Draw Attention vs MakeSense.ai
Draw Attention
wpdrawattention.comMakeSense.ai
makesense.aiSide by side
| Figure | Draw Attention | MakeSense.ai |
|---|---|---|
| Price from | $8.25/mo | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 3 | 1 |
| Spec score · Image Annotation Software | 8.3 (#6) | 8.6 (#3) |
Plans
Draw Attention
- FreeFree
- Pro - Single Site$99 a year
- Pro - Unlimited Sites$199 a year
In their own words
Draw Attention
Draw Attention is a WordPress plugin for creating interactive image maps. Site owners draw polygon, rectangle, or circle hotspots that visitors can click, tap, or hover over. Hotspots can display text, images, shortcodes, galleries, video, or audio, or direct visitors to another URL. The free edition supports one interactive image. Pro adds six information layouts—tooltip, lightbox, top, bottom, left, and right—and allows unlimited interactive images and clickable areas. The plugin can be inserted with a shortcode, Beaver Builder module, or WordPress Editor Block, and the maker names WPML as a compatible translation plugin. It says image content is available to screen readers, hotspots support keyboard commands, and content remains accessible without JavaScript through an image-map fallback. Plugin data stays in the site owner’s WordPress database; a Pro license key is periodically sent for status checks. Free costs nothing; Pro costs $99 a year for one website or $199 a year for unlimited websites.
MakeSense.ai
MakeSense.ai is a browser-based tool for labeling photos and preparing datasets for computer vision projects. It supports point, line, rectangle, polygon, and label annotations, with model-assisted labeling through YOLOv5, SSD pretrained on COCO, and PoseNet. Users can load their own YOLOv5 models exported to TensorFlow.js format. Export options include CSV, YOLO, VOC XML, VGG JSON, and COCO JSON; imports include YOLO, VOC XML, and COCO JSON. The available format combinations vary by annotation type, and some are not yet supported. The project says images are not sent to a server and AI features run using TensorFlow.js. It works in a browser across operating systems, and documented local and Docker setups are available; Docker serves the application on localhost:3000. The project describes it as suitable for small computer vision deep-learning projects and dataset preparation. It was founded in 2019, is licensed under GPL-3.0, and credits Piotr Skalski as author and copyright holder. The Free plan costs nothing.