首页YOLOV8分类命令

YOLOV8分类命令

时间: 2025-04-29 18:46:53 浏览: 17

### YOLOv8 Classification Command Example For classification tasks using YOLOv8, the configuration and command structure differ slightly from detection tasks. The provided examples focus on object detection with specific configurations for models like `yolov8_DynamicHead`[^1] and `yolov8_MobileNetV3`[^2]. However, adapting these commands to a classification task involves specifying an appropriate model designed or modified for classification purposes. A typical command line setup for training a YOLOv8 model on a classification task might look as follows: ```bash yolo task=classify mode=train model=path/to/classification_model.yaml data=cfg/datasets/your_classification_dataset.yaml epochs=100 batch=16 device=cpu project=yolov8_classify ``` In this context: - Replace `path/to/classification_model.yaml` with the path to your chosen architecture file configured specifically for classification. - Use `your_classification_dataset.yaml`, which should define paths to image folders and other dataset-specific parameters suitable for classification rather than detection datasets such as COCO128 used in detection examples. The introduction of components like BiFPN enhances feature extraction capabilities but is more relevant to improving performance in detection scenarios by facilitating better multi-scale feature fusion across different levels {P3-P7}[^3], whereas classification may not directly benefit from it unless part of transfer learning strategies where pre-trained weights are utilized.

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