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ultralytics 8.0.32 HUB and TensorFlow fixes (#870)

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# Ultralytics HUB
<div align="center">
<a href="https://hub.ultralytics.com" target="_blank">
<img width="1024" src="https://github.com/ultralytics/assets/raw/main/im/ultralytics-hub.png"></a>
<a href="https://bit.ly/ultralytics_hub" target="_blank">
<img width="100%" src="https://github.com/ultralytics/assets/raw/main/im/ultralytics-hub.png"></a>
<br>
<br>
<div align="center">
<a href="https://github.com/ultralytics" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
<a href="https://www.linkedin.com/company/ultralytics" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="2%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
<a href="https://twitter.com/ultralytics" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-twitter.png" width="2%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
<a href="https://www.producthunt.com/@glenn_jocher" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-producthunt.png" width="2%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
<a href="https://youtube.com/ultralytics" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-youtube.png" width="2%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
<a href="https://www.facebook.com/ultralytics" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-facebook.png" width="2%" alt="" /></a>
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
<a href="https://www.instagram.com/ultralytics/" style="text-decoration:none;">
<img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-instagram.png" width="2%" alt="" /></a>
<br>
<br>
<a href="https://github.com/ultralytics/hub/actions/workflows/ci.yaml">
<img src="https://github.com/ultralytics/hub/actions/workflows/ci.yaml/badge.svg" alt="CI CPU"></a>
<a href="https://colab.research.google.com/github/ultralytics/hub/blob/master/hub.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>
</div>
<br>
[Ultralytics HUB](https://hub.ultralytics.com) is a new no-code online tool developed
by [Ultralytics](https://ultralytics.com), the creators of the popular [YOLOv5](https://github.com/ultralytics/yolov5)
object detection and image segmentation models. With Ultralytics HUB, users can easily train and deploy YOLOv5 models
object detection and image segmentation models. With Ultralytics HUB, users can easily train and deploy YOLO models
without any coding or technical expertise.
Ultralytics HUB is designed to be user-friendly and intuitive, with a drag-and-drop interface that allows users to
easily upload their data and select their model configurations. It also offers a range of pre-trained models and
templates to choose from, making it easy for users to get started with training their own models. Once a model is
trained, it can be easily deployed and used for real-time object detection and image segmentation tasks. Overall,
Ultralytics HUB is an essential tool for anyone looking to use YOLOv5 for their object detection and image segmentation
Ultralytics HUB is an essential tool for anyone looking to use YOLO for their object detection and image segmentation
projects.
**[Get started now](https://hub.ultralytics.com)** and experience the power and simplicity of Ultralytics HUB for
yourself. Sign up for a free account and
start building, training, and deploying YOLOv5 and YOLOv8 models today.
yourself. Sign up for a free account and start building, training, and deploying YOLOv5 and YOLOv8 models today.
## 1. Upload a Dataset
@ -44,7 +68,9 @@ zip -r coco6.zip coco6
The example [coco6.zip](https://github.com/ultralytics/hub/blob/master/coco6.zip) dataset in this repository can be
downloaded and unzipped to see exactly how to structure your custom dataset.
<p align="center"><img width="80%" src="https://user-images.githubusercontent.com/26833433/201424843-20fa081b-ad4b-4d6c-a095-e810775908d8.png" title="COCO6" /></p>
<p align="center">
<img width="80%" src="https://user-images.githubusercontent.com/26833433/201424843-20fa081b-ad4b-4d6c-a095-e810775908d8.png" title="COCO6" />
</p>
The dataset YAML is the same standard YOLOv5 YAML format. See
the [YOLOv5 Train Custom Data tutorial](https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data) for full details.
@ -68,20 +94,21 @@ names:
After zipping your dataset, sign in to [Ultralytics HUB](https://bit.ly/ultralytics_hub) and click the Datasets tab.
Click 'Upload Dataset' to upload, scan and visualize your new dataset before training new YOLOv5 models on it!
<img width="100%" alt="HUB Dataset Upload" src="https://user-images.githubusercontent.com/26833433/198611715-540c9856-49d7-4069-a2fd-7c9eb70e772e.png">
<img width="100%" alt="HUB Dataset Upload" src="https://user-images.githubusercontent.com/26833433/216763338-9a8812c8-a4e5-4362-8102-40dad7818396.png">
## 2. Train a Model
Connect to the Ultralytics HUB notebook and use your model API key to begin
training! <a href="https://colab.research.google.com/github/ultralytics/hub/blob/master/hub.ipynb" target="_blank"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>
Connect to the Ultralytics HUB notebook and use your model API key to begin training!
<a href="https://colab.research.google.com/github/ultralytics/hub/blob/master/hub.ipynb" target="_blank">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>
## 3. Deploy to Real World
Export your model to 13 different formats, including TensorFlow, ONNX, OpenVINO, CoreML, Paddle and many others. Run
models directly on your mobile device by downloading the [Ultralytics App](https://ultralytics.com/app_install)!
<a href="https://ultralytics.com/app_install" target="_blank">
<img width="100%" alt="Ultralytics mobile app" src="https://github.com/ultralytics/assets/raw/main/im/ultralytics-app.png"></a>
models directly on your [iOS](https://apps.apple.com/xk/app/ultralytics/id1583935240) or
[Android](https://play.google.com/store/apps/details?id=com.ultralytics.ultralytics_app) mobile device by downloading
the [Ultralytics App](https://ultralytics.com/app_install)!
## ❓ Issues