@ -44,7 +44,7 @@ To request an Enterprise License please complete the form at [Ultralytics Licens
</div>
</div>
## Documentation
## <divalign="center">Documentation</div>
See below for a quickstart installation and usage example, and see the [YOLOv8 Docs](https://docs.ultralytics.com) for full documentation on training, validation, prediction and deployment.
@ -98,7 +98,7 @@ See YOLOv8 [Python Docs](https://docs.ultralytics.com/usage/python) for more exa
</details>
## Models
## <divalign="center">Models</div>
YOLOv8 [Detect](https://docs.ultralytics.com/tasks/detect), [Segment](https://docs.ultralytics.com/tasks/segment) and [Pose](https://docs.ultralytics.com/tasks/pose) models pretrained on the [COCO](https://docs.ultralytics.com/datasets/detect/coco) dataset are available here, as well as YOLOv8 [Classify](https://docs.ultralytics.com/tasks/classify) models pretrained on the [ImageNet](https://docs.ultralytics.com/datasets/classify/imagenet) dataset. [Track](https://docs.ultralytics.com/modes/track) mode is available for all Detect, Segment and Pose models.
@ -203,7 +203,7 @@ See [Classification Docs](https://docs.ultralytics.com/tasks/classify/) for usag
</details>
## Integrations
## <divalign="center">Integrations</div>
Our key integrations with leading AI platforms extend the functionality of Ultralytics' offerings, enhancing tasks like dataset labeling, training, visualization, and model management. Discover how Ultralytics, in collaboration with [Roboflow](https://roboflow.com/?ref=ultralytics), ClearML, [Comet](https://bit.ly/yolov8-readme-comet), Neural Magic and [OpenVINO](https://docs.ultralytics.com/integrations/openvino), can optimize your AI workflow.
@ -231,14 +231,14 @@ Our key integrations with leading AI platforms extend the functionality of Ultra
| Label and export your custom datasets directly to YOLOv8 for training with [Roboflow](https://roboflow.com/?ref=ultralytics) | Automatically track, visualize and even remotely train YOLOv8 using [ClearML](https://cutt.ly/yolov5-readme-clearml) (open-source!) | Free forever, [Comet](https://bit.ly/yolov8-readme-comet) lets you save YOLOv8 models, resume training, and interactively visualize and debug predictions | Run YOLOv8 inference up to 6x faster with [Neural Magic DeepSparse](https://bit.ly/yolov5-neuralmagic) |
## Ultralytics HUB
## <divalign="center">Ultralytics HUB</div>
Experience seamless AI with [Ultralytics HUB](https://bit.ly/ultralytics_hub) ⭐, the all-in-one solution for data visualization, YOLOv5 and YOLOv8 🚀 model training and deployment, without any coding. Transform images into actionable insights and bring your AI visions to life with ease using our cutting-edge platform and user-friendly [Ultralytics App](https://ultralytics.com/app_install). Start your journey for **Free** now!
We love your input! YOLOv5 and YOLOv8 would not be possible without help from our community. Please see our [Contributing Guide](https://docs.ultralytics.com/help/contributing) to get started, and fill out our [Survey](https://ultralytics.com/survey?utm_source=github&utm_medium=social&utm_campaign=Survey) to send us feedback on your experience. Thank you 🙏 to all our contributors!
@ -247,14 +247,14 @@ We love your input! YOLOv5 and YOLOv8 would not be possible without help from ou
Ultralytics offers two licensing options to accommodate diverse use cases:
- **AGPL-3.0 License**: This [OSI-approved](https://opensource.org/licenses/) open-source license is ideal for students and enthusiasts, promoting open collaboration and knowledge sharing. See the [LICENSE](https://github.com/ultralytics/ultralytics/blob/main/LICENSE) file for more details.
- **Enterprise License**: Designed for commercial use, this license permits seamless integration of Ultralytics software and AI models into commercial goods and services, bypassing the open-source requirements of AGPL-3.0. If your scenario involves embedding our solutions into a commercial offering, reach out through [Ultralytics Licensing](https://ultralytics.com/license).
## Contact
## <divalign="center">Contact</div>
For Ultralytics bug reports and feature requests please visit [GitHub Issues](https://github.com/ultralytics/ultralytics/issues), and join our [Discord](https://ultralytics.com/discord) community for questions and discussions!
Description: A comprehensive guide on various performance metrics related to YOLOv8, their significance, and how to interpret them.
description: A comprehensive guide on various performance metrics related to YOLOv8, their significance, and how to interpret them.
keywords: YOLOv8, Performance metrics, Object detection, Intersection over Union (IoU), Average Precision (AP), Mean Average Precision (mAP), Precision, Recall, Validation mode, Ultralytics
@ -94,11 +94,11 @@ The YOLO-NAS models are primarily designed for object detection tasks. You can d
The YOLO-NAS models support both inference and validation modes, allowing you to predict and validate results with ease. Training mode, however, is currently not supported.
| Mode | Supported |
|------------|--------------------|
| Inference | :heavy_check_mark: |
| Validation | :heavy_check_mark: |
| Training | :x: |
| Mode | Supported |
|------------|-----------|
| Inference | ✅ |
| Validation | ✅ |
| Training | ❌ |
Harness the power of the YOLO-NAS models to drive your object detection tasks to new heights of performance and speed.
@ -148,12 +148,13 @@ The Ultralytics command line interface (CLI) allows for simple single-line comma
Ultralytics `yolo` commands use the following syntax:
```bash
yolo TASK MODE ARGS
Where TASK (optional) is one of [detect, segment, classify]
MODE (required) is one of [train, val, predict, export, track]
ARGS (optional) are any number of custom 'arg=value' pairs like 'imgsz=320' that override defaults.
```
See all ARGS in the full [Configuration Guide](usage/cfg.md) or with `yolo cfg`
- `TASK` (optional) is one of ([detect](tasks/detect.md), [segment](tasks/segment.md), [classify](tasks/classify.md), [pose](tasks/pose.md))
- `MODE` (required) is one of ([train](modes/train.md), [val](modes/val.md), [predict](modes/predict.md), [export](modes/export.md), [track](modes/track.md))
- `ARGS` (optional) are `arg=value` pairs like `imgsz=640` that override defaults.
See all `ARGS` in the full [Configuration Guide](usage/cfg.md) or with the `yolo cfg` CLI command.
=== "Train"
@ -197,11 +198,12 @@ The Ultralytics command line interface (CLI) allows for simple single-line comma
!!! warning "Warning"
Arguments must be passed as `arg=val` pairs, split by an equals `=` sign and delimited by spaces ` `between pairs. Do not use `--` argument prefixes or commas `,` between arguments.
Arguments must be passed as `arg=val` pairs, split by an equals `=` sign and delimited by spaces between pairs. Do not use `--` argument prefixes or commas `,` between arguments.
Glenn Jocher
1 year ago
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GitHub