I’m building ImagePipe to help businesses handle repetitive product-image work. The goal is to bring image quality checks, object detection, background removal, and compliance checks into a practical workflow.
The project is in public alpha. This write-up is a starting point; each capability still needs a clear account of what is available today and what is planned.
The problem
A useful image tool has to fit the work around the image: getting files into the system, processing them, reviewing the output, and using the results. I’m interested in that whole workflow, as well as the computer vision itself.
What I’m working through
- How images move through storage and processing.
- How to make processing failures understandable and recoverable.
- Where automation helps and where a person should review the result.
- How feedback from potential users changes what I build next.
Next for this write-up
I want to add a real before-and-after example, describe the current processing pipeline, and explain one decision that changed during development.