I built QuantTakeoff and releasing v1.0 for validation: Input a construction PDF, get back
takeoff report with wall lengths, areas, door/window counts and sizes
3D GLB of the building at real-world scale all under ~10 mins.
The pain it solves: Reduce time estimator to trace out elements either by hand or software and extract out reports.
Stack: Ensemble of computer vision tools (95%), VLM OCR (5%)
Hard parts that are working:
Auto-find the plan page in a 200-sheet bid set (most stacks make you point at the right sheet manually). I am still manually annotating a new dataset for the new models.
Holds up on noisy as-builts and hand-marked sheets that break OCR-first pipelines
Post CV processing to optimize for usability.
Pixel accuracy to measure elements including size / width of doors and windows.
The pain it solves: Reduce time estimator to trace out elements either by hand or software and extract out reports.
Stack: Ensemble of computer vision tools (95%), VLM OCR (5%)
Hard parts that are working: Auto-find the plan page in a 200-sheet bid set (most stacks make you point at the right sheet manually). I am still manually annotating a new dataset for the new models. Holds up on noisy as-builts and hand-marked sheets that break OCR-first pipelines Post CV processing to optimize for usability. Pixel accuracy to measure elements including size / width of doors and windows.
Demo: https://youtu.be/fVy7tDFqR98
Particularly want feedback on: Real world estimators feedback on what could be better for the practice. What would make use this or what is missing?
P.S Live demo has been removed to manage compute costs from a few enthusiasts who burn through the HF spaces bill.