Procedural CAD Synthetic Vision
Procedural CAD assembly renders with ray-traced defect injection (scratches, porosity, structural cracks) for industrial QA models.
Quality & Precision Benchmarks
DEFECT VARIETY
50+ Procedural Defect Types
LABEL ACCURACY
100% Mathematically Perfect
SIM2REAL FID
FID < 11.5
SLA THROUGHPUT
10M+ Frames / Day
Dataset Taxonomy & Output Structure
cad_step_file_id (STEP / IGES Assembly Latch)
procedural_defect_type (Scratch / Porosity / Crack)
defect_severity_metric (Micron Depth / Surface Area)
raytraced_depth_pass (32-bit Metric Float Array)
instance_mask_pass (Pixel-Exact Masks)
Specific Type Tasks & Applications
- • Industrial Manufacturing Defect Detection
- • Automated Optical Inspection (AOI) Training
- • Robotic Assembly Bin Picking
What Is Right vs What Is Wrong
| COMMON COMPETITOR ERRORS (WRONG) | BLUE PROJECTS GROUND TRUTH (RIGHT) |
|---|---|
| FAIL: Manual physical defect preparation requiring costly destruction of expensive manufacturing parts | PASS: Procedural CAD defect generation injecting realistic scratches and structural cracks in simulation |
| FAIL: Coarse bounding boxes failing to isolate micro-defects | PASS: Pixel-exact instance segmentation masks generated directly from GPU render passes |
Files & Sim2Real Vision Example (Python)
import json
# Load Blue Projects Sim2Real Dataset Type: Procedural CAD Synthetic Vision
with open("procedural-cad-synthetic-vision_sim2real.json", "r") as f:
data = json.load(f)
print("Loaded Sim2Real Keys:", list(data.keys()))
Why Blue Projects for Procedural CAD Synthetic Vision?
Request a free matched 1,000-pair Sim2Real sample batch generated for your exact target environment or camera sensor specs.
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