use yolo12 to detect isolators
fly6516
c33f35d0de
- 在 train/labels 和 valid/labels目录下添加了多个标签文件 - 标签文件包含物体检测的坐标信息 - 此次添加的标签主要用于绝缘子检测任务 |
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|---|---|---|
| runs/detect | ||
| train | ||
| valid | ||
| data.yaml | ||
| README.dataset.txt | ||
| README.roboflow.txt | ||
| test.py | ||
| train.py | ||
isolators - v1 2024-06-17 7:53am ============================== This dataset was exported via roboflow.com on March 24, 2025 at 2:03 PM GMT Roboflow is an end-to-end computer vision platform that helps you * collaborate with your team on computer vision projects * collect & organize images * understand and search unstructured image data * annotate, and create datasets * export, train, and deploy computer vision models * use active learning to improve your dataset over time For state of the art Computer Vision training notebooks you can use with this dataset, visit https://github.com/roboflow/notebooks To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com The dataset includes 130 images. Isolators are annotated in YOLOv12 format. The following pre-processing was applied to each image: * Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x480 (Stretch) No image augmentation techniques were applied.