2.7.4. Configuration Options

Comparison of Presets

Preset

Sorted by

Strengths and Weaknesses

Requirements, runtime for 100,000 parts

visual_raw

Shape and Proportion from Six Rendered Views

Groups parts the way a human would at first glance. Does not take into account any part characteristics— threads, dimensions, and standards are ignored.

Hole pattern, no threads.

STL only; requires rebuilding the container. 8 to 15 hours

visual_3d

Shape derived directly from the 3D geometry

Best for flat sheet metal and plate parts. Overall coarser than visual_raw and also without part features.

STL only; runs strictly in serial mode. 12 to 23 hours

visual_norm_hybrid

Two-tiered: top tier by appearance, bottom tier by Feature XML

Takes into account the technical characteristics of the parts: The main groups remain visually plausible, and within them, parts are neatly separated based on characteristics and dimensions. Requires feature data for each part—parts without this data are excluded.

XML required, plus new build. 8 to 15 hours; creates a `reuse_file` in the registry—if the catalog matches, only 5 to 11 hours

visual_blend_norm_hybrid

Three-channel: Appearance and 3D (rough), XML (fine)

Same level of accuracy for features; the 3D geometry stabilizes the upper groups for sheet metal parts. Also requires feature data for each part.

XML required, plus new build. 20 to 36 hours – the most complex preset

Decision Guide: If a Feature XML file is available for each part, the Hybrid preset is the first choice—it takes technical characteristics into account and reliably separates parts even when the same shape appears in many sizes. If no additional data is available, or if you have a mixed or unknown inventory, use visual_raw. For catalogs with a high proportion of sheet metal parts, discuss visual_3d and a pilot run early on.

Common Mistakes in Counseling:

  • Setting unrealistically high expectations for cluster purity—even in the best-case scenario, a large portion of the clusters will remain mixed because many elements in the dataset simply have no true siblings.

  • Don't expect purely visual presets to include standard designations or be categorized by size—they show the shape, not the features; that's what the hybrid presets are for.

  • Protection against empty clusters cannot be guaranteed across the board—it depends on the selected preset .

  • Promoting the three-channel preset as the best—it's an option for brass and mixed instrument catalogs, not an improvement on the hybrid preset.

  • Runtimes Off the top of my head—the fastest and slowest presets differ by a factor of several times, and consistently heavy sections multiply that difference even further.

  • A preset or a request using the old language model (gemma3) for the new image—it fails at runtime, and the error message is misleading.

  • Determine the memory requirements based on the old measurements, even though the new language model has not yet been evaluated.