--- title: "Describe images with local AI in C# | Nutrient .NET SDK" canonical_url: "https://www.nutrient.io/guides/dotnet/csharp/extraction/describe-image-with-local-ai/" md_url: "https://www.nutrient.io/guides/dotnet/csharp/extraction/describe-image-with-local-ai.md" last_updated: "2026-10-08T00:00:00.000Z" description: "Generate accessible image descriptions using local AI models with Nutrient .NET SDK." --- # Generating image descriptions using local AI Use local AI image description when you need privacy, cost control, or offline operation. Common use cases include: - On-premises accessibility workflows - Medical or regulated environments with local-only data handling - Secure networks where external APIs are restricted - High-volume processing without per-image API fees - Offline-capable applications This guide uses a local OpenAI-compatible VLM endpoint with Nutrient Vision API. [Download sample](https://www.nutrient.io/downloads/samples/csharp/describe-image-with-local-ai.zip) ## How Nutrient helps Nutrient.NET SDK handles local VLM integration, endpoint configuration, and request/response processing. The SDK handles: - OpenAI-compatible endpoint formatting and communication - Image encoding and multimodal payload construction - Model parameters such as temperature and max tokens - Local server and model runtime failure handling ## Complete implementation This example generates image descriptions using a local AI endpoint: ```csharp using Nutrient; ``` ## Opening the image file and configuring the local server Open the image with a [using statement](https://learn.microsoft.com/dotnet/csharp/language-reference/statements/using) and configure local endpoint settings if needed. In this sample: - The SDK supports PNG, JPEG, GIF, BMP, and TIFF. - The default endpoint is `http://localhost:1234/v1`. - The default model is `qwen/qwen3-vl-4b`. - The custom VLM API settings override defaults. ```csharp try { using Document document = Document.Open("input_photo.png"); // Optional: Configure the VLM API endpoint settings // These settings are customizable based on your VLM provider var vlmSettings = document.Settings.CustomVlmApiSettings; vlmSettings.ApiEndpoint = "http://localhost:1234/v1"; vlmSettings.Model = "qwen/qwen3-vl-4b"; ``` ## Creating a vision instance Create a vision instance with `Vision.Set(document)`. Before calling vision methods, ensure: - The local server is running. - A vision-capable model is loaded. - The configured endpoint is reachable. ```csharp var vision = Vision.Set(document); ``` ## Generating the description Call `vision.Describe()` to generate a natural language description. The SDK handles image encoding, request construction, and response parsing: ```csharp string description = vision.Describe(); ``` ## Outputting the description Print the description for review, or store it in your application. Common destinations include: - Database fields - JSON output files - HTML `alt` attributes ```csharp Console.WriteLine("Image description:"); Console.WriteLine(description); } catch (NutrientException e) { Console.Error.WriteLine($"Error: {e.Message}"); Environment.Exit(1); } ``` ## Understanding the output `Describe()` returns natural language text generated by the local model. Descriptions are typically: - **Concise** — Focused on key subjects and details, often one to three sentences - **Accessible** — Suitable for users who rely on screen readers - **Accurate** — Based on visible content only - **Model-dependent quality** — Quality varies by model architecture and size Use this output for accessibility metadata, image search, and document workflows, all with local processing. ## Configuring the VLM API endpoint Vision API uses OpenAI-compatible endpoints. Configure the custom VLM API settings if your setup differs from defaults: - `ApiEndpoint` — Base URL for the OpenAI-compatible API (default: `http://localhost:1234/v1`) - `ApiKey` — API key for secured deployments (optional on many local servers) - `Model` — Model identifier (default: `qwen/qwen3-vl-4b`) - `Temperature` — Creativity control (`0.0` deterministic, `1.0` varied phrasing) - `MaxTokens` — Response token limit (`-1` unlimited) **Local server setup examples**: - **LM Studio** — Start server with vision model loaded, default endpoint `http://localhost:1234/v1` - **Ollama** — Run `ollama serve` with vision model, default endpoint `http://localhost:11434/v1` - **vLLM** — Launch with `--api-key` flag for authentication, custom port configuration The SDK handles request formatting and response parsing for local endpoints. ## Error handling The SDK throws a `NutrientException` when vision operations fail. Common failure scenarios include: - The input image can't be read due to path, permission, or format issues - The local VLM server isn't running or reachable - No compatible vision model is loaded - Responses time out on large images or heavy models - Available CPU/GPU memory is insufficient - Endpoint or authentication settings are invalid In production code: - Catch `NutrientException`. - Return a clear error message. - Log failure details for debugging. - Add retry logic for transient local server issues. ## Conclusion Use this workflow to generate image descriptions with local AI: 1. Open the image file with a `using` statement for automatic resource cleanup. 2. The SDK supports multiple image formats, including PNG, JPEG, GIF, BMP, and TIFF. 3. Vision API uses OpenAI-compatible endpoints for local VLM servers by default. 4. Default configuration connects to `http://localhost:1234/v1` with model `qwen/qwen3-vl-4b`. 5. Supported local VLM servers include LM Studio, Ollama, vLLM, and custom inference servers. 6. Optionally configure custom server settings through `Settings.CustomVlmApiSettings`. 7. Create a vision instance with `Vision.Set()` bound to the document for local AI processing. 8. Generate the description with `vision.Describe()`, which sends the image to the local server endpoint and returns natural language text. 9. The SDK encodes image data, constructs OpenAI-compatible multimodal requests, and parses responses automatically. 10. Generated descriptions are concise (1–3 sentences), accessible (WCAG-compliant alt text), accurate (observable details only), and model-dependent. 11. Description quality varies by model size — larger models (7B+) produce more nuanced descriptions than smaller variants (4B). 12. Print or save the description for use in accessibility systems, content management, or cataloging workflows. 13. Handle `NutrientException` failures for vision processing issues, including server unavailable, model not loaded, or timeout errors. For related image workflows, refer to the [.NET SDK guides](https://www.nutrient.io/guides/dotnet/csharp.md). Download [this ready-to-use sample package](https://www.nutrient.io/downloads/samples/csharp/describe-image-with-local-ai.zip) to explore local AI image description. --- ## Related pages - [Nutrient .NET SDK extraction guides](/guides/dotnet/csharp/extraction.md) - [Applying OCR to a PDF page](/guides/dotnet/csharp/extraction/apply-ocr-to-pdf-page.md) - [Applying OCR to a PDF document](/guides/dotnet/csharp/extraction/apply-ocr-to-pdf.md) - [Classifying documents](/guides/dotnet/csharp/extraction/classify-document.md) - [Generating image descriptions using Claude](/guides/dotnet/csharp/extraction/describe-image-with-claude.md) - [Generating image descriptions using OpenAI](/guides/dotnet/csharp/extraction/describe-image-with-openai.md) - [Detecting document language](/guides/dotnet/csharp/extraction/detect-document-language.md) - [Extracting data from images using ICR](/guides/dotnet/csharp/extraction/extract-data-from-image-icr.md) - [Extracting data from images using OCR](/guides/dotnet/csharp/extraction/extract-data-from-image-ocr.md) - [Extracting data from images using vision language models](/guides/dotnet/csharp/extraction/extract-data-from-image-vlm.md) - [Extracting data from specific pages](/guides/dotnet/csharp/extraction/extract-data-from-specific-pages.md) - [Extracting form fields from images](/guides/dotnet/csharp/extraction/extract-form-fields-from-image.md) - [Extracting structured data from documents](/guides/dotnet/csharp/extraction/extract-structured-data.md) - [Generating extraction schemas](/guides/dotnet/csharp/extraction/generate-extraction-schema.md) - [Extracting JSON data from a PDF document](/guides/dotnet/csharp/extraction/json-data-extraction.md) - [Labeling form fields with a vision language model](/guides/dotnet/csharp/extraction/label-form-fields-with-vlm.md) - [Parsing a document into structured content](/guides/dotnet/csharp/extraction/parse-document.md) - [Extracting text from PDF documents](/guides/dotnet/csharp/extraction/pdf-to-text.md) - [Reading barcodes with vision extraction](/guides/dotnet/csharp/extraction/read-barcodes-with-vision.md) - [Extracting text from multilingual images](/guides/dotnet/csharp/extraction/read-text-from-image-multi-language.md) - [Extracting text from images](/guides/dotnet/csharp/extraction/read-text-from-image.md) - [Searching document text](/guides/dotnet/csharp/extraction/search-document-text.md) - [Speeding up first ICR operation by predownloading models](/guides/dotnet/csharp/extraction/speed-up-first-icr-by-downloading-requirements.md)