2.0 KiB
JSON to CDSL
This program converts SolidWorks export JSON into parameterized Learning IR
(*.cdsl.json).
Conversion responsibilities:
- normalize SolidWorks JSON into an intermediate representation;
- classify sketches into named parameterized profiles;
- reuse equivalent profiles through semantic references;
- derive deterministic geometry through the sketch solver;
- remove avoidable floating-point noise;
- report unsupported or non-self-sufficient shapes.
The converter must not hide missing geometry behind an external context file when producing a training-ready CDSL artifact.
Evidence v2 batch converter
evidence_v2_to_cdsl.py converts the newer
solidworks.cad_evidence.v2 extraction format into semantic CDSL v1.1. It
does not modify the current rebuild engine: features without a runtime
implementation are emitted with execution_status: "deferred" instead.
PYTHONPATH=backend/engine python json_to_cdsl/evidence_v2_to_cdsl.py \
json_to_cdsl/input/evidence_v2 \
--truth-dir json_to_cdsl/input/evidence_v2/truth \
--out json_to_cdsl/output \
--workers 1
For every *.solidworks_evidence_v2.json input it writes:
<part_id>.cdsl.json: self-contained semantic CDSL in millimetres;<part_id>.diagnostic.json: source blockers, deferred features, optionalinferred_from_stepselectors, semantic validation, and STEP-versus-source bounding-box/volume/area/topology metrics;manifest.json: batch-level counts and paths.
The optional STEP directory is used only to infer a host face when exactly one
candidate is compatible with a Hole Wizard's captured locations. Ambiguous
geometry stays in unresolved; the converter never invents a selector.
Source records are discovered recursively. Output remains flat and is named by the normalized full source filename. Files that normalize to the same part ID receive a deterministic relative-path hash suffix, so every input record maps to a distinct output. When a matching STEP file exists, it is resolved through the same relative subdirectory as its source record.