# Convert To Vector (`datavault/convert-to-vector`) Actor Convert raster images (PNG, JPG, WEBP) into high-quality SVG vectors in seconds. Perfect for logo vectorization, icon conversion, and illustration tracing, with clean paths, accurate colors, and a results ready for web, print, and manufacturing. - **URL**: https://apify.com/datavault/convert-to-vector.md - **Developed by:** [Datavault](https://apify.com/datavault) (community) - **Categories:** Automation, Other, Developer tools - **Stats:** 14 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Image to Vector Actor Transform your bitmaps (PNG, JPG, WEBP) into high-quality, scalable SVG vectors. This actor is optimized for logos, icons, and illustrations, providing clean paths and accurate color reproduction with professional-grade results. ### Key Features - **Professional Tracing**: Uses advanced algorithms to produce clean, sharp SVG paths suitable for professional design work. - **Batch Processing**: Convert multiple images in a single run by providing a list of URLs. - **Full Color Support**: Convert images with up to 256 colors. Each color is traced as a separate high-fidelity layer. - **High-Contrast B&W**: Optimized for generating silhouettes, masks, and stencil-ready vectors. - **Artifact-Free Encoding**: Custom PGM-based processing ensures perfect pixel alignment, eliminating the "swoosh" artifacts or shearing common in basic converters. - **Transparency Aware**: Smart background detection automatically handles transparency and can skip solid white backgrounds for clean, stand-alone vectors. ### Use Cases - **Logo Vectorization**: Convert low-resolution logos into scalable, print-ready formats. - **Icon Design**: Turn raster icons into lightweight SVGs for web and mobile development. - **Stencils & Manufacturing**: Create clean B&W paths for laser cutting, plotting, or CNC. - **Digital Art**: Rapidly vectorize sketches and illustrations for further editing in tools like Adobe Illustrator or Figma. ### Input Parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `imageUrls` | Array | (Required) | A list of image URLs you want to convert. For a single image, provide a list with one URL. | | `maxColors`| Integer | (Optional) | If set, performs color vectorization with up to the specified number of colors (2-256). Omit for high-contrast B&W. | | `threshold`| Integer | 128 | Luma threshold for B&W mode (0-255). Higher values result in thicker/darker paths. | ### Output The actor provides: 1. **OUTPUT.svg**: The final vectorized file, saved in the default Key-Value Store. 2. **Dataset Record**: Metadata for each run, including: - `imageUrl`: Link to the source image. - `svgUrl`: Direct link to your generated SVG. - `svgSize`: Final file size in bytes. - `convertedAt`: Timestamp of the operation. # Actor input Schema ## `imageUrls` (type: `array`): The list of image URLs to convert to SVG. ## `threshold` (type: `integer`): Luma threshold (0-255) for black & white conversion. Higher values make the image darker. Default is 128. ## `maxColors` (type: `integer`): If set, performs color quantization with this many colors (e.g., 8, 16). Omit for black & white. ## `useOriginalNames` (type: `boolean`): If true, the output SVGs will use the filename from the URL (e.g., logo.svg). If false, it uses OUTPUT_X.svg. ## Actor input object example ```json { "imageUrls": [ "https://www.python.org/static/community_logos/python-logo-master-v3-TM.png" ], "threshold": 128, "maxColors": 16, "useOriginalNames": false } ```` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "imageUrls": [ "https://www.python.org/static/community_logos/python-logo-master-v3-TM.png" ], "maxColors": 16 }; // Run the Actor and wait for it to finish const run = await client.actor("datavault/convert-to-vector").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "imageUrls": ["https://www.python.org/static/community_logos/python-logo-master-v3-TM.png"], "maxColors": 16, } # Run the Actor and wait for it to finish run = client.actor("datavault/convert-to-vector").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "imageUrls": [ "https://www.python.org/static/community_logos/python-logo-master-v3-TM.png" ], "maxColors": 16 }' | apify call datavault/convert-to-vector --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=datavault/convert-to-vector", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Convert To Vector", "description": "Convert raster images (PNG, JPG, WEBP) into high-quality SVG vectors in seconds. Perfect for logo vectorization, icon conversion, and illustration tracing, with clean paths, accurate colors, and a results ready for web, print, and manufacturing.", "version": "1.0", "x-build-id": "QtMcBh7mwgesoyKq5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/datavault~convert-to-vector/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-datavault-convert-to-vector", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/datavault~convert-to-vector/runs": { "post": { "operationId": "runs-sync-datavault-convert-to-vector", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/datavault~convert-to-vector/run-sync": { "post": { "operationId": "run-sync-datavault-convert-to-vector", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "imageUrls" ], "properties": { "imageUrls": { "title": "Image URLs", "type": "array", "description": "The list of image URLs to convert to SVG.", "items": { "type": "string" } }, "threshold": { "title": "Threshold", "minimum": 0, "maximum": 255, "type": "integer", "description": "Luma threshold (0-255) for black & white conversion. Higher values make the image darker. Default is 128.", "default": 128 }, "maxColors": { "title": "Max Colors", "minimum": 2, "maximum": 256, "type": "integer", "description": "If set, performs color quantization with this many colors (e.g., 8, 16). Omit for black & white." }, "useOriginalNames": { "title": "Use Original Filenames", "type": "boolean", "description": "If true, the output SVGs will use the filename from the URL (e.g., logo.svg). If false, it uses OUTPUT_X.svg.", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```