Add FAQs to Docs Datasets and Help sections (#14211)
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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@ -59,3 +59,29 @@ In the sunburst graphic below, the innermost circle is the entire project, movin
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<a href="https://codecov.io/github/ultralytics/ultralytics">
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<img src="https://codecov.io/gh/ultralytics/ultralytics/branch/main/graphs/sunburst.svg?token=HHW7IIVFVY" alt="Ultralytics Codecov Image">
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</a>
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## FAQ
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### What is Continuous Integration (CI) in Ultralytics?
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Continuous Integration (CI) in Ultralytics involves automatically integrating and testing code changes to ensure high-quality standards. Our CI setup includes running [unit tests, linting checks, and comprehensive tests](https://github.com/ultralytics/ultralytics/actions/workflows/ci.yaml). Additionally, we perform [Docker deployment](https://github.com/ultralytics/ultralytics/actions/workflows/docker.yaml), [broken link checks](https://github.com/ultralytics/ultralytics/actions/workflows/links.yml), [CodeQL analysis](https://github.com/ultralytics/ultralytics/actions/workflows/codeql.yaml) for security vulnerabilities, and [PyPI publishing](https://github.com/ultralytics/ultralytics/actions/workflows/publish.yml) to package and distribute our software.
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### How does Ultralytics check for broken links in documentation and code?
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Ultralytics uses a specific CI action to [check for broken links](https://github.com/ultralytics/ultralytics/actions/workflows/links.yml) within our markdown and HTML files. This helps maintain the integrity of our documentation by scanning and identifying dead or broken links, ensuring that users always have access to accurate and live resources.
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### Why is CodeQL analysis important for Ultralytics' codebase?
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[CodeQL analysis](https://github.com/ultralytics/ultralytics/actions/workflows/codeql.yaml) is crucial for Ultralytics as it performs semantic code analysis to find potential security vulnerabilities and maintain high-quality standards. With CodeQL, we can proactively identify and mitigate risks in our code, helping us deliver robust and secure software solutions.
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### How does Ultralytics utilize Docker for deployment?
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Ultralytics employs Docker to validate the deployment of our projects through a dedicated CI action. This process ensures that our [Dockerfile and associated scripts](https://github.com/ultralytics/ultralytics/actions/workflows/docker.yaml) are functioning correctly, allowing for consistent and reproducible deployment environments which are critical for scalable and reliable AI solutions.
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### What is the role of automated PyPI publishing in Ultralytics?
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Automated [PyPI publishing](https://github.com/ultralytics/ultralytics/actions/workflows/publish.yml) ensures that our projects can be packaged and published without errors. This step is essential for distributing Ultralytics' Python packages, allowing users to easily install and use our tools via the Python Package Index (PyPI).
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### How does Ultralytics measure code coverage and why is it important?
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Ultralytics measures code coverage by integrating with [Codecov](https://codecov.io/github/ultralytics/ultralytics), providing insights into how much of the codebase is executed during tests. High code coverage can indicate well-tested code, helping to uncover untested areas that might be prone to bugs. Detailed code coverage metrics can be explored via badges displayed on our main repositories or directly on [Codecov](https://codecov.io/gh/ultralytics/ultralytics).
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@ -26,3 +26,25 @@ You agree that the following terms apply to all of your past, present and future
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**Disputes.** This Agreement shall be governed by and construed in accordance with the laws of the State of New York, United States of America, without giving effect to its principles or rules regarding conflicts of laws, other than such principles directing application of New York law. The parties hereby submit to venue in, and jurisdiction of the courts located in New York, New York for purposes relating to this Agreement. In the event that any of the provisions of this Agreement shall be held by a court or other tribunal of competent jurisdiction to be unenforceable, the remaining portions hereof shall remain in full force and effect.
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**Assignment.** You agree that Ultralytics may assign this Agreement, and all of its rights, obligations and licenses hereunder.
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## FAQ
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### What is the purpose of the Ultralytics Individual Contributor License Agreement?
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The Ultralytics Individual Contributor License Agreement (ICLA) governs the terms under which you contribute to Ultralytics' open-source projects. It sets out the rights and obligations related to your contributions, including granting copyright and patent licenses, waiving moral rights, and disclosing any third-party content.
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### Why do I need to agree to the Copyright License in the ICLA?
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Agreeing to the Copyright License allows Ultralytics to use and distribute your contributions, including making derivative works. This ensures that your contributions can be integrated into Ultralytics projects and shared with the community, fostering collaboration and software development.
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### How does the Patent License benefit both contributors and Ultralytics?
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The Patent License grants Ultralytics the rights to use, make, and sell contributions covered by your patents, which is crucial for product development and commercialization. In return, it allows your patented innovations to be more widely used and recognized, promoting innovation within the community.
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### What should I do if my contribution contains third-party content?
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If your contribution includes third-party content or you are aware of any third-party intellectual property rights, you must provide full details of such content and rights when submitting your contribution. This includes identifying the third-party content, its author, and the applicable license terms. For more information on third-party content, refer to the Third Party Content/Rights section of the Agreement.
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### What happens if Ultralytics does not use my contributions?
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Ultralytics is not obligated to use or incorporate your contributions into any projects. The decision to use or integrate contributions is at Ultralytics' sole discretion. This means that while your contributions are valuable, they may not always align with the project's current needs or directions. For further details, see the No Obligation section.
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@ -8,7 +8,9 @@ keywords: Ultralytics, YOLO, FAQ, object detection, hardware requirements, fine-
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This FAQ section addresses some common questions and issues users might encounter while working with [Ultralytics](https://ultralytics.com) YOLO repositories.
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## 1. What is Ultralytics and what does it offer?
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## FAQ
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### 1. What is Ultralytics and what does it offer?
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Ultralytics is a computer vision AI company that develops and maintains state-of-the-art object detection and image segmentation models, primarily focusing on the YOLO (You Only Look Once) family of models. Ultralytics offers:
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@ -18,7 +20,7 @@ Ultralytics is a computer vision AI company that develops and maintains state-of
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- [Tools for training, testing, and deploying models](https://docs.ultralytics.com/modes/)
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- [Extensive documentation and community support](https://docs.ultralytics.com/)
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## 2. How do I install the Ultralytics package?
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### 2. How do I install the Ultralytics package?
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To install the Ultralytics package, you can use pip, the Python package manager. Open a terminal or command prompt and run:
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@ -34,7 +36,7 @@ pip install git+https://github.com/ultralytics/ultralytics.git
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For more details, refer to the [quickstart guide](https://docs.ultralytics.com/quickstart/).
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## 3. What are the system requirements for running Ultralytics models?
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### 3. What are the system requirements for running Ultralytics models?
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Minimum requirements:
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@ -52,7 +54,7 @@ Recommended:
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For more information, visit [YOLO Common Issues](https://docs.ultralytics.com/guides/yolo-common-issues/).
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## 4. How can I train a custom YOLOv8 model on my own dataset?
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### 4. How can I train a custom YOLOv8 model on my own dataset?
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To train a custom YOLOv8 model:
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@ -73,7 +75,7 @@ results = model.train(data="path/to/your/data.yaml", epochs=100, imgsz=640)
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For detailed instructions, refer to the [training guide](https://docs.ultralytics.com/modes/train/).
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## 5. What pretrained models are available in Ultralytics?
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### 5. What pretrained models are available in Ultralytics?
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Ultralytics offers a range of pretrained YOLOv8 models for various tasks:
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@ -83,7 +85,7 @@ Ultralytics offers a range of pretrained YOLOv8 models for various tasks:
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These models vary in size and complexity, offering different trade-offs between speed and accuracy. Learn more about [pretrained models](https://docs.ultralytics.com/models/yolov8/).
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## 6. How do I perform inference using a trained Ultralytics model?
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### 6. How do I perform inference using a trained Ultralytics model?
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To perform inference with a trained model:
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@ -105,7 +107,7 @@ for r in results:
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For more details, visit the [prediction guide](https://docs.ultralytics.com/modes/predict/).
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## 7. Can Ultralytics models be deployed on edge devices or in production environments?
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### 7. Can Ultralytics models be deployed on edge devices or in production environments?
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Yes, Ultralytics models can be deployed on various platforms:
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@ -116,7 +118,7 @@ Yes, Ultralytics models can be deployed on various platforms:
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Ultralytics provides export functions to convert models to various formats for deployment. Learn more about [deployment options](https://docs.ultralytics.com/guides/model-deployment-options/).
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## 8. What's the difference between YOLOv5 and YOLOv8?
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### 8. What's the difference between YOLOv5 and YOLOv8?
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Key differences include:
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@ -128,7 +130,7 @@ Key differences include:
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For a detailed comparison, visit [YOLOv5 vs YOLOv8](https://www.ultralytics.com/yolo).
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## 9. How can I contribute to the Ultralytics open-source project?
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### 9. How can I contribute to the Ultralytics open-source project?
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To contribute:
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@ -140,7 +142,79 @@ To contribute:
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You can also contribute by reporting bugs, suggesting features, or improving documentation. Refer to the [contributing guide](https://docs.ultralytics.com/help/contributing/).
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## 10. Where can I find examples and tutorials for using Ultralytics?
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### 10. How do I install the Ultralytics package in Python?
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To install the Ultralytics package in Python, you can use pip by running the following command in your terminal or command prompt:
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```bash
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pip install ultralytics
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```
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If you want the latest development version, you can install it directly from the GitHub repository:
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```bash
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pip install git+https://github.com/ultralytics/ultralytics.git
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```
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For additional instructions and details, you can refer to the [quickstart guide](https://docs.ultralytics.com/quickstart/).
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### 11. What are the main features of Ultralytics YOLO?
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Ultralytics YOLO offers several advanced features to enhance object detection and image segmentation tasks:
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- **Real-Time Detection:** Efficient detection and classification of objects in real-time.
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- **Pre-Trained Models:** Access to a variety of pretrained models that balance speed and accuracy ([Pretrained Models](https://docs.ultralytics.com/models/yolov8/)).
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- **Custom Training:** Easily fine-tune models on custom datasets ([Training Guide](https://docs.ultralytics.com/modes/train/)).
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- **Wide Deployment Options:** Models can be exported to various formats like TensorRT, ONNX, and CoreML for deployment on different platforms ([Deployment Options](https://docs.ultralytics.com/guides/model-deployment-options/)).
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- **Extensive Documentation:** Comprehensive documentation and community support to help users at all levels ([Documentation](https://docs.ultralytics.com/)).
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For further information, you can explore the [YOLO models page](https://docs.ultralytics.com/models/yolov8/).
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### 12. How can I improve the performance of my YOLO model?
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Improving the performance of your YOLO model can be achieved through several techniques:
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1. **Hyperparameter Tuning:** Experiment with different hyperparameters to optimize model performance ([Hyperparameter Tuning Guide](https://docs.ultralytics.com/guides/hyperparameter-tuning/)).
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2. **Data Augmentation:** Use techniques like flip, scale, rotate, and color adjustments to enhance your training dataset.
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3. **Transfer Learning:** Start with a pre-trained model and fine-tune it on your specific dataset ([Train YOLOv8](https://docs.ultralytics.com/modes/train/)).
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4. **Export to Efficient Formats:** Export your model to optimized formats like TensorRT or ONNX for faster inference ([Export](../modes/export.md)).
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5. **Benchmarking:** Use the benchmarking tools available to measure and improve the inference speed and accuracy ([Benchmark Mode](https://docs.ultralytics.com/modes/benchmark/)).
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### 13. Can I deploy Ultralytics YOLO models on mobile and edge devices?
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Yes, you can deploy Ultralytics YOLO models on mobile and edge devices by converting them to supported formats. Here are some options:
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- **Mobile:** Convert models to TFLite or CoreML for integration into Android or iOS apps ([TFLite Integration Guide](https://docs.ultralytics.com/integrations/tflite/) and [CoreML Integration Guide](https://docs.ultralytics.com/integrations/coreml/)).
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- **Edge Devices:** Use TensorRT or ONNX for optimized inference on devices like NVIDIA Jetson or other edge hardware ([Edge TPU Integration Guide](https://docs.ultralytics.com/integrations/edge-tpu/)).
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For detailed instructions on different deployment options, visit the [deployment options guide](https://docs.ultralytics.com/guides/model-deployment-options/).
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### 14. How can I perform inference using a trained Ultralytics YOLO model?
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To perform inference using a trained Ultralytics YOLO model, follow these steps:
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1. **Load the Model:**
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```python
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from ultralytics import YOLO
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model = YOLO("path/to/your/model.pt")
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```
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2. **Run Inference:**
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```python
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results = model("path/to/image.jpg")
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for r in results:
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print(r.boxes) # print bounding box predictions
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print(r.masks) # print mask predictions
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print(r.probs) # print class probabilities
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```
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For more detailed instructions, check out the [prediction guide](https://docs.ultralytics.com/modes/predict/).
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### 15. Where can I find examples and tutorials for using Ultralytics?
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You can find examples and tutorials in several places:
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@ -1,6 +1,6 @@
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---
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comments: true
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description: Join our welcoming community! Learn about Ultralytics's Code of Conduct to ensure a harassment-free experience for all participants.
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description: Join our welcoming community! Learn about the Ultralytics Code of Conduct to ensure a harassment-free experience for all participants.
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keywords: Ultralytics, Contributor Covenant, Code of Conduct, community guidelines, harassment-free, inclusive community, diversity, enforcement policy
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---
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@ -83,3 +83,27 @@ Community Impact Guidelines were inspired by [Mozilla's code of conduct enforcem
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For answers to common questions about this code of conduct, see the FAQ at https://www.contributor-covenant.org/faq. Translations are available at https://www.contributor-covenant.org/translations.
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[homepage]: https://www.contributor-covenant.org
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## FAQ
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### What is the Ultralytics Contributor Covenant Code of Conduct?
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The Ultralytics Contributor Covenant Code of Conduct aims to create a harassment-free experience for everyone participating in the Ultralytics community. It applies to all community interactions, including online and offline activities. The code details expected behaviors, unacceptable behaviors, and the enforcement responsibilities of community leaders. For more detailed information, see the [Enforcement Responsibilities](#enforcement-responsibilities) section.
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### How does the enforcement process work for the Ultralytics Code of Conduct?
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Enforcement of the Ultralytics Code of Conduct is managed by community leaders who can take appropriate action in response to any behavior deemed inappropriate. This could range from a private warning to a permanent ban, depending on the severity of the violation. Instances of misconduct can be reported to hello@ultralytics.com for investigation. Learn more about the enforcement steps in the [Enforcement Guidelines](#enforcement-guidelines) section.
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### Why is diversity and inclusion important in the Ultralytics community?
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Ultralytics values diversity and inclusion as fundamental aspects for fostering innovation and creativity within its community. A diverse and inclusive environment allows different perspectives and experiences to contribute to an open, welcoming, and healthy community. This commitment is reflected in our [Pledge](#our-pledge) to ensure a harassment-free experience for everyone regardless of their background.
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### How can I contribute to Ultralytics while adhering to the Code of Conduct?
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Contributing to Ultralytics means engaging positively and respectfully with other community members. You can contribute by demonstrating empathy, offering and accepting constructive feedback, and taking responsibility for any mistakes. Always aim to contribute in a way that benefits the entire community. For more details on acceptable behaviors, refer to the [Our Standards](#our-standards) section.
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### Where can I find additional information about the Ultralytics Code of Conduct?
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For more comprehensive details about the Ultralytics Code of Conduct, including reporting guidelines and enforcement policies, you can visit the [Contributor Covenant homepage](https://www.contributor-covenant.org/version/2/0/code_of_conduct.html) or check the [FAQ section of Contributor Covenant](https://www.contributor-covenant.org/faq). Learn more about Ultralytics' goals and initiatives on [our brand page](https://www.ultralytics.com/brand) and [about page](https://www.ultralytics.com/about).
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Should you have more questions or need further assistance, check our [Help Center](../help/FAQ.md) and [Contributing Guide](../help/contributing.md) for more information.
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@ -129,3 +129,31 @@ Users and developers are encouraged to familiarize themselves with the terms of
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Thank you for your interest in contributing to [Ultralytics open-source](https://github.com/ultralytics) YOLO projects. Your participation is crucial in shaping the future of our software and fostering a community of innovation and collaboration. Whether you're improving code, reporting bugs, or suggesting features, your contributions make a significant impact.
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We look forward to seeing your ideas in action and appreciate your commitment to advancing object detection technology. Let's continue to grow and innovate together in this exciting open-source journey. Happy coding! 🚀🌟
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## FAQ
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### Why should I contribute to Ultralytics YOLO open-source repositories?
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Contributing to Ultralytics YOLO open-source repositories helps improve the software, making it more robust and feature-rich for the entire community. Contributions can include code enhancements, bug fixes, documentation improvements, and new feature implementations. Additionally, contributing offers the chance to collaborate with other skilled developers and experts in the field, boosting your own skills and reputation. For information on how to get started, refer to the [Contributing via Pull Requests](#contributing-via-pull-requests) section.
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### How do I sign the Contributor License Agreement (CLA) for Ultralytics YOLO?
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To sign the Contributor License Agreement (CLA), follow the instructions provided by the CLA bot after submitting your pull request. This will ensure your contributions are properly licensed under the AGPL-3.0 license, maintaining the legal integrity of the open-source project. Add a comment in your pull request mentioning:
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```
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I have read the CLA Document and I sign the CLA
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```
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For more information, see the [CLA Signing](#cla-signing) section.
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### What are Google-style docstrings and why are they required for Ultralytics YOLO contributions?
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Google-style docstrings provide clear and concise documentation for functions and classes, enhancing readability and maintainability of the code. These docstrings outline the function's purpose, arguments, and return values with specific formatting rules. When contributing to Ultralytics YOLO, adhering to Google-style docstrings ensures that your additions are comprehensible and well-documented. For examples and guidelines, visit the [Google-Style Docstrings](#google-style-docstrings) section.
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### How can I ensure my changes pass the GitHub Actions CI tests?
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Before your pull request is merged, it must pass all GitHub Actions Continuous Integration (CI) tests. These tests include linting, unit tests, and other checks to ensure the code meets the project's quality standards. Review the output of the GitHub Actions and address any issues. For detailed information on the CI process and troubleshooting tips, see the [GitHub Actions CI Tests](#github-actions-ci-tests) section.
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### How do I report a bug in Ultralytics YOLO repositories?
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To report a bug, provide a clear and concise [Minimum Reproducible Example](../help/minimum_reproducible_example.md) along with your bug report. This helps developers quickly identify and fix the issue. Ensure your example is minimal yet sufficient to replicate the problem. For more detailed steps on reporting bugs, refer to the [Reporting Bugs](#reporting-bugs) section.
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@ -35,3 +35,29 @@ At Ultralytics, we recognize that the long-term success of our company relies no
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This policy reflects our commitment to minimizing our environmental footprint, ensuring the safety and well-being of our employees, and continuously improving our performance.
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Please remember that the implementation of an effective EHS policy requires the involvement and commitment of everyone working at or with Ultralytics. We encourage you to take personal responsibility for your safety and the safety of others, and to take care of the environment in which we live and work.
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## FAQ
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### What is Ultralytics' Environmental, Health, and Safety (EHS) policy?
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Ultralytics' Environmental, Health, and Safety (EHS) policy is a comprehensive framework designed to ensure the safety and well-being of employees, stakeholders, and the environment. It emphasizes compliance with relevant laws, accident prevention through risk management, continuous improvement through measurable objectives, open communication, and education and training for employees. By following these principles, Ultralytics aims to minimize its environmental footprint and promote sustainable practices. [Learn more about Ultralytics' commitment to EHS](https://www.ultralytics.com/about).
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### How does Ultralytics ensure compliance with EHS regulations?
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Ultralytics ensures compliance with EHS regulations by adhering to all applicable laws, regulations, and standards. The company not only strives to meet these requirements but often exceeds them by implementing stringent internal policies. Regular audits, monitoring, and reviews are conducted to ensure ongoing compliance. Managers and supervisors are also accountable for ensuring these standards are maintained within their areas of control. For more details, refer to the [Policy Principles section](#policy-principles) on the documentation page.
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### Why is continuous improvement a key principle in Ultralytics' EHS policy?
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Continuous improvement is essential in Ultralytics' EHS policy because it ensures the company consistently enhances its performance in environmental, health, and safety areas. By setting measurable objectives, monitoring performance, and revising policies and procedures as needed, Ultralytics can adapt to new challenges and optimize its processes. This approach not only mitigates risks but also demonstrates Ultralytics' commitment to sustainability and excellence. For practical examples of continuous improvement, check the [Implementation Measures section](#implementation-measures).
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### What are the roles and responsibilities of employees in implementing the EHS policy at Ultralytics?
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Every employee and contractor at Ultralytics is responsible for adhering to the EHS policy. This includes following safety protocols, participating in necessary training, and taking personal responsibility for their safety and the safety of others. Managers and supervisors have an added responsibility of ensuring the EHS policy is effectively implemented within their areas of control, which involves risk assessments and resource allocation. For more information about responsibility and accountability, see the [Implementation Measures section](#implementation-measures).
|
||||
|
||||
### How does Ultralytics handle emergency preparedness and response in its EHS policy?
|
||||
|
||||
Ultralytics handles emergency preparedness and response by developing, maintaining, and regularly testing emergency plans to address potential EHS incidents effectively. These plans ensure that the company can respond swiftly and efficiently to minimize harm to employees, the environment, and property. Regular training and drills are conducted to keep the response teams prepared for various emergency scenarios. For additional context, refer to the [emergency preparedness and response measure](#implementation-measures).
|
||||
|
||||
### How does Ultralytics engage with stakeholders regarding its EHS performance?
|
||||
|
||||
Ultralytics communicates openly with stakeholders about its EHS performance by sharing relevant information and addressing any concerns or expectations. This engagement includes regular reporting on EHS activities, performance metrics, and improvement initiatives. Stakeholders are also encouraged to provide feedback, which helps Ultralytics to refine its policies and practices continually. Learn more about this commitment in the [Communication principle](#policy-principles) section.
|
||||
|
|
|
|||
|
|
@ -17,3 +17,33 @@ Welcome to the Ultralytics Help page! We are dedicated to providing you with det
|
|||
- [Privacy Policy](privacy.md): Read our privacy policy to understand how we protect your data and respect your privacy in all our services and operations.
|
||||
|
||||
We encourage you to review these resources for a seamless and productive experience. Our aim is to foster a helpful and friendly environment for everyone in the Ultralytics community. Should you require additional support, please feel free to reach out via GitHub Issues or our official discussion forums. Happy coding!
|
||||
|
||||
## FAQ
|
||||
|
||||
### What is Ultralytics YOLO and how does it benefit my machine learning projects?
|
||||
|
||||
Ultralytics YOLO (You Only Look Once) is a state-of-the-art, real-time object detection model. Its latest version, YOLOv8, enhances speed, accuracy, and versatility, making it ideal for a wide range of applications, from real-time video analytics to advanced machine learning research. YOLO's efficiency in detecting objects in images and videos has made it the go-to solution for businesses and researchers looking to integrate robust computer vision capabilities into their projects.
|
||||
|
||||
For more details on YOLOv8, visit the [YOLOv8 documentation](../tasks/detect.md).
|
||||
|
||||
### How do I contribute to Ultralytics YOLO repositories?
|
||||
|
||||
Contributing to Ultralytics YOLO repositories is straightforward. Start by reviewing the [Contributing Guide](../help/contributing.md) to understand the protocols for submitting pull requests, reporting bugs, and more. You'll also need to sign the [Contributor License Agreement (CLA)](../help/CLA.md) to ensure your contributions are legally recognized. For effective bug reporting, refer to the [Minimum Reproducible Example (MRE) Guide](../help/minimum_reproducible_example.md).
|
||||
|
||||
### Why should I use Ultralytics HUB for my machine learning projects?
|
||||
|
||||
Ultralytics HUB offers a seamless, no-code solution for managing your machine learning projects. It enables you to generate, train, and deploy AI models like YOLOv8 effortlessly. Unique features include cloud training, real-time tracking, and intuitive dataset management. Ultralytics HUB simplifies the entire workflow, from data processing to model deployment, making it an indispensable tool for both beginners and advanced users.
|
||||
|
||||
To get started, visit [Ultralytics HUB Quickstart](../hub/quickstart.md).
|
||||
|
||||
### What is Continuous Integration (CI) in Ultralytics, and how does it ensure high-quality code?
|
||||
|
||||
Continuous Integration (CI) in Ultralytics involves automated processes that ensure the integrity and quality of the codebase. Our CI setup includes Docker deployment, broken link checks, CodeQL analysis, and PyPI publishing. These processes help maintain stable and secure repositories by automatically running tests and checks on new code submissions.
|
||||
|
||||
Learn more in the [Continuous Integration (CI) Guide](../help/CI.md).
|
||||
|
||||
### How is data privacy handled by Ultralytics?
|
||||
|
||||
Ultralytics takes data privacy seriously. Our [Privacy Policy](../help/privacy.md) outlines how we collect and use anonymized data to improve the YOLO package while prioritizing user privacy and control. We adhere to strict data protection regulations to ensure your information is secure at all times.
|
||||
|
||||
For more information, review our [Privacy Policy](../help/privacy.md).
|
||||
|
|
|
|||
|
|
@ -77,3 +77,63 @@ RuntimeError: Expected input[1, 0, 640, 640] to have 3 channels, but got 0 chann
|
|||
In this example, the MRE demonstrates the issue with a minimal amount of code, uses a public model (`"yolov8n.pt"`), includes all necessary dependencies, and provides a clear description of the problem along with the error message.
|
||||
|
||||
By following these guidelines, you'll help the maintainers and [contributors](https://github.com/ultralytics/ultralytics/graphs/contributors) of Ultralytics YOLO repositories to understand and resolve your issue more efficiently.
|
||||
|
||||
## FAQ
|
||||
|
||||
### How do I create an effective Minimum Reproducible Example (MRE) for bug reports in Ultralytics YOLO repositories?
|
||||
|
||||
To create an effective Minimum Reproducible Example (MRE) for bug reports in Ultralytics YOLO repositories, follow these steps:
|
||||
|
||||
1. **Isolate the Problem**: Remove any code or dependencies that are not directly related to the issue.
|
||||
2. **Use Public Models and Datasets**: Utilize public resources like `yolov8n.pt` and `coco8.yaml` for easier reproducibility.
|
||||
3. **Include All Necessary Dependencies**: Specify required packages and their versions. You can list dependencies using `yolo checks` if you have `ultralytics` installed or `pip list`.
|
||||
4. **Write a Clear Description of the Issue**: Explain the expected and actual behavior, including any error messages or logs.
|
||||
5. **Format Your Code Properly**: Use code blocks to format your code, making it easier to read.
|
||||
6. **Test Your MRE**: Ensure your MRE reproduces the issue without modifications.
|
||||
|
||||
For a detailed guide, see [Creating a Minimum Reproducible Example](#creating-a-minimum-reproducible-example-for-bug-reports-in-ultralytics-yolo-repositories).
|
||||
|
||||
### Why should I use publicly available models and datasets in my MRE for Ultralytics YOLO bug reports?
|
||||
|
||||
Using publicly available models and datasets in your MRE ensures that maintainers can easily run your example without needing access to proprietary data. This allows for quicker and more efficient issue resolution. For instance, using the `yolov8n.pt` model and `coco8.yaml` dataset helps standardize and simplify the debugging process. Learn more about public models and datasets in the [Use Public Models and Datasets](#2-use-public-models-and-datasets) section.
|
||||
|
||||
### What information should I include in my bug report for Ultralytics YOLO?
|
||||
|
||||
A comprehensive bug report for Ultralytics YOLO should include:
|
||||
|
||||
- **Clear Description**: Explain the issue, expected behavior, and actual behavior.
|
||||
- **Error Messages**: Include any relevant error messages or logs.
|
||||
- **Dependencies**: List required dependencies and their versions.
|
||||
- **MRE**: Provide a Minimum Reproducible Example.
|
||||
- **Steps to Reproduce**: Outline the steps needed to reproduce the issue.
|
||||
|
||||
For a complete checklist, refer to the [Write a Clear Description of the Issue](#4-write-a-clear-description-of-the-issue) section.
|
||||
|
||||
### How can I format my code properly when submitting a bug report on GitHub?
|
||||
|
||||
To format your code properly when submitting a bug report on GitHub:
|
||||
|
||||
- Use triple backticks (\```) to create code blocks.
|
||||
- Specify the programming language for syntax highlighting, e.g., \```python.
|
||||
- Ensure your code is indented correctly for readability.
|
||||
|
||||
Example:
|
||||
|
||||
````bash
|
||||
```python
|
||||
# Your Python code goes here
|
||||
```
|
||||
````
|
||||
|
||||
For more tips on code formatting, see [Format Your Code Properly](#5-format-your-code-properly).
|
||||
|
||||
### What are some common errors to check before submitting my MRE for a bug report?
|
||||
|
||||
Before submitting your MRE, make sure to:
|
||||
|
||||
- Verify the issue is reproducible.
|
||||
- Ensure all dependencies are listed and correct.
|
||||
- Remove any unnecessary code.
|
||||
- Test the MRE to ensure it reproduces the issue without modifications.
|
||||
|
||||
For a detailed checklist, visit the [Test Your MRE](#6-test-your-mre) section.
|
||||
|
|
|
|||
|
|
@ -77,6 +77,7 @@ To gain insight into the current configuration of your settings, you can view th
|
|||
!!! Example "View settings"
|
||||
|
||||
=== "Python"
|
||||
|
||||
You can use Python to view your settings. Start by importing the `settings` object from the `ultralytics` module. Print and return settings using the following commands:
|
||||
```python
|
||||
from ultralytics import settings
|
||||
|
|
@ -89,6 +90,7 @@ To gain insight into the current configuration of your settings, you can view th
|
|||
```
|
||||
|
||||
=== "CLI"
|
||||
|
||||
Alternatively, the command-line interface allows you to check your settings with a simple command:
|
||||
```bash
|
||||
yolo settings
|
||||
|
|
@ -101,6 +103,7 @@ Ultralytics allows users to easily modify their settings. Changes can be perform
|
|||
!!! Example "Update settings"
|
||||
|
||||
=== "Python"
|
||||
|
||||
Within the Python environment, call the `update` method on the `settings` object to change your settings:
|
||||
```python
|
||||
from ultralytics import settings
|
||||
|
|
@ -113,6 +116,7 @@ Ultralytics allows users to easily modify their settings. Changes can be perform
|
|||
```
|
||||
|
||||
=== "CLI"
|
||||
|
||||
If you prefer using the command-line interface, the following commands will allow you to modify your settings:
|
||||
```bash
|
||||
# Disable analytics and crash reporting
|
||||
|
|
@ -135,3 +139,78 @@ Ultralytics takes user privacy seriously. We design our data collection practice
|
|||
## Questions or Concerns
|
||||
|
||||
If you have any questions or concerns about our data collection practices, please reach out to us via our [contact form](https://ultralytics.com/contact) or via [support@ultralytics.com](mailto:support@ultralytics.com). We are dedicated to ensuring our users feel informed and confident in their privacy when using our package.
|
||||
|
||||
## FAQ
|
||||
|
||||
### How does Ultralytics ensure the privacy of the data it collects?
|
||||
|
||||
Ultralytics prioritizes user privacy through several key measures. First, all data collected via Google Analytics and Sentry is anonymized to ensure that no personally identifiable information (PII) is gathered. Secondly, data is analyzed in aggregate form, allowing us to observe patterns without identifying individual user activities. Finally, we do not collect any training or inference images, further protecting user data. These measures align with our commitment to transparency and privacy. For more details, visit our [Privacy Considerations](#privacy-considerations) section.
|
||||
|
||||
### What types of data does Ultralytics collect with Google Analytics?
|
||||
|
||||
Ultralytics collects three primary types of data using Google Analytics:
|
||||
|
||||
- **Usage Metrics**: These include how often and in what ways the YOLO Python package is used, preferred features, and typical command-line arguments.
|
||||
- **System Information**: General non-identifiable information about the computing environments where the package is run.
|
||||
- **Performance Data**: Metrics related to the performance of models during training, validation, and inference.
|
||||
This data helps us enhance user experience and optimize software performance. Learn more in the [Anonymized Google Analytics](#anonymized-google-analytics) section.
|
||||
|
||||
### How can I disable data collection in the Ultralytics YOLO package?
|
||||
|
||||
To opt out of data collection, you can simply set `sync=False` in your YOLO settings. This action stops the transmission of any analytics or crash reports. You can disable data collection using Python or CLI methods:
|
||||
|
||||
!!! Example "Update settings"
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
from ultralytics import settings
|
||||
|
||||
# Disable analytics and crash reporting
|
||||
settings.update({"sync": False})
|
||||
|
||||
# Reset settings to default values
|
||||
settings.reset()
|
||||
```
|
||||
|
||||
=== "CLI"
|
||||
|
||||
```bash
|
||||
# Disable analytics and crash reporting
|
||||
yolo settings sync=False
|
||||
|
||||
# Reset settings to default values
|
||||
yolo settings reset
|
||||
```
|
||||
|
||||
For more details on modifying your settings, refer to the [Modifying Settings](#modifying-settings) section.
|
||||
|
||||
### How does crash reporting with Sentry work in Ultralytics YOLO?
|
||||
|
||||
If the `sentry-sdk` package is pre-installed, Sentry collects detailed crash logs and error messages whenever a crash event occurs. This data helps us diagnose and resolve issues promptly, improving the robustness and reliability of the YOLO Python package. The collected crash logs are scrubbed of any personally identifiable information to protect user privacy. For more information, check the [Sentry Crash Reporting](#sentry-crash-reporting) section.
|
||||
|
||||
### Can I inspect my current data collection settings in Ultralytics YOLO?
|
||||
|
||||
Yes, you can easily view your current settings to understand the configuration of your data collection preferences. Use the following methods to inspect these settings:
|
||||
|
||||
!!! Example "View settings"
|
||||
|
||||
=== "Python"
|
||||
|
||||
```python
|
||||
from ultralytics import settings
|
||||
|
||||
# View all settings
|
||||
print(settings)
|
||||
|
||||
# Return analytics and crash reporting setting
|
||||
value = settings["sync"]
|
||||
```
|
||||
|
||||
=== "CLI"
|
||||
|
||||
```bash
|
||||
yolo settings
|
||||
```
|
||||
|
||||
For further details, refer to the [Inspecting Settings](#inspecting-settings) section.
|
||||
|
|
|
|||
|
|
@ -34,3 +34,41 @@ We enable private vulnerability reporting, allowing users to discreetly report p
|
|||
If you suspect or discover a security vulnerability in any of our repositories, please let us know immediately. You can reach out to us directly via our [contact form](https://ultralytics.com/contact) or via [security@ultralytics.com](mailto:security@ultralytics.com). Our security team will investigate and respond as soon as possible.
|
||||
|
||||
We appreciate your help in keeping all Ultralytics open-source projects secure and safe for everyone 🙏.
|
||||
|
||||
## FAQ
|
||||
|
||||
### What are the security measures implemented by Ultralytics to protect user data?
|
||||
|
||||
Ultralytics employs a comprehensive security strategy to protect user data and systems. Key measures include:
|
||||
|
||||
- **Snyk Scanning**: Conducts security scans to detect vulnerabilities in code and Dockerfiles.
|
||||
- **GitHub CodeQL**: Analyzes code semantics to detect complex vulnerabilities such as SQL injection.
|
||||
- **Dependabot Alerts**: Monitors dependencies for known vulnerabilities and sends alerts for swift remediation.
|
||||
- **Secret Scanning**: Detects sensitive data like credentials or private keys in code repositories to prevent data breaches.
|
||||
- **Private Vulnerability Reporting**: Offers a secure channel for users to report potential security issues discreetly.
|
||||
|
||||
These tools ensure proactive identification and resolution of security issues, enhancing overall system security. For more details, visit our [export documentation](../modes/export.md).
|
||||
|
||||
### How does Ultralytics use Snyk for security scanning?
|
||||
|
||||
Ultralytics utilizes [Snyk](https://snyk.io/advisor/python/ultralytics) to conduct thorough security scans on its repositories. Snyk extends beyond basic dependency checks, examining the code and Dockerfiles for various vulnerabilities. By proactively identifying and resolving potential security issues, Snyk helps ensure that Ultralytics' open-source projects remain secure and reliable.
|
||||
|
||||
To see the Snyk badge and learn more about its deployment, check the [Snyk Scanning section](#snyk-scanning).
|
||||
|
||||
### What is CodeQL and how does it enhance security for Ultralytics?
|
||||
|
||||
[CodeQL](https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/about-code-scanning-with-codeql) is a security analysis tool integrated into Ultralytics' workflow via GitHub. It delves deep into the codebase to identify complex vulnerabilities such as SQL injection and Cross-Site Scripting (XSS). CodeQL analyzes the semantic structure of the code to provide an advanced level of security, ensuring early detection and mitigation of potential risks.
|
||||
|
||||
For more information on how CodeQL is used, visit the [GitHub CodeQL Scanning section](#github-codeql-scanning).
|
||||
|
||||
### How does Dependabot help maintain Ultralytics' code security?
|
||||
|
||||
[Dependabot](https://docs.github.com/en/code-security/dependabot) is an automated tool that monitors and manages dependencies for known vulnerabilities. When Dependabot detects a vulnerability in an Ultralytics project dependency, it sends an alert, allowing the team to quickly address and mitigate the issue. This ensures that dependencies are kept secure and up-to-date, minimizing potential security risks.
|
||||
|
||||
For more details, explore the [GitHub Dependabot Alerts section](#github-dependabot-alerts).
|
||||
|
||||
### How does Ultralytics handle private vulnerability reporting?
|
||||
|
||||
Ultralytics encourages users to report potential security issues through private channels. Users can report vulnerabilities discreetly via the [contact form](https://ultralytics.com/contact) or by emailing [security@ultralytics.com](mailto:security@ultralytics.com). This ensures responsible disclosure and allows the security team to investigate and address vulnerabilities securely and efficiently.
|
||||
|
||||
For more information on private vulnerability reporting, refer to the [Private Vulnerability Reporting section](#private-vulnerability-reporting).
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue