diff --git a/.openpublishing.publish.config.json b/.openpublishing.publish.config.json index 9376e9928d4..d2a0d037bfd 100644 --- a/.openpublishing.publish.config.json +++ b/.openpublishing.publish.config.json @@ -12,7 +12,8 @@ "monikers": [], "open_to_public_contributors": true, "type_mapping": { - "Conceptual": "Content" + "Conceptual": "Content", + "ZonePivotGroups": "Toc" }, "build_entry_point": "docs" } @@ -169,8 +170,6 @@ "branch_mapping": {} } ], - "git_repository_url_open_to_public_contributors": "https://github.com/MicrosoftDocs/azure-ai-docs", - "git_repository_branch_open_to_public_contributors": "main", "branch_target_mapping": {}, "targets": {} } diff --git a/articles/ai-services/content-safety/faq.yml b/articles/ai-services/content-safety/faq.yml index 3d019f094c1..c6eccddf7a2 100644 --- a/articles/ai-services/content-safety/faq.yml +++ b/articles/ai-services/content-safety/faq.yml @@ -8,10 +8,10 @@ metadata: ms.service: azure-ai-content-safety ms.topic: faq - ms.date: 04/30/2024 + ms.date: 09/04/2024 ms.author: pafarley ms.custom: -title: Azure AI Content Safety API Frequently Asked Questions +title: Azure AI Content Safety Frequently Asked Questions summary: | > [!TIP] > If you can't find answers to your questions in this FAQ, ask the Cognitive Services API community on [StackOverflow](https://stackoverflow.com/questions/tagged/project-oxford+or+microsoft-cognitive) or contact Help and Support on [UserVoice](https://feedback.azure.com/d365community/forum/09041fae-0b25-ec11-b6e6-000d3a4f0858) @@ -25,8 +25,8 @@ sections: answer: | The main differences between the two services are: - - Azure Content Moderator uses binary classification for each content type (such as `profanity` or `adult`), while Azure AI Content Safety uses multiple classes (such as `sexual`, `violent`, `hate`, and `self-harm`) with different severity levels. - - Azure AI Content Safety supports multilingual content moderation in English, German, Japanese, Spanish, French, Italian, Portuguese, and Chinese, while Azure Content Moderator's AI classifiers only support English. + - Azure Content Moderator uses binary classification for each content type (such as `profanity` or `adult`), while Azure AI Content Safety uses different classes (such as `sexual`, `violent`, `hate`, and `self-harm`) with multiple severity levels. + - Azure AI Content Safety supports multilingual content moderation (see [Language support](./language-support.md)), while Azure Content Moderator's AI classifiers only support English. - Azure Content Moderator has a built-in term list and a custom term list feature, while Azure AI Content Safety does not have a built-in term list but relies on advanced language and vision models to detect harmful content. It also provides a custom term list feature for customization. - Azure AI Content Safety has an interactive studio for exploring and testing the service capabilities, while Azure Content Moderator does not. - question: | @@ -35,7 +35,7 @@ sections: Microsoft recommends that customers who are using Azure Content Moderator migrate to Azure AI Content Safety because: - Azure AI Content Safety offers more accurate and granular detection of harmful content in text and images using state-of-the-art AI models. - - Azure AI Content Safety supports multilingual content moderation in English, Japanese, German, Spanish, French, Portuguese, Italian, and Chinese. + - Azure AI Content Safety supports multilingual content moderation (see [Language support](./language-support.md)). - Azure AI Content Safety enables responsible AI practices by monitoring both user-generated and AI-generated content. - question: | Can I detect harmful content in custom categories that I define myself? @@ -44,8 +44,8 @@ sections: - question: | How does billing work for the Azure AI Content Safety service? answer: | - In the S tier, there are two types of APIs. For the Text API, the service is billed for the amount of text records submitted to the service. For the Image API, the service is billed for the number of images submitted to the service. + In the **S0** tier, there are two types of APIs. For the Text API, the service is billed for the amount of text records submitted to the service. For the Image API, the service is billed for the number of images submitted to the service. See the Azure [pricing page](https://aka.ms/content-safety-pricing) for more information. - question: | What happens if I exceed the transaction limit on my free tier for Azure AI Content Safety? answer: | - Usage is throttled if the transaction limit is reached on the Free tier. Customers cannot accrue overages on the free tier. + Service usage is throttled if you reach the transaction limit on the Free tier. Customers cannot accrue overages on the free tier. diff --git a/articles/ai-services/content-safety/includes/language-notice.md b/articles/ai-services/content-safety/includes/language-notice.md new file mode 100644 index 00000000000..ffbcbef6b8f --- /dev/null +++ b/articles/ai-services/content-safety/includes/language-notice.md @@ -0,0 +1,14 @@ +--- +title: "Language notice" +#services: cognitive-services +author: PatrickFarley +manager: nitinme +ms.service: azure-ai-content-safety +ms.topic: include +ms.date: 05/03/2023 +ms.author: pafarley +--- + +The Azure AI Content Safety models for protected material, groundedness detection, and custom categories (standard) work with English only. + +Other Azure AI Content Safety models have been specifically trained and tested on the following languages: Chinese, English, French, German, Spanish, Italian, Japanese, Portuguese. However, these features can work in many other languages, but the quality might vary. In all cases, you should do your own testing to ensure that it works for your application. \ No newline at end of file diff --git a/articles/ai-services/content-safety/language-support.md b/articles/ai-services/content-safety/language-support.md index 8e7ffcda1a4..641297dc734 100644 --- a/articles/ai-services/content-safety/language-support.md +++ b/articles/ai-services/content-safety/language-support.md @@ -7,7 +7,7 @@ author: PatrickFarley manager: nitinme ms.service: azure-ai-content-safety ms.topic: conceptual -ms.date: 06/01/2024 +ms.date: 09/04/2024 ms.author: pafarley --- @@ -15,121 +15,121 @@ ms.author: pafarley # Language support for Azure AI Content Safety > [!IMPORTANT] -> The Azure AI Content Safety models for protected material, groundedness detection, and custom categories (standard) work with English only. -> -> Other Azure AI Content Safety models have been specifically trained and tested on the following languages: Chinese, English, French, German, Spanish, Italian, Japanese, Portuguese. However, these features can work in many other languages, but the quality might vary. In all cases, you should do your own testing to ensure that it works for your application. +> [!INCLUDE [language-notice](includes/language-notice.md)] > [!NOTE] > **Language auto-detection** > > You don't need to specify a language code for text moderation or Prompt Shields. The service automatically detects your input language. -| Language name | Language code | Supported | Specially trained| -|-----------------------|---------------|--------|--| -| Afrikaans | `af` | ✔️ | | -| Albanian | `sq` | ✔️ | | -| Amharic | `am` | ✔️ | | -| Arabic | `ar` | ✔️ | | -| Armenian | `hy` | ✔️ | | -| Azerbaijani | `az` | ✔️ | | -| Bangla | `bn` | ✔️ | | -| Basque | `eu` | ✔️ | | -| Belarusian | `be` | ✔️ | | -| Bulgarian | `bg` | ✔️ | | -| Bulgarian (Latin) | `bg-Latn` | ✔️ | | -| Burmese | `my` | ✔️ | | -| Catalan | `ca` | ✔️ | | -| Cebuano | `ceb` | ✔️ | | -| Chinese | `zh` | ✔️ | ✔️ | -| Chinese (Latin) | `zh-Latn` | ✔️ | | -| Corsican | `co` | ✔️ | | -| Croatian | `hr` | ✔️ | | -| Czech | `cs` | ✔️ | | -| Danish | `da` | ✔️ | | -| Dutch | `nl` | ✔️ | | -| English | `en` | ✔️ | ✔️ | -| Esperanto | `eo` | ✔️ | | -| Estonian | `et` | ✔️ | | -| Filipino | `fil` | ✔️ | | -| Finnish | `fi` | ✔️ | | -| French | `fr` | ✔️ | ✔️ | -| Galician | `gl` | ✔️ | | -| Georgian | `ka` | ✔️ | | -| German | `de` | ✔️ | ✔️ | -| Greek | `el` | ✔️ | | -| Greek (Latin) | `el-Latn` | ✔️ | | -| Gujarati | `gu` | ✔️ | | -| Haitian | `ht` | ✔️ | | -| Hausa | `ha` | ✔️ | | -| Hawaiian | `haw` | ✔️ | | -| Hebrew | `iw` | ✔️ | | -| Hindi | `hi` | ✔️ | | -| Hindi (Latin script) | `hi-Latn` | ✔️ | | -| Hmong, Mong | `hmn` | ✔️ | | -| Hungarian | `hu` | ✔️ | | -| Icelandic | `is` | ✔️ | | -| Igbo | `ig` | ✔️ | | -| Indonesian | `id` | ✔️ | | -| Irish | `ga` | ✔️ | | -| Italian | `it` | ✔️ | ✔️ | -| Japanese | `ja` | ✔️ | ✔️ | -| Japanese (Latin) | `ja-Latn` | ✔️ | | -| Javanese | `jv` | ✔️ | | -| Kazakh | `kk` | ✔️ | | -| Khmer | `km` | ✔️ | | -| Korean | `ko` | ✔️ | | -| Kurdish | `ku` | ✔️ | | -| Kyrgyz | `ky` | ✔️ | | -| Lao | `lo` | ✔️ | | -| Latin | `la` | ✔️ | | -| Latvian | `lv` | ✔️ | | -| Lithuanian | `lt` | ✔️ | | -| Luxembourgish | `lb` | ✔️ | | -| Macedonian | `mk` | ✔️ | | -| Malagasy | `mg` | ✔️ | | -| Malay | `ms` | ✔️ | | -| Malayalam | `ml` | ✔️ | | -| Maltese | `mt` | ✔️ | | -| Maori | `mi` | ✔️ | | -| Marathi | `mr` | ✔️ | | -| Mongolian | `mn` | ✔️ | | -| Nepali | `ne` | ✔️ | | -| Nyanja | `ny` | ✔️ | | -| Norwegian | `no` | ✔️ | | -| Pashto | `ps` | ✔️ | | -| Persian | `fa` | ✔️ | | -| Polish | `pl` | ✔️ | | -| Portuguese | `pt` | ✔️ | ✔️ | -| Punjabi | `pa` | ✔️ | | -| Romanian | `ro` | ✔️ | | -| Russian | `ru` | ✔️ | | -| Russian (Latin) | `ru-Latn` | ✔️ | | -| Scottish Gaelic | `gd` | ✔️ | | -| Serbian | `sr` | ✔️ | | -| Shona | `sn` | ✔️ | | -| Sindhi | `sd` | ✔️ | | -| Sinhala | `si` | ✔️ | | -| Slovak | `sk` | ✔️ | | -| Slovenian | `sl` | ✔️ | | -| Somali | `so` | ✔️ | | -| Southern Sotho | `st` | ✔️ | | -| Spanish | `es` | ✔️ | ✔️ | -| Sundanese | `su` | ✔️ | | -| Swahili | `sw` | ✔️ | | -| Swedish | `sv` | ✔️ | | -| Tajik | `tg` | ✔️ | | -| Tamil | `ta` | ✔️ | | -| Telugu | `te` | ✔️ | | -| Thai | `th` | ✔️ | | -| Turkish | `tr` | ✔️ | | -| Ukrainian | `uk` | ✔️ | | -| Unknown language | `und` | ✔️ | | -| Urdu | `ur` | ✔️ | | -| Uzbek | `uz` | ✔️ | | -| Vietnamese | `vi` | ✔️ | | -| Welsh | `cy` | ✔️ | | -| Western Frisian | `fy` | ✔️ | | -| Xhosa | `xh` | ✔️ | | -| Yiddish | `yi` | ✔️ | | -| Yoruba | `yo` | ✔️ | | -| Zulu | `zu` | ✔️ | | + + +| Language name | Language code | Specially trained | Supported | +|-----------------------|---------------|-------------------|-----------| +| Afrikaans | `af` | | ✔️ | +| Albanian | `sq` | | ✔️ | +| Amharic | `am` | | ✔️ | +| Arabic | `ar` | | ✔️ | +| Armenian | `hy` | | ✔️ | +| Azerbaijani | `az` | | ✔️ | +| Bangla | `bn` | | ✔️ | +| Basque | `eu` | | ✔️ | +| Belarusian | `be` | | ✔️ | +| Bulgarian | `bg` | | ✔️ | +| Bulgarian (Latin) | `bg-Latn` | | ✔️ | +| Burmese | `my` | | ✔️ | +| Catalan | `ca` | | ✔️ | +| Cebuano | `ceb` | | ✔️ | +| Chinese | `zh` | ✔️ | ✔️ | +| Chinese (Latin) | `zh-Latn` | | ✔️ | +| Corsican | `co` | | ✔️ | +| Croatian | `hr` | | ✔️ | +| Czech | `cs` | | ✔️ | +| Danish | `da` | | ✔️ | +| Dutch | `nl` | | ✔️ | +| English | `en` | ✔️ | ✔️ | +| Esperanto | `eo` | | ✔️ | +| Estonian | `et` | | ✔️ | +| Filipino | `fil` | | ✔️ | +| Finnish | `fi` | | ✔️ | +| French | `fr` | ✔️ | ✔️ | +| Galician | `gl` | | ✔️ | +| Georgian | `ka` | | ✔️ | +| German | `de` | ✔️ | ✔️ | +| Greek | `el` | | ✔️ | +| Greek (Latin) | `el-Latn` | | ✔️ | +| Gujarati | `gu` | | ✔️ | +| Haitian | `ht` | | ✔️ | +| Hausa | `ha` | | ✔️ | +| Hawaiian | `haw` | | ✔️ | +| Hebrew | `iw` | | ✔️ | +| Hindi | `hi` | | ✔️ | +| Hindi (Latin script) | `hi-Latn` | | ✔️ | +| Hmong, Mong | `hmn` | | ✔️ | +| Hungarian | `hu` | | ✔️ | +| Icelandic | `is` | | ✔️ | +| Igbo | `ig` | | ✔️ | +| Indonesian | `id` | | ✔️ | +| Irish | `ga` | | ✔️ | +| Italian | `it` | ✔️ | ✔️ | +| Japanese | `ja` | ✔️ | ✔️ | +| Japanese (Latin) | `ja-Latn` | | ✔️ | +| Javanese | `jv` | | ✔️ | +| Kazakh | `kk` | | ✔️ | +| Khmer | `km` | | ✔️ | +| Korean | `ko` | | ✔️ | +| Kurdish | `ku` | | ✔️ | +| Kyrgyz | `ky` | | ✔️ | +| Lao | `lo` | | ✔️ | +| Latin | `la` | | ✔️ | +| Latvian | `lv` | | ✔️ | +| Lithuanian | `lt` | | ✔️ | +| Luxembourgish | `lb` | | ✔️ | +| Macedonian | `mk` | | ✔️ | +| Malagasy | `mg` | | ✔️ | +| Malay | `ms` | | ✔️ | +| Malayalam | `ml` | | ✔️ | +| Maltese | `mt` | | ✔️ | +| Maori | `mi` | | ✔️ | +| Marathi | `mr` | | ✔️ | +| Mongolian | `mn` | | ✔️ | +| Nepali | `ne` | | ✔️ | +| Nyanja | `ny` | | ✔️ | +| Norwegian | `no` | | ✔️ | +| Pashto | `ps` | | ✔️ | +| Persian | `fa` | | ✔️ | +| Polish | `pl` | | ✔️ | +| Portuguese | `pt` | ✔️ | ✔️ | +| Punjabi | `pa` | | ✔️ | +| Romanian | `ro` | | ✔️ | +| Russian | `ru` | | ✔️ | +| Russian (Latin) | `ru-Latn` | | ✔️ | +| Scottish Gaelic | `gd` | | ✔️ | +| Serbian | `sr` | | ✔️ | +| Shona | `sn` | | ✔️ | +| Sindhi | `sd` | | ✔️ | +| Sinhala | `si` | | ✔️ | +| Slovak | `sk` | | ✔️ | +| Slovenian | `sl` | | ✔️ | +| Somali | `so` | | ✔️ | +| Southern Sotho | `st` | | ✔️ | +| Spanish | `es` | ✔️ | ✔️ | +| Sundanese | `su` | | ✔️ | +| Swahili | `sw` | | ✔️ | +| Swedish | `sv` | | ✔️ | +| Tajik | `tg` | | ✔️ | +| Tamil | `ta` | | ✔️ | +| Telugu | `te` | | ✔️ | +| Thai | `th` | | ✔️ | +| Turkish | `tr` | | ✔️ | +| Ukrainian | `uk` | | ✔️ | +| Unknown language | `und` | | ✔️ | +| Urdu | `ur` | | ✔️ | +| Uzbek | `uz` | | ✔️ | +| Vietnamese | `vi` | | ✔️ | +| Welsh | `cy` | | ✔️ | +| Western Frisian | `fy` | | ✔️ | +| Xhosa | `xh` | | ✔️ | +| Yiddish | `yi` | | ✔️ | +| Yoruba | `yo` | | ✔️ | +| Zulu | `zu` | | ✔️ | \ No newline at end of file diff --git a/articles/ai-services/content-safety/overview.md b/articles/ai-services/content-safety/overview.md index b7113b2c741..8c32a1a2230 100644 --- a/articles/ai-services/content-safety/overview.md +++ b/articles/ai-services/content-safety/overview.md @@ -7,7 +7,7 @@ author: PatrickFarley manager: nitinme ms.service: azure-ai-content-safety ms.topic: overview -ms.date: 06/01/2024 +ms.date: 09/04/2024 ms.author: pafarley keywords: content safety, Azure AI Content Safety, online content safety, content filtering software, content moderation service, content moderation ms.custom: references_regions, build-2023, build-2023-dataai @@ -16,12 +16,11 @@ ms.custom: references_regions, build-2023, build-2023-dataai # What is Azure AI Content Safety? -Azure AI Content Safety detects harmful user-generated and AI-generated content in applications and services. Azure AI Content Safety includes text and image APIs that allow you to detect material that is harmful. We also have an interactive Content Safety Studio that allows you to view, explore and try out sample code for detecting harmful content across different modalities. +Azure AI Content Safety is an AI service that detects harmful user-generated and AI-generated content in applications and services. Azure AI Content Safety includes text and image APIs that allow you to detect material that is harmful. The interactive Content Safety Studio allows you to view, explore, and try out sample code for detecting harmful content across different modalities. Content filtering software can help your app comply with regulations or maintain the intended environment for your users. This documentation contains the following article types: - * **[Concepts](concepts/harm-categories.md)** provide in-depth explanations of the service functionality and features. * **[Quickstarts](./quickstart-text.md)** are getting-started instructions to guide you through making requests to the service. * **[How-to guides](./how-to/use-blocklist.md)** contain instructions for using the service in more specific or customized ways. @@ -43,7 +42,7 @@ The following are a few scenarios in which a software developer or team would re ## Product features -There are different types of analysis available from this service. The following table describes the currently available APIs. +This service makes several different types of analysis available. The following table describes the currently available APIs. | Feature | Functionality | Concepts guide | Get started | | :-------------------------- | :---------------------- | --| --| @@ -60,19 +59,19 @@ There are different types of analysis available from this service. The following [Azure AI Content Safety Studio](https://contentsafety.cognitive.azure.com) is an online tool designed to handle potentially offensive, risky, or undesirable content using cutting-edge content moderation ML models. It provides templates and customized workflows, enabling users to choose and build their own content moderation system. Users can upload their own content or try it out with provided sample content. -Content Safety Studio not only contains out-of-the-box AI models but also includes Microsoft's built-in **terms blocklists** to flag profanities and stay up to date with new trends. You can also upload your own blocklists to enhance the coverage of harmful content that's specific to your use case. +Content Safety Studio not only contains out-of-the-box AI models but also includes **Microsoft's built-in terms blocklists** to flag profanities and stay up to date with new content trends. You can also upload your own blocklists to enhance the coverage of harmful content that's specific to your use case. Studio also lets you set up a **moderation workflow**, where you can continuously monitor and improve content moderation performance. It can help you meet content requirements from all kinds of industries like gaming, media, education, E-commerce, and more. Businesses can easily connect their services to the Studio and have their content moderated in real-time, whether user-generated or AI-generated. All of these capabilities are handled by the Studio and its backend; customers don’t need to worry about model development. You can onboard your data for quick validation and monitor your KPIs accordingly, like technical metrics (latency, accuracy, recall), or business metrics (block rate, block volume, category proportions, language proportions, and more). With simple operations and configurations, customers can test different solutions quickly and find the best fit, instead of spending time experimenting with custom models or doing moderation manually. > [!div class="nextstepaction"] -> [Content Safety Studio](https://contentsafety.cognitive.azure.com) +> [Try Content Safety Studio](https://contentsafety.cognitive.azure.com) ### Content Safety Studio features -In Content Safety Studio, the following Azure AI Content Safety service features are available: +In Content Safety Studio, the following Azure AI Content Safety features are available: * **[Moderate Text Content](https://contentsafety.cognitive.azure.com/text)**: With the text moderation tool, you can easily run tests on text content. Whether you want to test a single sentence or an entire dataset, our tool offers a user-friendly interface that lets you assess the test results directly in the portal. You can experiment with different sensitivity levels to configure your content filters and blocklist management, ensuring that your content is always moderated to your exact specifications. Plus, with the ability to export the code, you can implement the tool directly in your application, streamlining your workflow and saving time. @@ -96,7 +95,7 @@ Learn how Azure AI Content Safety handles the [encryption and decryption of your ## Pricing -Currently, Azure AI Content Safety has an **F0 and S0** pricing tier. See the Azure [pricing page](https://aka.ms/content-safety-pricing) for more information. +Currently, Azure AI Content Safety has an **F0** and **S0** pricing tier. See the Azure [pricing page](https://aka.ms/content-safety-pricing) for more information. ## Service limits @@ -115,58 +114,54 @@ See the following list for the input requirements for each feature. - Maximum image file size: 4 MB - Dimensions between 50 x 50 and 2048 x 2048 pixels. - Images can be in JPEG, PNG, GIF, BMP, TIFF, or WEBP formats. -- **Prompt Shields**: +- **Prompt Shields API**: - Maximum prompt length: 10K characters. - Up to five documents with a total of 10K characters. -- **Groundedness detection (preview)**: +- **Groundedness detection API (preview)**: - Maximum length for grounding sources: 55,000 characters (per API call). - Maximum text and query length: 7,500 characters. -- **Protected material detection**: +- **Protected material detection API**: - Default maximum length: 1K characters. - Default minimum length: 110 characters (for scanning LLM completions, not user prompts). -- **Custom categories (standard)**: +- **Custom categories (standard) API**: - Maximum inference input length: 1K characters. ### Language support -Content Safety models have been specifically trained and tested in the following languages: English, German, Spanish, Japanese, French, Italian, Portuguese, and Chinese. However, the service can work in many other languages, but the quality might vary. In all cases, you should do your own testing to ensure that it works for your application. - -Custom Categories currently only works well in English. You can try to use other languages with your own dataset, but the quality might vary across languages. +[!INCLUDE [language-notice](includes/language-notice.md)] For more information, see [Language support](/azure/ai-services/content-safety/language-support). ### Region availability -To use the Content Safety APIs, you must create your Azure AI Content Safety resource in the supported regions. Currently, the Content Safety features are available in the following Azure regions: +To use the Content Safety APIs, you must create your Azure AI Content Safety resource in a supported region. Currently, the Content Safety features are available in the following Azure regions: -| Region | Moderation APIs (text and image) | Prompt Shields | Protected material detection for Text | Groundedness detection (preview) | Custom categories (rapid) (preview) | Custom categories (standard) | Blocklists | +| Region | Moderation APIs (text and image) | Prompt Shields | Protected material detection for Text | Groundedness detection (preview) | Custom categories (rapid) (preview) | Custom categories (standard) (preview) | Blocklists | |---------------------|----------------------------------|----------------|--------------------------------------|-----------------------------------|------------------------------------|-------------------------------|------------| | East US | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | -| East US 2 | ✅ | | ✅ | ✅ | ✅ | | ✅ | -| West US | | ✅ | ✅ | | ✅ | | | +| East US 2 | ✅ | ✅ | ✅ | ✅ | ✅ | | ✅ | +| West US | | ✅ | ✅ | | ✅ | | | | West US 2 | ✅ | ✅ | ✅ | | ✅ | | ✅ | | West US 3 | ✅ | ✅ | ✅ | | ✅ | | ✅ | | Poland Central | ✅ | ✅ | ✅ | | ✅ | | ✅ | -| South East Asia | ✅ | | ✅ | | ✅ | | ✅ | -| Central US | ✅ | | ✅ | | ✅ | | ✅ | -| North Central US | ✅ | | ✅ | | ✅ | | ✅ | -| South Central US | ✅ | | ✅ | | ✅ | | ✅ | +| South East Asia | ✅ |✅ | ✅ | | ✅ | | ✅ | +| Central US | ✅ | | ✅ | | ✅ | | ✅ | +| North Central US | ✅ | ✅ | ✅ | | ✅ | | ✅ | +| South Central US | ✅ | ✅ | ✅ | | ✅ | | ✅ | | Canada East | ✅ | ✅ | ✅ | | ✅ | | ✅ | | Switzerland North | ✅ | ✅ | ✅ | | ✅ | ✅ | ✅ | | Sweden Central | ✅ | ✅ | ✅ | ✅ | ✅ | | ✅ | -| UK South | ✅ | | ✅ | | ✅ | | ✅ | +| UK South | ✅ | ✅ | ✅ | | ✅ | | ✅ | | France Central | ✅ | ✅ | ✅ | | ✅ | | ✅ | | West Europe | ✅ | ✅ | ✅ | | ✅ | | ✅ | | Japan East | ✅ | ✅ | ✅ | | ✅ | | ✅ | -| Australia East | ✅ | ✅ | ✅ | | ✅ | | ✅ | -| South India | ✅ | | ✅ | | ✅ | ✅ | ✅ | -| USGov Arizona | ✅ | ✅ | ✅ | | | | | -| USGov Virginia | ✅ | ✅ | ✅ | | | | | - - +| Australia East | ✅ | ✅ | ✅ | | ✅ | ✅ | ✅ | +| South India | ✅ | | ✅ | | ✅ | | ✅ | +| USGov Arizona | ✅ | | | | | | ✅ | +| USGov Virginia | ✅ | | | | | | ✅ | -Feel free to [contact us](mailto:contentsafetysupport@microsoft.com) if you need other regions for your business. +Feel free to [contact us](mailto:contentsafetysupport@microsoft.com) if your business needs other regions to be available. ### Query rates @@ -174,10 +169,10 @@ Content Safety features have query rate limits in requests-per-second (RPS) or r |Pricing tier | Moderation APIs
(text and image) | Prompt Shields | Protected material
detection | Groundedness
detection (preview) | Custom categories
(rapid) (preview) | Custom categories
(standard) (preview)| |--------|---------|-------------|---------|---------|---------|--| -| F0 | 1000 RP10S | 1000 RP10S | 1000 RP10S | 50 RP10S | 1000 RP10S | 5 RPS| +| F0 | 5 RPS | 5 RPS | 5 RPS | 10 RP10S | 5 RPS | 10 RP10S| | S0 | 1000 RP10S | 1000 RP10S | 1000 RP10S | 50 RP10S | 1000 RP10S | 5 RPS| -If you need a faster rate, please [contact us](mailto:contentsafetysupport@microsoft.com) to request. +If you need a faster rate, please [contact us](mailto:contentsafetysupport@microsoft.com) to request it. ## Contact us diff --git a/articles/ai-services/content-safety/whats-new.md b/articles/ai-services/content-safety/whats-new.md index c1b983ba971..8a622a4deea 100644 --- a/articles/ai-services/content-safety/whats-new.md +++ b/articles/ai-services/content-safety/whats-new.md @@ -8,7 +8,7 @@ manager: nitinme ms.service: azure-ai-content-safety ms.custom: build-2023 ms.topic: overview -ms.date: 02/27/2024 +ms.date: 09/04/2024 ms.author: pafarley --- @@ -20,11 +20,10 @@ Learn what's new in the service. These items might be release notes, videos, blo ### Custom categories (standard) API -The custom categories API lets you create and train your own custom content categories and scan text for matches. See [Custom categories](./concepts/custom-categories.md) to learn more. +The custom categories (standard) API lets you create and train your own custom content categories and scan text for matches. See [Custom categories](./concepts/custom-categories.md) to learn more. ## May 2024 - ### Custom categories (rapid) API The custom categories (rapid) API lets you quickly define emerging harmful content patterns and scan text and images for matches. See [Custom categories](./concepts/custom-categories.md) to learn more. @@ -33,11 +32,11 @@ The custom categories (rapid) API lets you quickly define emerging harmful conte ### Prompt Shields public preview -Previously known as **Jailbreak risk detection**, this updated feature detects User Prompt injection attacks, in which users deliberately exploit system vulnerabilities to elicit unauthorized behavior from large language model. Prompt Shields analyzes both direct user prompt attacks and indirect attacks that are embedded in input documents or images. See [Prompt Shields](./concepts/jailbreak-detection.md) to learn more. +Previously known as **Jailbreak risk detection**, this updated feature detects prompt attacks, in which users deliberately exploit system vulnerabilities to elicit unauthorized behavior from large language model. Prompt Shields analyzes both direct user prompt attacks and indirect attacks which are embedded in input documents or images. See [Prompt Shields](./concepts/jailbreak-detection.md) to learn more. ### Groundedness detection public preview -The Groundedness detection API detects whether the text responses of large language models (LLMs) are grounded in the source materials provided by the users. Ungroundedness refers to instances where the LLMs produce information that is non-factual or inaccurate from what was present in the source materials. See [Groundedness detection](./concepts/groundedness.md) to learn more. +The Groundedness detection API detects whether the text responses of large language models (LLMs) are grounded in the source materials provided by the users. Ungroundedness describes instances where the LLMs produce information that is non-factual or inaccurate according to what was present in the source materials. See [Groundedness detection](./concepts/groundedness.md) to learn more. ## January 2024 @@ -56,14 +55,14 @@ The Azure AI Content Safety service is now generally available through the follo ## November 2023 -### Jailbreak risk and Protected material detection (preview) +### Jailbreak risk and protected material detection (preview) -The new Jailbreak risk detection and Protected material detection APIs let you mitigate some of the risks when using generative AI. +The new Jailbreak risk detection and protected material detection APIs let you mitigate some of the risks when using generative AI. - Jailbreak risk detection scans text for the risk of a [jailbreak attack](./concepts/jailbreak-detection.md) on a Large Language Model. [Quickstart](./quickstart-jailbreak.md) - Protected material text detection scans AI-generated text for known text content (for example, song lyrics, articles, recipes, selected web content). [Quickstart](./quickstart-protected-material.md) -Jailbreak risk and Protected material detection are only available in select regions. See [Region availability](/azure/ai-services/content-safety/overview#region-availability). +Jailbreak risk and protected material detection are only available in select regions. See [Region availability](/azure/ai-services/content-safety/overview#region-availability). ## October 2023 @@ -72,11 +71,11 @@ Jailbreak risk and Protected material detection are only available in select reg The Azure AI Content Safety service is now generally available as a cloud service. - The service is available in many more Azure regions. See the [Overview](./overview.md) for a list. - The return formats of the Analyze APIs have changed. See the [Quickstarts](./quickstart-text.md) for the latest examples. -- The names and return formats of several APIs have changed. See the [Migration guide](./how-to/migrate-to-general-availability.md) for a full list of breaking changes. Other guides and quickstarts now reflect the GA version. +- The names and return formats of several other APIs have changed. See the [Migration guide](./how-to/migrate-to-general-availability.md) for a full list of breaking changes. Other guides and quickstarts now reflect the GA version. ### Azure AI Content Safety Java and JavaScript SDKs -The Azure AI Content Safety service is now available through Java and JavaScript SDKs. The SDKs are available on [Maven](https://central.sonatype.com/artifact/com.azure/azure-ai-contentsafety) and [npm](https://www.npmjs.com/package/@azure-rest/ai-content-safety). Follow a [quickstart](./quickstart-text.md) to get started. +The Azure AI Content Safety service is now available through Java and JavaScript SDKs. The SDKs are available on [Maven](https://central.sonatype.com/artifact/com.azure/azure-ai-contentsafety) and [npm](https://www.npmjs.com/package/@azure-rest/ai-content-safety) respectively. Follow a [quickstart](./quickstart-text.md) to get started. ## July 2023 diff --git a/articles/ai-services/openai/how-to/assistant-functions.md b/articles/ai-services/openai/how-to/assistant-functions.md index 7add4f1dfde..fba65bee900 100644 --- a/articles/ai-services/openai/how-to/assistant-functions.md +++ b/articles/ai-services/openai/how-to/assistant-functions.md @@ -6,9 +6,9 @@ services: cognitive-services manager: nitinme ms.service: azure-ai-openai ms.topic: how-to -ms.date: 05/22/2024 -author: mrbullwinkle -ms.author: mbullwin +ms.date: 09/04/2024 +author: aahill +ms.author: aahi recommendations: false --- @@ -29,8 +29,7 @@ To use all features of function calling including parallel functions, you need t ### API Versions -- `2024-02-15-preview` -- `2024-05-01-preview` +API versions starting with `2024-02-15-preview`. ## Example function definition @@ -46,40 +45,27 @@ from openai import AzureOpenAI client = AzureOpenAI( api_key=os.getenv("AZURE_OPENAI_API_KEY"), - api_version="2024-02-15-preview", + api_version="2024-07-01-preview", azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT") ) assistant = client.beta.assistants.create( + name="Weather Bot", instructions="You are a weather bot. Use the provided functions to answer questions.", - model="gpt-4-1106-preview", #Replace with model deployment name + model="gpt-4", #Replace with model deployment name tools=[{ "type": "function", "function": { - "name": "getCurrentWeather", + "name": "get_weather", "description": "Get the weather in location", "parameters": { "type": "object", "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]} + "location": {"type": "string", "description": "The city name, for example San Francisco"} }, "required": ["location"] } } - }, { - "type": "function", - "function": { - "name": "getNickname", - "description": "Get the nickname of a city", - "parameters": { - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - }, - "required": ["location"] - } - } }] ) ``` @@ -90,40 +76,25 @@ assistant = client.beta.assistants.create( > With Azure OpenAI the `model` parameter requires model deployment name. If your model deployment name is different than the underlying model name then you would adjust your code to ` "model": "{your-custom-model-deployment-name}"`. ```console -curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/assistants?api-version=2024-02-15-preview \ +curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/assistants?api-version=2024-07-01-preview \ -H "api-key: $AZURE_OPENAI_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "instructions": "You are a weather bot. Use the provided functions to answer questions.", - "tools": [{ - "type": "function", - "function": { - "name": "getCurrentWeather", - "description": "Get the weather in location", - "parameters": { - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]} - }, - "required": ["location"] - } - } - }, - { + tools=[{ "type": "function", - "function": { - "name": "getNickname", - "description": "Get the nickname of a city", - "parameters": { - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"} - }, - "required": ["location"] - } - } - }], + "function": { + "name": "get_weather", + "description": "Get the weather in location", + "parameters": { + "type": "object", + "properties": { + "location": {"type": "string", "description": "The city name, for example San Francisco"} + }, + "required": ["location"] + } + } + }], "model": "gpt-4-1106-preview" }' ``` @@ -149,18 +120,10 @@ When you initiate a **Run** with a user Message that triggers the function, the "id": "call_abc123", "type": "function", "function": { - "name": "getCurrentWeather", - "arguments": "{\"location\":\"San Francisco\"}" + "name": "get_weather", + "arguments": "{\"location\":\"Seattle\"}" } }, - { - "id": "call_abc456", - "type": "function", - "function": { - "name": "getNickname", - "arguments": "{\"location\":\"Los Angeles\"}" - } - } ] } }, @@ -169,50 +132,66 @@ When you initiate a **Run** with a user Message that triggers the function, the ## Submitting function outputs -You can then complete the **Run** by submitting the tool output from the function(s) you call. Pass the `tool_call_id` referenced in the `required_action` object above to match output to each function call. +You can then complete the **Run** by submitting the tool output from the function(s) you call. Pass the `tool_call_id` referenced in the `required_action` object to match output to each function call. # [Python 1.x](#tab/python) ```python -from openai import AzureOpenAI - -client = AzureOpenAI( - api_key=os.getenv("AZURE_OPENAI_API_KEY"), - api_version="2024-02-15-preview", - azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT") - ) - -run = client.beta.threads.runs.submit_tool_outputs( - thread_id=thread.id, - run_id=run.id, - tool_outputs=[ - { - "tool_call_id": call_ids[0], - "output": "22C", - }, - { - "tool_call_id": call_ids[1], - "output": "LA", - }, - ] -) +# Example function +def get_weather(): + return "It's 80 degrees F and slightly cloudy." + +# Define the list to store tool outputs +tool_outputs = [] + +# Loop through each tool in the required action section +for tool in run.required_action.submit_tool_outputs.tool_calls: + # get data from the weather function + if tool.function.name == "get_weather": + weather = get_weather() + tool_outputs.append({ + "tool_call_id": tool.id, + "output": weather + }) + +# Submit all tool outputs at once after collecting them in a list +if tool_outputs: + try: + run = client.beta.threads.runs.submit_tool_outputs_and_poll( + thread_id=thread.id, + run_id=run.id, + tool_outputs=tool_outputs + ) + print("Tool outputs submitted successfully.") + except Exception as e: + print("Failed to submit tool outputs:", e) +else: + print("No tool outputs to submit.") + +if run.status == 'completed': + print("run status: ", run.status) + messages = client.beta.threads.messages.list(thread_id=thread.id) + print(messages.to_json(indent=2)) + +else: + print("run status: ", run.status) + print (run.last_error.message) ``` # [REST](#tab/rest) +In the following example, replace `output` with the output of the function you want to use. + ```console -curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/threads/thread_abc123/runs/run_123/submit_tool_outputs?api-version=2024-02-15-preview \ +curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/threads/thread_abc123/runs/run_123/submit_tool_outputs?api-version=2024-07-01-preview \ -H "Content-Type: application/json" \ - -H "api-key: $AZURE_OPENAI_API_KEY" \ + -H "api-key: 851c6e0b83744d8c8fc2a07eab098376" \ -d '{ "tool_outputs": [{ - "tool_call_id": "call_abc123", - "output": "{"temperature": "22", "unit": "celsius"}" - }, { - "tool_call_id": "call_abc456", - "output": "{"nickname": "LA"}" + "tool_call_id": "call_123", + "output": "{\"60 degrees F and raining\"}" }] }' ``` diff --git a/articles/machine-learning/how-to-inference-onnx-automl-image-models.md b/articles/machine-learning/how-to-inference-onnx-automl-image-models.md index cb12b4ea4ad..c73f793d4d9 100644 --- a/articles/machine-learning/how-to-inference-onnx-automl-image-models.md +++ b/articles/machine-learning/how-to-inference-onnx-automl-image-models.md @@ -333,7 +333,7 @@ Every ONNX model has a predefined set of input and output formats. # [Multi-class image classification](#tab/multi-class) -This example applies the model trained on the [fridgeObjects](https://cvbp-secondary.z19.web.core.windows.net/datasets/image_classification/fridgeObjects.zip) dataset with 134 images and 4 classes/labels to explain ONNX model inference. For more information on training an image classification task, see the [multi-class image classification notebook](https://github.com/Azure/azureml-examples/tree/main/sdk/python/jobs/automl-standalone-jobs/automl-image-classification-multiclass-task-fridge-items). +This example applies the model trained on the [fridgeObjects](https://automlsamplenotebookdata.blob.core.windows.net/image-object-detection/odFridgeObjects.zip) dataset with 134 images and 4 classes/labels to explain ONNX model inference. For more information on training an image classification task, see the [multi-class image classification notebook](https://github.com/Azure/azureml-examples/tree/main/sdk/python/jobs/automl-standalone-jobs/automl-image-classification-multiclass-task-fridge-items). ### Input format @@ -354,7 +354,7 @@ The output is an array of logits for all the classes/labels. # [Multi-label image classification](#tab/multi-label) -This example uses the model trained on the [multi-label fridgeObjects dataset](https://cvbp-secondary.z19.web.core.windows.net/datasets/image_classification/multilabelFridgeObjects.zip) with 128 images and 4 classes/labels to explain ONNX model inference. For more information on model training for multi-label image classification, see the [multi-label image classification notebook](https://github.com/Azure/azureml-examples/tree/main/sdk/python/jobs/automl-standalone-jobs/automl-image-classification-multilabel-task-fridge-items). +This example uses the model trained on the [multi-label fridgeObjects dataset](https://automlsamplenotebookdata.blob.core.windows.net/image-classification/multilabelFridgeObjects.zip) with 128 images and 4 classes/labels to explain ONNX model inference. For more information on model training for multi-label image classification, see the [multi-label image classification notebook](https://github.com/Azure/azureml-examples/tree/main/sdk/python/jobs/automl-standalone-jobs/automl-image-classification-multilabel-task-fridge-items). ### Input format @@ -375,8 +375,7 @@ The output is an array of logits for all the classes/labels. # [Object detection with Faster R-CNN or RetinaNet](#tab/object-detect-cnn) - -This object detection example uses the model trained on the [fridgeObjects detection dataset](https://cvbp-secondary.z19.web.core.windows.net/datasets/object_detection/odFridgeObjects.zip) of 128 images and 4 classes/labels to explain ONNX model inference. This example trains Faster R-CNN models to demonstrate inference steps. For more information on training object detection models, see the [object detection notebook](https://github.com/Azure/azureml-examples/tree/main/sdk/python/jobs/automl-standalone-jobs/automl-image-object-detection-task-fridge-items). +This object detection example uses the model trained on the [fridgeObjects detection dataset](https://automlsamplenotebookdata.blob.core.windows.net/image-object-detection/odFridgeObjects.zip) of 128 images and 4 classes/labels to explain ONNX model inference. This example trains Faster R-CNN models to demonstrate inference steps. For more information on training object detection models, see the [object detection notebook](https://github.com/Azure/azureml-examples/tree/main/sdk/python/jobs/automl-standalone-jobs/automl-image-object-detection-task-fridge-items). ### Input format @@ -408,7 +407,7 @@ The following table describes boxes, labels, and scores returned for each sample # [Object detection with YOLO](#tab/object-detect-yolo) -This object detection example uses the model trained on the [fridgeObjects detection dataset](https://cvbp-secondary.z19.web.core.windows.net/datasets/object_detection/odFridgeObjects.zip) of 128 images and 4 classes/labels to explain ONNX model inference. This example trains YOLO models to demonstrate inference steps. For more information on training object detection models, see the [object detection notebook](https://github.com/Azure/azureml-examples/tree/main/sdk/python/jobs/automl-standalone-jobs/automl-image-object-detection-task-fridge-items). +This object detection example uses the model trained on the [fridgeObjects detection dataset](https://automlsamplenotebookdata.blob.core.windows.net/image-object-detection/odFridgeObjects.zip) of 128 images and 4 classes/labels to explain ONNX model inference. This example trains YOLO models to demonstrate inference steps. For more information on training object detection models, see the [object detection notebook](https://github.com/Azure/azureml-examples/tree/main/sdk/python/jobs/automl-standalone-jobs/automl-image-object-detection-task-fridge-items). ### Input format @@ -430,7 +429,7 @@ Each cell in the list indicates box detections of a sample with shape `(n_boxes, # [Instance segmentation](#tab/instance-segmentation) -For this instance segmentation example, you use the Mask R-CNN model that has been trained on the [fridgeObjects dataset](https://cvbp-secondary.z19.web.core.windows.net/datasets/object_detection/odFridgeObjectsMask.zip) with 128 images and 4 classes/labels to explain ONNX model inference. For more information on training of the instance segmentation model, see the [instance segmentation notebook](https://github.com/Azure/azureml-examples/tree/main/sdk/python/jobs/automl-standalone-jobs/automl-image-instance-segmentation-task-fridge-items). +For this instance segmentation example, you use the Mask R-CNN model that has been trained on the [fridgeObjects dataset](https://automlsamplenotebookdata.blob.core.windows.net/image-object-detection/odFridgeObjects.zip) with 128 images and 4 classes/labels to explain ONNX model inference. For more information on training of the instance segmentation model, see the [instance segmentation notebook](https://github.com/Azure/azureml-examples/tree/main/sdk/python/jobs/automl-standalone-jobs/automl-image-instance-segmentation-task-fridge-items). >[!IMPORTANT] > Only Mask R-CNN is supported for instance segmentation tasks. The input and output formats are based on Mask R-CNN only. diff --git a/articles/machine-learning/v1/how-to-inference-onnx-automl-image-models.md b/articles/machine-learning/v1/how-to-inference-onnx-automl-image-models.md index a99b207edbc..08260331398 100644 --- a/articles/machine-learning/v1/how-to-inference-onnx-automl-image-models.md +++ b/articles/machine-learning/v1/how-to-inference-onnx-automl-image-models.md @@ -266,7 +266,7 @@ Every ONNX model has a predefined set of input and output formats. # [Multi-class image classification](#tab/multi-class) -This example applies the model trained on the [fridgeObjects](https://cvbp-secondary.z19.web.core.windows.net/datasets/image_classification/fridgeObjects.zip) dataset with 134 images and 4 classes/labels to explain ONNX model inference. For more information on training an image classification task, see the [multi-class image classification notebook](https://github.com/Azure/azureml-examples/tree/v1-archive/v1/python-sdk/tutorials/automl-with-azureml/image-classification-multiclass). +This example applies the model trained on the [fridgeObjects](https://automlsamplenotebookdata.blob.core.windows.net/image-object-detection/odFridgeObjects.zip) dataset with 134 images and 4 classes/labels to explain ONNX model inference. For more information on training an image classification task, see the [multi-class image classification notebook](https://github.com/Azure/azureml-examples/tree/v1-archive/v1/python-sdk/tutorials/automl-with-azureml/image-classification-multiclass). ### Input format @@ -287,7 +287,7 @@ The output is an array of logits for all the classes/labels. # [Multi-label image classification](#tab/multi-label) -This example uses the model trained on the [multi-label fridgeObjects dataset](https://cvbp-secondary.z19.web.core.windows.net/datasets/image_classification/multilabelFridgeObjects.zip) with 128 images and 4 classes/labels to explain ONNX model inference. For more information on model training for multi-label image classification, see the [multi-label image classification notebook](https://github.com/Azure/azureml-examples/tree/v1-archive/v1/python-sdk/tutorials/automl-with-azureml/image-classification-multilabel). +This example uses the model trained on the [multi-label fridgeObjects dataset](https://automlsamplenotebookdata.blob.core.windows.net/image-classification/multilabelFridgeObjects.zip) with 128 images and 4 classes/labels to explain ONNX model inference. For more information on model training for multi-label image classification, see the [multi-label image classification notebook](https://github.com/Azure/azureml-examples/tree/v1-archive/v1/python-sdk/tutorials/automl-with-azureml/image-classification-multilabel). ### Input format @@ -309,7 +309,7 @@ The output is an array of logits for all the classes/labels. # [Object detection with Faster R-CNN or RetinaNet](#tab/object-detect-cnn) -This object detection example uses the model trained on the [fridgeObjects detection dataset](https://cvbp-secondary.z19.web.core.windows.net/datasets/object_detection/odFridgeObjects.zip) of 128 images and 4 classes/labels to explain ONNX model inference. This example trains Faster R-CNN models to demonstrate inference steps. For more information on training object detection models, see the [object detection notebook](https://github.com/Azure/azureml-examples/tree/v1-archive/v1/python-sdk/tutorials/automl-with-azureml/image-object-detection). +This object detection example uses the model trained on the [fridgeObjects detection dataset](https://automlsamplenotebookdata.blob.core.windows.net/image-object-detection/odFridgeObjects.zip) of 128 images and 4 classes/labels to explain ONNX model inference. This example trains Faster R-CNN models to demonstrate inference steps. For more information on training object detection models, see the [object detection notebook](https://github.com/Azure/azureml-examples/tree/v1-archive/v1/python-sdk/tutorials/automl-with-azureml/image-object-detection). ### Input format @@ -341,7 +341,7 @@ The following table describes boxes, labels and scores returned for each sample # [Object detection with YOLO](#tab/object-detect-yolo) -This object detection example uses the model trained on the [fridgeObjects detection dataset](https://cvbp-secondary.z19.web.core.windows.net/datasets/object_detection/odFridgeObjects.zip) of 128 images and 4 classes/labels to explain ONNX model inference. This example trains YOLO models to demonstrate inference steps. For more information on training object detection models, see the [object detection notebook](https://github.com/Azure/azureml-examples/tree/v1-archive/v1/python-sdk/tutorials/automl-with-azureml/image-object-detection). +This object detection example uses the model trained on the [fridgeObjects detection dataset](https://automlsamplenotebookdata.blob.core.windows.net/image-object-detection/odFridgeObjects.zip) of 128 images and 4 classes/labels to explain ONNX model inference. This example trains YOLO models to demonstrate inference steps. For more information on training object detection models, see the [object detection notebook](https://github.com/Azure/azureml-examples/tree/v1-archive/v1/python-sdk/tutorials/automl-with-azureml/image-object-detection). ### Input format @@ -363,7 +363,7 @@ Each cell in the list indicates box detections of a sample with shape `(n_boxes, # [Instance segmentation](#tab/instance-segmentation) -For this instance segmentation example, you use the Mask R-CNN model that has been trained on the [fridgeObjects dataset](https://cvbp-secondary.z19.web.core.windows.net/datasets/object_detection/odFridgeObjectsMask.zip) with 128 images and 4 classes/labels to explain ONNX model inference. For more information on training of the instance segmentation model, see the [instance segmentation notebook](https://github.com/Azure/azureml-examples/tree/v1-archive/v1/python-sdk/tutorials/automl-with-azureml/image-instance-segmentation). +For this instance segmentation example, you use the Mask R-CNN model that has been trained on the [fridgeObjects dataset](https://automlsamplenotebookdata.blob.core.windows.net/image-object-detection/odFridgeObjects.zip) with 128 images and 4 classes/labels to explain ONNX model inference. For more information on training of the instance segmentation model, see the [instance segmentation notebook](https://github.com/Azure/azureml-examples/tree/v1-archive/v1/python-sdk/tutorials/automl-with-azureml/image-instance-segmentation). >[!IMPORTANT] > Only Mask R-CNN is supported for instance segmentation tasks. The input and output formats are based on Mask R-CNN only. diff --git a/docfx.json b/docfx.json index 402f089d721..eda7a84743a 100644 --- a/docfx.json +++ b/docfx.json @@ -82,6 +82,13 @@ ], "src": "breadcrumb/azure-ai", "dest": "breadcrumb/azure-ai" + }, + { + "files": [ + "zone-pivot-groups.yml" + ], + "src": "zone-pivots", + "dest": "zone-pivots/azure-ai/" } ], "resource": [ @@ -260,7 +267,8 @@ "Certification" ], "uhfHeaderId": "azure", - "ms.suite": "office" + "ms.suite": "office", + "zone_pivot_group_filename": "zone-pivots/azure-ai/zone-pivot-groups.json" }, "fileMetadata": { "author": { diff --git a/zone-pivots/zone-pivot-groups.yml b/zone-pivots/zone-pivot-groups.yml new file mode 100644 index 00000000000..aaa89520f22 --- /dev/null +++ b/zone-pivots/zone-pivot-groups.yml @@ -0,0 +1,822 @@ +### YamlMime:ZonePivotGroups +groups: +- id: programming-languages-portal-cli-ps +# Owner: eur + title: Programming languages + prompt: Choose a programming language or tool + pivots: + - id: azportal + title: Azure portal + - id: azcli + title: Azure CLI + - id: azpowershell + title: Azure PowerShell +- id: programming-languages-set-twenty-eight +# Owner: aahi + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python +# Service-specific groups +- id: azure-ai-model-catalog-samples-chat +# Owner: santiagxf + title: Programing languages + prompt: Choose a tool or API + pivots: + - id: programming-language-python + title: Python + - id: programming-language-javascript + title: JavaScript + - id: programming-language-csharp + title: C# + - id: programming-language-rest + title: REST +- id: programming-languages-set-conmod +# Owner: pafarley + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-java + title: Java + - id: programming-language-python + title: Python + - id: programming-language-rest-api + title: REST API +- id: programming-languages-content-safety +# Owner: pafarley + title: Programming languages + prompt: Choose a platform + pivots: + - id: programming-language-rest + title: REST + - id: programming-language-csharp + title: C# + - id: programming-language-python + title: Python + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript +- id: cloud-location + # Owner: lajanuar + title: Workflow + prompt: Choose a workflow + pivots: + - id: workflow-onedrive + title: OneDrive + - id: workflow-sharepoint + title: SharePoint +- id: immersive-reader-how-to-guides +# Owner: erhopf + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-javascript + title: Node.js + - id: programming-language-python + title: Python + - id: programming-language-android + title: Android + - id: programming-language-ios + title: iOS +# Owner: mbullwin +- id: programming-languages-set-luis + title: Programming languages + prompt: Make a selection + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python + - id: rest-api + title: REST API +- id: programming-languages-set-one + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-go + title: Go + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python +- id: openai-quickstart-assistants + title: Programming languages + prompt: Choose your preferred usage method + pivots: + - id: programming-language-studio + title: Azure OpenAI Studio + - id: programming-language-ai-studio + title: AI Studio (Preview) + - id: programming-language-csharp + title: C# + - id: programming-language-python + title: Python + - id: programming-language-javascript + title: JavaScript + - id: rest-api + title: REST +# Owner: mbullwin +- id: openai-quickstart-new + title: Programming languages + prompt: Choose your preferred usage method + pivots: + - id: programming-language-studio + title: Studio + - id: programming-language-csharp + title: C# + - id: programming-language-go + title: Go + - id: programming-language-java + title: Java + - id: programming-language-spring + title: Spring + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python + - id: programming-language-powershell + title: PowerShell + - id: rest-api + title: REST +- id: openai-quickstart-dall-e + title: Programming languages + prompt: Choose your preferred usage method + pivots: + - id: programming-language-studio + title: Studio + - id: rest-api + title: REST + - id: programming-language-python + title: Python + - id: programming-language-csharp + title: C# + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-go + title: Go + - id: programming-language-powershell + title: PowerShell +# Owner: pafarley +- id: openai-quickstart-gpt-v + title: Programming languages + prompt: Choose your preferred usage method + pivots: + - id: programming-language-studio + title: Studio + - id: programming-language-python + title: Python + - id: rest-api + title: REST +# Owner: mbullwin +- id: openai-use-your-data + title: Programming languages + prompt: Choose your preferred usage method + pivots: + - id: programming-language-studio + title: Studio + - id: programming-language-csharp + title: C# + - id: programming-language-spring + title: Spring + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python + - id: programming-language-go + title: Go + - id: rest-api + title: REST + - id: programming-language-powershell + title: PowerShell +# Owner: pafarley +- id: openai-whisper + title: Programming languages + prompt: Choose your preferred usage method + pivots: + - id: rest-api + title: REST + - id: programming-language-powershell + title: PowerShell + - id: programming-language-python + title: Python +# Owner: diberry +- id: programming-languages-set-six +# Owner: diberry + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python +- id: programming-languages-reference-ai-services +# Owner: laujan + title: Programming languages + prompt: Choose a programming language or tool + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-cpp + title: C++ + - id: programming-language-go + title: Go + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-objectivec + title: Objective-C + - id: programming-language-python + title: Python + - id: programming-language-ruby + title: Ruby + - id: programming-language-swift + title: Swift +- id: speech-cli-rest +# Owner: eur + title: Programming languages + prompt: Choose a tool or API + pivots: + - id: rest-api + title: REST + - id: speech-cli + title: CLI +- id: programming-languages-speech-sdk-cli +# Owner: eur + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-cpp + title: C++ + - id: programming-language-go + title: Go + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-objectivec + title: Objective-C + - id: programming-language-python + title: Python + - id: programming-language-swift + title: Swift + - id: programming-language-cli + title: CLI +- id: programming-languages-speech-services +# Owner: eur + title: Programming languages + prompt: Choose a programming language or tool + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-cpp + title: C++ + - id: programming-language-go + title: Go + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-objectivec + title: Objective-C + - id: programming-language-python + title: Python + - id: programming-language-swift + title: Swift + - id: programming-language-cli + title: CLI + - id: programming-language-rest + title: REST +- id: programming-languages-set-thirteen + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-cpp + title: C++ + - id: programming-language-java + title: Java +- id: programming-languages-speech-services-studio +# Owner: eur + title: Programming languages + prompt: Choose a programming language or tool + pivots: + - id: ai-studio + title: AI Studio + - id: programming-language-csharp + title: C# + - id: programming-language-cpp + title: C++ + - id: programming-language-go + title: Go + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python + - id: programming-language-swift + title: Swift + - id: programming-language-cli + title: CLI + - id: programming-language-rest + title: REST +- id: programming-languages-set-twenty-one + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-java + title: Java +- id: programming-languages-set-two +# Owner: erhopf + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-cpp + title: C++ + - id: programming-language-java + title: Java + - id: programming-language-python + title: Python + - id: programming-language-more + title: More languages... +- id: programming-languages-set-three +# Owner: erhopf + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-cpp + title: C++ + - id: programming-language-go + title: Go + - id: programming-language-java + title: Java + - id: programming-language-python + title: Python +- id: speech-studio-cli-rest +# Owner: eur + title: Programming languages + prompt: Choose a tool or API + pivots: + - id: speech-studio + title: Speech Studio + - id: rest-api + title: REST + - id: speech-cli + title: CLI +- id: programming-languages-set-nineteen + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-cpp + title: C++ + - id: programming-language-java + title: Java + - id: programming-language-python + title: Python + - id: programming-language-objectivec + title: Objective-C +- id: programming-languages-ai-services +# Owner: eur + title: Programming languages + prompt: Choose a programming language or tool + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-cpp + title: C++ + - id: programming-language-go + title: Go + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-objectivec + title: Objective-C + - id: programming-language-python + title: Python + - id: programming-language-swift + title: Swift +- id: programming-languages-speech-services-nomore-variant +# Owner: erhopf + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-cpp + title: C++ + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python + - id: programming-language-objectivec + title: Objective-C +- id: acs-js-csharp-python + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python +- id: programming-languages-set-two-with-js-spx +# Owner: erhopf + title: Programming languages + prompt: Choose a programming language or CLI + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-cpp + title: C++ + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python + - id: programmer-tool-spx + title: CLI +- id: programming-languages-csharp-python +# Owner: eur + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-python + title: Python +- id: speech-studio-rest +# Owner: eur + title: Programming languages + prompt: Choose a tool or API + pivots: + - id: speech-studio + title: Speech Studio + - id: rest-api + title: REST +- id: programming-languages-set-translator-sdk +# Owner: lajanuar + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: "C#: Visual Studio" + - id: programming-language-java + title: "Java: Gradle" + - id: programming-language-javascript + title: "JavaScript: Node.js" + - id: programming-language-python + title: Python +- id: azure-ai-model-catalog-samples-embeddings +# Owner: santiagxf + title: Programing languages + prompt: Choose a tool or API + pivots: + - id: programming-language-python + title: Python + - id: programming-language-javascript + title: JavaScript + - id: programming-language-rest + title: REST +- id: aml-control-methods + # Owner: gopalv + title: Azure Machine Learning control plane + prompt: Choose an Azure Machine Learning control plane interface + pivots: + - id: py-sdk + title: Python SDK + - id: cli + title: Azure CLI +- id: anomaly-detector-quickstart-multivariate + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python + - id: programming-language-java + title: Java +- id: anomaly-detector-quickstart + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python + - id: rest-api + title: REST +# Owner: mbullwin +- id: programming-languages-computer-vision + title: Programming languages + prompt: Choose a programming language. + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-python + title: Python + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-rest-api + title: REST API +- id: programming-languages-ocr + title: Programming languages + prompt: Choose a programming language. + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-python + title: Python + - id: programming-language-javascript + title: JavaScript + - id: programming-language-rest-api + title: REST API + - id: vision-studio + title: Vision Studio +- id: programming-languages-set-face + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-python + title: Python + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-rest-api + title: REST API +- id: programming-languages-computer-vision-40 + title: Programming languages + prompt: Choose a programming language. + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-python + title: Python + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-rest-api + title: REST API + - id: vision-studio + title: Vision Studio +- id: programming-languages-vision-40-sdk + title: Programming languages + prompt: Choose a programming language. + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-python + title: Python + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript +- id: programming-languages-set-cusvis +# Owner: pafarley + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-go + title: Go + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python + - id: programming-language-rest-api + title: REST API +- id: programming-languages-set-formre +# Owner: pafarley + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python + - id: programming-language-rest-api + title: REST API +- id: programming-languages-set-twenty + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-nodejs + title: Node.js + - id: programming-language-java-android + title: Java (Android) + - id: programming-language-kotlin + title: Kotlin (Android) + - id: programming-language-swift + title: Swift (iOS) +- id: usage-custom-language-features +# Owner aahill + title: Usage methods + prompt: Choose your preferred usage method + pivots: + - id: language-studio + title: Language Studio + - id: rest-api + title: REST API +- id: programming-languages-text-analytics + title: Programming languages + prompt: Choose one of the client library languages or REST API. + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-python + title: Python + - id: programming-language-javascript + title: JavaScript + - id: programming-language-java + title: Java + - id: rest-api + title: REST API +- id: programming-languages-metrics-monitor + title: Programming languages + prompt: Choose a programming language. + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-python + title: Python + - id: programming-language-java + title: Java + - id: programming-language-javascript + title: JavaScript + - id: programming-language-rest-api + title: REST API +- id: openai-prompt + title: API Options + prompt: API options + pivots: + - id: programming-language-chat-completions + title: Chat Completion + - id: programming-language-completions + title: Completion +# Owner: mbullwin +- id: openai-fine-tuning-batch + title: Programming languages + prompt: Choose your preferred usage method + pivots: + - id: programming-language-ai-studio + title: AI Studio + - id: programming-language-python + title: Python + - id: rest-api + title: REST +# Owner: mbullwin +- id: openai-create-resource + title: Programming languages + prompt: Choose your preferred resource creation method + pivots: + - id: web-portal + title: Portal + - id: cli + title: CLI + - id: ps + title: PowerShell +# Owner: mbullwin +- id: openai-fine-tuning-new + title: Programming languages + prompt: Choose your preferred fine-tuning method + pivots: + - id: programming-language-studio + title: Studio + - id: programming-language-ai-studio + title: AI Studio (Preview) + - id: programming-language-python + title: Python + - id: rest-api + title: REST +# Owner: mbullwin +- id: URL-test-interface + title: URL Test tool + prompt: Choose one of the following + pivots: + - id: url-test-tool-curl + title: cURL + - id: url-test-tool-visual-studio-code-rest-client-extension + title: Visual Studio Code REST Client Extension +#Owner: kraigb +- id: qnamaker-quickstart + title: Programming languages + prompt: Choose a programming language + pivots: + - id: rest + title: REST + - id: programming-language-csharp + title: C# + - id: programming-language-javascript + title: JavaScript + - id: programming-language-python + title: Python + - id: programming-language-java + title: Java + # Owner: mbullwin +- id: programming-languages-set-nine + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-cpp + title: C++ +- id: programming-languages-voice-assistants + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-go + title: Go + - id: programming-language-java + title: Java + - id: programming-language-more + title: More languages... +- id: custom-qna-quickstart + title: Programming languages + prompt: Choose a programming language + pivots: + - id: studio + title: Language Studio + - id: rest + title: REST + - id: programming-language-csharp + title: C# + - id: programming-language-python + title: Python +# Owner: farazgis +- id: programming-languages-document-sdk + # Owner: lajanuar + title: Programming languages + prompt: Choose a programming language + pivots: + - id: programming-language-csharp + title: C# + - id: programming-language-python + title: Python +# Owner: mbullwin +- id: openai-embeddings + title: Programming languages + prompt: Choose your preferred usage method + pivots: + - id: programming-language-python + title: Python + - id: programming-language-powershell + title: PowerShell \ No newline at end of file