71778 (epoch: 75) | 0.44731 (epoch: 89) |
|
| 29 |
+
| YOLO_11x | 0.74299 (epoch: 94) | 0.6688 (epoch: 80) | 0.7113 (epoch: 60) | 0.4437 (epoch: 89) |
|
| 30 |
|
| 31 |
|
| 32 |
Further results can be found in [Results Folder](https://huggingface.co/maco018/billboard-detection-Yolo11/tree/main/results).
|