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👋 Hello @playground, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution.
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Python>=3.7.0 with all requirements.txt installed including PyTorch>=1.7. To get started:
git clone https://github.com/ultralytics/yolov5 # clone
cd yolov5
pip install -r requirements.txt # install
YOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
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We're excited to announce the launch of our latest state-of-the-art (SOTA) object detection model for 2023 - YOLOv8 🚀!
Designed to be fast, accurate, and easy to use, YOLOv8 is an ideal choice for a wide range of object detection, image segmentation and image classification tasks. With YOLOv8, you'll be able to quickly and accurately detect objects in real-time, streamline your workflows, and achieve new levels of accuracy in your projects.
Check out our YOLOv8 Docs for details and get started with:
pip install ultralytics
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Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!
Thank you for your contributions to YOLOv5 🚀 and Vision AI ⭐!
@playground hey there! To load a YOLOv3 model and run predictions in your Node.js backend using tfjs-node, you can convert your YOLOv3 model to TensorFlow.js format using the tfjs-converter tool. Once converted, you can utilize tfjs-node to load the model and make predictions in your Node.js environment. For detailed steps, you can refer to the TensorFlow.js documentation and the YOLOv5 documentation on Ultralytics. Let me know if you need further assistance!
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I have trained a yolov3 model, how to load this model and run prediction in my node backend with tfjs-node? Thank you.
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