The vision workbench for macOS
Your images. Your models. Your imagination.
One thoughtful space to bring them together.
Native on Mac · Local training · Made for curious minds
Good computer vision takes more than a training button. BadBob connects the careful work before, during and after it.
01 / Capture Lab
Collect the images your model actually needs. Capture from a camera, explore a tricky scenario, or build coverage across your project classes.
02 / Annotator
Draw boxes and contours, review AI suggestions, and keep your work organized in named annotation lists. The little details are where a useful dataset begins.
03 / Data Studio
Turn reviewed images into versioned datasets. Keep training, validation and test images distinct, so your next result has something honest to measure against.
04 / Training
Train object detection with Create ML or follow the segmentation path. Preview optional augmentation before you run, and keep an eye on progress as your model learns.
05 / Compare & improve
Compare model candidates on a shared dataset. Inspect difficult predictions in Failure Bank, then bring those lessons back into your next round of images.
Same curiosity. Different questions.
Sometimes you need to know where something is.
Sometimes every edge matters. Choose the path that fits.
01 / Object detectionPowered by Create ML
Teach a model to recognize your project classes and locate them with bounding boxes. Build on Apple's Create ML training tools, right on your Mac.
Classes → Boxes → Detections
02 / SegmentationLook a little closer
Move beyond rectangles. Annotate contours and follow the segmentation training path when your project needs the shape of an object.
Contours → Masks → ShapesMade for people who want to understand their data, shape their tools and keep creating.
Capture, annotate and train on your Mac. Work with local projects and image banks, with training environments prepared for the path you choose.
Named lists, saved annotation revisions and dataset versions keep the journey traceable. A result means more when you know where it came from.
A contextual manual follows the section you're in. Quick starts, search and bookmarks help you find the next step when the workflow gets interesting.
A small robot. A curious mind.04 / The human behind the robot
Behind the little robot is a serious amount of care. BadBob brings interface design, native development and practical computer vision into the same project.
Built by Johan, with a soft spot for useful tools and the small details that make them feel right.
Meet the makerWork on custom object detection and segmentation projects: from everyday objects and hobby experiments to a dataset for your next product. You define the project classes and collect the images that matter for your use case.
BadBob is a native macOS application. Create ML supports the object detection training path; segmentation uses a separately prepared local training environment. Hardware and available memory affect what you can train and how long it takes.
The core capture, annotation, dataset and local training workflow runs with your projects and image bank on your Mac. You can also work with shared storage. Training tools and models may need to be downloaded when you prepare an environment.
They have dedicated dataset splits. Training augmentation is optional and applies to the training images, while your originals and reserved validation and test images stay unchanged.
BadBob is in active development. Public downloads, trial terms and final pricing are being prepared. This first website introduces the product and its workflow; purchasing is not available here yet.
Public downloads / Coming soon
A camera, a little curiosity, and a project worth making.
Your next model starts with you.
