description: Discover how Ultralytics collects and uses anonymized data to enhance the YOLO Python package while prioritizing user privacy and control.
keywords: Ultralytics, data collection, YOLO, Python package, Google Analytics, Sentry, privacy, anonymized data, user control, crash reporting
[Ultralytics](https://www.ultralytics.com/) is dedicated to the continuous enhancement of the user experience and the capabilities of our Python package, including the advanced YOLO models we develop. Our approach involves the gathering of anonymized usage statistics and crash reports, helping us identify opportunities for improvement and ensuring the reliability of our software. This transparency document outlines what data we collect, its purpose, and the choice you have regarding this data collection.
[Google Analytics](https://developers.google.com/analytics) is a web analytics service offered by Google that tracks and reports website traffic. It allows us to collect data about how our Python package is used, which is crucial for making informed decisions about design and functionality.
### What We Collect
- **Usage Metrics**: These metrics help us understand how frequently and in what ways the package is utilized, what features are favored, and the typical command-line arguments that are used.
- **System Information**: We collect general non-identifiable information about your computing environment to ensure our package performs well across various systems.
- **Performance Data**: Understanding the performance of our models during training, validation, and inference helps us in identifying optimization opportunities.
For more information about Google Analytics and [data privacy](https://www.ultralytics.com/glossary/data-privacy), visit [Google Analytics Privacy](https://support.google.com/analytics/answer/6004245).
- **Feature Improvement**: Insights from usage metrics guide us in enhancing user satisfaction and interface design.
- **Optimization**: Performance data assist us in fine-tuning our models for better efficiency and speed across diverse hardware and software configurations.
- **Trend Analysis**: By studying usage trends, we can predict and respond to the evolving needs of our community.
### Privacy Considerations
We take several measures to ensure the privacy and security of the data you entrust to us:
- **Anonymization**: We configure Google Analytics to anonymize the data collected, which means no personally identifiable information (PII) is gathered. You can use our services with the assurance that your personal details remain private.
- **Aggregation**: Data is analyzed only in aggregate form. This practice ensures that patterns can be observed without revealing any individual user's activity.
- **No Image Data Collection**: Ultralytics does not collect, process, or view any training or inference images.
[Sentry](https://sentry.io/welcome/) is a developer-centric error tracking software that aids in identifying, diagnosing, and resolving issues in real-time, ensuring the robustness and reliability of applications. Within our package, it plays a crucial role by providing insights through crash reporting, significantly contributing to the stability and ongoing refinement of our software.
Crash reporting via Sentry is activated only if the `sentry-sdk` Python package is pre-installed on your system. This package isn't included in the `ultralytics` prerequisites and won't be installed automatically by Ultralytics.
- **Debugging**: Analyzing crash logs and error messages enables us to swiftly identify and correct software bugs.
- **Stability Metrics**: By constantly monitoring for crashes, we aim to improve the stability and reliability of our package.
### Privacy Considerations
- **Sensitive Information**: We ensure that crash logs are scrubbed of any personally identifiable or sensitive user data, safeguarding the confidentiality of your information.
- **Controlled Collection**: Our crash reporting mechanism is meticulously calibrated to gather only what is essential for troubleshooting while respecting user privacy.
By detailing the tools used for data collection and offering additional background information with URLs to their respective privacy pages, users are provided with a comprehensive view of our practices, emphasizing transparency and respect for user privacy.
## Disabling Data Collection
We believe in providing our users with full control over their data. By default, our package is configured to collect analytics and crash reports to help improve the experience for all users. However, we respect that some users may prefer to opt out of this data collection.
To opt out of sending analytics and crash reports, you can simply set `sync=False` in your YOLO settings. This ensures that no data is transmitted from your machine to our analytics tools.
### Inspecting Settings
To gain insight into the current configuration of your settings, you can view them directly:
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:
The `sync=False` setting will prevent any data from being sent to Google Analytics or Sentry. Your settings will be respected across all sessions using the Ultralytics package and saved to disk for future sessions.
If you have any questions or concerns about our data collection practices, please reach out to us via our [contact form](https://www.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.
### 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:
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: