ultralytics 8.0.142 add OpenVINO docs (ultralytics#3624)

Co-authored-by: Adrian Boguszewski <[email protected]>

.github/workflows/ci.yaml

@@ -125,16 +125,16 @@ jobs:
           pip list
       - name: Benchmark DetectionModel
         shell: bash
-        run: yolo benchmark model='path with spaces/${{ matrix.model }}.pt' imgsz=160, verbose=0.26
+        run: yolo benchmark model='path with spaces/${{ matrix.model }}.pt' imgsz=160 verbose=0.26
       - name: Benchmark SegmentationModel
         shell: bash
-        run: yolo benchmark model='path with spaces/${{ matrix.model }}-seg.pt' imgsz=160, verbose=0.30
+        run: yolo benchmark model='path with spaces/${{ matrix.model }}-seg.pt' imgsz=160 verbose=0.30
       - name: Benchmark ClassificationModel
         shell: bash
-        run: yolo benchmark model='path with spaces/${{ matrix.model }}-cls.pt' imgsz=160, verbose=0.36
+        run: yolo benchmark model='path with spaces/${{ matrix.model }}-cls.pt' imgsz=160 verbose=0.36
       - name: Benchmark PoseModel
         shell: bash
-        run: yolo benchmark model='path with spaces/${{ matrix.model }}-pose.pt' imgsz=160, verbose=0.17
+        run: yolo benchmark model='path with spaces/${{ matrix.model }}-pose.pt' imgsz=160 verbose=0.17
       - name: Benchmark Summary
         run: |
           cat benchmarks.log

.github/workflows/docker.yaml

@@ -74,7 +74,8 @@ jobs:
           docker run ultralytics/ultralytics:${{ matrix.tags }} /bin/bash -c "pip install pytest && pytest tests"
 
       - name: Run Benchmarks
-        if: (github.event_name == 'push' || github.event.inputs.dockerfile == matrix.dockerfile) && matrix.platforms == 'linux/amd64'  # arm64 images not supported on GitHub CI runners
+        # WARNING: Dockerfile (GPU) error on TF.js export 'module 'numpy' has no attribute 'object'.
+        if: (github.event_name == 'push' || github.event.inputs.dockerfile == matrix.dockerfile) && matrix.platforms == 'linux/amd64' && matrix.dockerfile != 'Dockerfile'  # arm64 images not supported on GitHub CI runners
         run: |
           docker run ultralytics/ultralytics:${{ matrix.tags }} yolo benchmark model=yolov8n.pt imgsz=160 verbose=0.26
 

README.md

@@ -192,6 +192,8 @@ See [Pose Docs](https://docs.ultralytics.com/tasks/pose) for usage examples with
 
 ## <div align="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.
+
 <br>
 <a href="https://bit.ly/ultralytics_hub" target="_blank">
 <img width="100%" src="https://github.com/ultralytics/assets/raw/main/yolov8/banner-integrations.png"></a>

README.zh-CN.md

@@ -191,6 +191,8 @@ success = model.export(format="onnx")  # 将模型导出为 ONNX 格式
 
 ## <div align="center">集成</div>
 
+我们与领先的AI平台的关键整合扩展了Ultralytics产品的功能，增强了数据集标签化、训练、可视化和模型管理等任务。探索Ultralytics如何与[Roboflow](https://roboflow.com/?ref=ultralytics)、ClearML、[Comet](https://bit.ly/yolov8-readme-comet)、Neural Magic以及[OpenVINO](https://docs.ultralytics.com/integrations/openvino)合作，优化您的AI工作流程。
+
 <br>
 <a href="https://bit.ly/ultralytics_hub" target="_blank">
 <img width="100%" src="https://github.com/ultralytics/assets/raw/main/yolov8/banner-integrations.png"></a>

docs/integrations/index.md

@@ -0,0 +1,61 @@
+---
+comments: true
+description: Explore Ultralytics integrations with tools for dataset management, model optimization, ML workflows automation, experiment tracking, version control, and more. Learn about our support for various model export formats for deployment.
+keywords: Ultralytics integrations, Roboflow, Neural Magic, ClearML, Comet ML, DVC, Ultralytics HUB, MLFlow, Neptune, Ray Tune, TensorBoard, W&B, model export formats, PyTorch, TorchScript, ONNX, OpenVINO, TensorRT, CoreML, TF SavedModel, TF GraphDef, TF Lite, TF Edge TPU, TF.js, PaddlePaddle, NCNN
+---
+
+# Ultralytics Integrations
+
+Welcome to the Ultralytics Integrations page! This page provides an overview of our partnerships with various tools and platforms, designed to streamline your machine learning workflows, enhance dataset management, simplify model training, and facilitate efficient deployment.
+
+<img width="1024" src="https://github.com/ultralytics/assets/raw/main/yolov8/banner-integrations.png">
+
+## Datasets Integrations
+
+- [Roboflow](https://roboflow.com/): Facilitate seamless dataset management for Ultralytics models, offering robust annotation, preprocessing, and augmentation capabilities.
+
+## Training Integrations
+
+- [Comet ML](https://www.comet.ml/): Enhance your model development with Ultralytics by tracking, comparing, and optimizing your machine learning experiments.
+
+- [ClearML](https://clear.ml/): Automate your Ultralytics ML workflows, monitor experiments, and foster team collaboration.
+
+- [DVC](https://dvc.org/): Implement version control for your Ultralytics machine learning projects, synchronizing data, code, and models effectively.
+
+- [Ultralytics HUB](https://hub.ultralytics.com): Access and contribute to a community of pre-trained Ultralytics models.
+
+- [MLFlow](https://mlflow.org/): Streamline the entire ML lifecycle of Ultralytics models, from experimentation and reproducibility to deployment.
+
+- [Neptune](https://neptune.ai/): Maintain a comprehensive log of your ML experiments with Ultralytics in this metadata store designed for MLOps.
+
+- [Ray Tune](ray-tune.md): Optimize the hyperparameters of your Ultralytics models at any scale.
+
+- [TensorBoard](https://tensorboard.dev/): Visualize your Ultralytics ML workflows, monitor model metrics, and foster team collaboration.
+
+- [Weights & Biases (W&B)](https://wandb.ai/site): Monitor experiments, visualize metrics, and foster reproducibility and collaboration on Ultralytics projects.
+
+## Deployment Integrations
+
+- [Neural Magic](https://neuralmagic.com/): Leverage Quantization Aware Training (QAT) and pruning techniques to optimize Ultralytics models for superior performance and leaner size.
+
+### Export Formats
+
+We also support a variety of model export formats for deployment in different environments. Here are the available formats:
+
+| Format                                                             | `format` Argument | Model                     | Metadata | Arguments                                           |
+|--------------------------------------------------------------------|-------------------|---------------------------|----------|-----------------------------------------------------|
+| [PyTorch](https://pytorch.org/)                                    | -                 | `yolov8n.pt`              | ✅        | -                                                   |
+| [TorchScript](https://pytorch.org/docs/stable/jit.html)            | `torchscript`     | `yolov8n.torchscript`     | ✅        | `imgsz`, `optimize`                                 |
+| [ONNX](https://onnx.ai/)                                           | `onnx`            | `yolov8n.onnx`            | ✅        | `imgsz`, `half`, `dynamic`, `simplify`, `opset`     |
+| [OpenVINO](/integrations/openvino.md)                              | `openvino`        | `yolov8n_openvino_model/` | ✅        | `imgsz`, `half`                                     |
+| [TensorRT](https://developer.nvidia.com/tensorrt)                  | `engine`          | `yolov8n.engine`          | ✅        | `imgsz`, `half`, `dynamic`, `simplify`, `workspace` |
+| [CoreML](https://github.com/apple/coremltools)                     | `coreml`          | `yolov8n.mlmodel`         | ✅        | `imgsz`, `half`, `int8`, `nms`                      |
+| [TF SavedModel](https://www.tensorflow.org/guide/saved_model)      | `saved_model`     | `yolov8n_saved_model/`    | ✅        | `imgsz`, `keras`                                    |
+| [TF GraphDef](https://www.tensorflow.org/api_docs/python/tf/Graph) | `pb`              | `yolov8n.pb`              | ❌        | `imgsz`                                             |
+| [TF Lite](https://www.tensorflow.org/lite)                         | `tflite`          | `yolov8n.tflite`          | ✅        | `imgsz`, `half`, `int8`                             |
+| [TF Edge TPU](https://coral.ai/docs/edgetpu/models-intro/)         | `edgetpu`         | `yolov8n_edgetpu.tflite`  | ✅        | `imgsz`                                             |
+| [TF.js](https://www.tensorflow.org/js)                             | `tfjs`            | `yolov8n_web_model/`      | ✅        | `imgsz`                                             |
+| [PaddlePaddle](https://github.com/PaddlePaddle)                    | `paddle`          | `yolov8n_paddle_model/`   | ✅        | `imgsz`                                             |
+| [NCNN](https://github.com/Tencent/ncnn)                            | `ncnn`            | `yolov8n_ncnn_model/`     | ✅        | `imgsz`, `half`                                     |
+
+Explore the links to learn more about each integration and how to get the most out of them with Ultralytics.