退购1.1定位算法

ultralytics/models/README.md

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+## Models
+
+Welcome to the Ultralytics Models directory! Here you will find a wide variety of pre-configured model configuration
+files (`*.yaml`s) that can be used to create custom YOLO models. The models in this directory have been expertly crafted
+and fine-tuned by the Ultralytics team to provide the best performance for a wide range of object detection and image
+segmentation tasks.
+
+These model configurations cover a wide range of scenarios, from simple object detection to more complex tasks like
+instance segmentation and object tracking. They are also designed to run efficiently on a variety of hardware platforms,
+from CPUs to GPUs. Whether you are a seasoned machine learning practitioner or just getting started with YOLO, this
+directory provides a great starting point for your custom model development needs.
+
+To get started, simply browse through the models in this directory and find one that best suits your needs. Once you've
+selected a model, you can use the provided `*.yaml` file to train and deploy your custom YOLO model with ease. See full
+details at the Ultralytics [Docs](https://docs.ultralytics.com/models), and if you need help or have any questions, feel free
+to reach out to the Ultralytics team for support. So, don't wait, start creating your custom YOLO model now!
+
+### Usage
+
+Model `*.yaml` files may be used directly in the Command Line Interface (CLI) with a `yolo` command:
+
+```bash
+yolo task=detect mode=train model=yolov8n.yaml data=coco128.yaml epochs=100
+```
+
+They may also be used directly in a Python environment, and accepts the same
+[arguments](https://docs.ultralytics.com/usage/cfg/) as in the CLI example above:
+
+```python
+from ultralytics import YOLO
+
+model = YOLO("model.yaml")  # build a YOLOv8n model from scratch
+# YOLO("model.pt")  use pre-trained model if available
+model.info()  # display model information
+model.train(data="coco128.yaml", epochs=100)  # train the model
+```
+
+## Pre-trained Model Architectures
+
+Ultralytics supports many model architectures. Visit https://docs.ultralytics.com/models to view detailed information
+and usage. Any of these models can be used by loading their configs or pretrained checkpoints if available.
+
+## Contributing New Models
+
+If you've developed a new model architecture or have improvements for existing models that you'd like to contribute to the Ultralytics community, please submit your contribution in a new Pull Request. For more details, visit our [Contributing Guide](https://docs.ultralytics.com/help/contributing).