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Annotate images and export coordinates in YOLO TXT format for computer vision model training.
Draw annotations (bounding boxes, polygons, circles, lines) on images for machine learning datasets (like window, door, facade, or object detection training datasets). Manage classes, and import/export datasets in COCO, LabelMe, and YOLO formats with a real-time synchronized JSON editor.
Designed for direct use without extra steps or inflated trust claims.
Upload or drag-and-drop an image or PDF to begin
Welcome to Universal Annotation Tool & Dataset Builder, a lightweight offline development helper. Draw, edit, and inspect image annotations with interactive canvas and COCO, LabelMe, and YOLO import/export support. Designed specifically for software engineers, database admins, and tech professionals, this tool automates repetitive formatting, encoding, and conversion tasks. All inputs are processed locally in your browser session. Your code snippets, JWT payloads, Base64 strings, or database queries are never transmitted to outside servers, protecting secure access tokens or customer data. Specifically, this tool addresses user needs for **image annotation tool**, **coco dataset builder**, and **labelme editor** with high efficiency. Draw, edit, and inspect image annotations with interactive canvas and COCO, LabelMe, and YOLO import/export support. It operates as a lightweight, clean, and zero-latency sandbox designed for daily productivity.
Step 1: Upload Image or PDF
Select and load your target image file or multi-page PDF document. Pages will load into the preview slider below the canvas.
Step 2: Select Class Label and Draw Shapes
Create classification classes and use the square, circle, triangle, line, polygon, or point marker drawing tools to outline objects directly on the canvas.
Step 3: Refactor and Apply Metadata
Add custom field schemas (like difficulty, occlusions, tags) to shapes. Use the JSON editor drawer to refactor class names, offsets, or coordinate scale factor.
Step 4: Export Dataset Files
Select your target computer vision formatting (COCO JSON, LabelMe JSON, or YOLO text) and click to trigger local download of your dataset files.
No. The entire process (file rendering, canvas calculations, and dataset formatting exports) is executed 100% locally in your browser. None of your data ever leaves your computer.
Yes. You can import existing annotations in COCO JSON, LabelMe JSON, or YOLO text formats by drag-dropping the JSON/text files to edit them.
When a multi-page PDF is loaded, it renders each page as a canvas background. You can select pages using the preview thumbnails below the canvas to manage drawings for each page independently.
Yes. All active shapes feature standard resize and rotate anchors on the canvas. You can toggle layer visibility and lock attributes to prevent accidental modifications.
You can use rectangles, circles, triangles, lines, points, custom freehand loops, and arrow shapes to annotate your images or documents.
Yes. Holding down the Shift key while dragging any of the transformer anchors locks the aspect ratio of the bounding boxes.
You can select any annotation and use the Arrow keys on your keyboard to nudge it by 1 pixel, or hold Shift + Arrow keys to nudge it by 10 pixels for precise placement.
Yes. Under the Props tab in the right-hand panel, you can add custom key-value metadata fields (such as occlusions, tags, or notes) that will be bundled into exported JSON formats.
Focus Mode expands the workspace into a clean, fullscreen interface to maximize screen real estate and remove distraction during large annotation tasks.
Yes. The workspace automatically saves your shapes, categories, and settings locally every 800 milliseconds, allowing you to resume your session if the browser refreshes.
YOLO Dataset Bounding Box Builder on ToolVines is built for direct, browser-based workflows. Open the page, use the interface immediately, and export your output with minimal friction. This tool belongs to Annotation Tools and is designed with responsive controls, clear accessibility labels, and practical defaults for daily use.
Looking for alternatives? Explore more in Annotation Tools or browse the complete tools directory.
This tool processes all inputs locally in your browser. Your files and data are never uploaded to our servers, keeping them 100% private.
Describing the keyboard-driven autocomplete and scored ranking algorithm we deployed. Details of scoring prioritizations, highlight text, and Arrow key listeners.
How local ML dataset tools like YOLO bounding box creators and COCO JSON viewers run directly inside browser sandboxes using client-side vector canvases.