Instructions to use jjhhjj/PCB_ObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use jjhhjj/PCB_ObjectDetection with ultralytics:
from ultralytics import YOLOvv11 model = YOLOvv11.from_pretrained("jjhhjj/PCB_ObjectDetection") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - object-detection | |
| - pcb | |
| - yolov11 | |
| - rt-detr | |
| - ultralytics | |
| # PCB Object Detection Checkpoints | |
| PCB 缺陷目标检测训练结果与模型权重。 | |
| ## 包含的训练结果 | |
| - RT-DETR:`rtdetr-AKConv` | |
| - YOLOv11:`yolo11n`、`yolo11s`、`yolo11m`、`yolo11L`、`yolo11x` | |
| 每个训练目录保留了训练配置、指标、可视化结果及 `weights` 下的模型权重。 | |
| ## 目录结构 | |
| ```text | |
| rt-detr/runs/train/rtdetr-AKConv/ | |
| yolov11/runs/train/yolo11n/ | |
| yolov11/runs/train/yolo11s/ | |
| yolov11/runs/train/yolo11m/ | |
| yolov11/runs/train/yolo11L/ | |
| yolov11/runs/train/yolo11x/ | |
| ``` | |
| 权重文件包括 `best.pt`、`last.pt`,YOLOv11 目录还包含相应的 FP32 权重。 | |
| ## 下载 | |
| ```powershell | |
| hf download jjhhjj/PCB_ObjectDetection --local-dir .\PCB_ObjectDetection | |
| ``` | |