NeurCADRecon Train

NeurCADReconTrain

Train NeurCADRecon to learn an SDF from a point cloud. Loss Terms (shown during training): • SDF: Distance error at surface points. Good: < 0.01 • Eikonal: Gradient magnitude should be 1 (|∇f|=1). Good: < 0.1 • Morse: Gaussian curvature regularization for sharp CAD edges. Good: < 1.0 • Total: Weighted sum. Typically starts 100-500, ends 10-50. Training takes 5-15 min on GPU for 10k iterations.

Pack: ComfyUI-NeurCADRecon

custom_nodes.ComfyUI-NeurCADRecon

Inputs (9)

Name	Type	Required
model	NEURCADRECON_MODEL	required
point_cloud	TRIMESH	required
num_iterations	INT	optional
batch_size	INT	optional
learning_rate	FLOAT	optional
loss_preset	COMBO	optional
save_checkpoint	BOOLEAN	optional
checkpoint_dir	STRING	optional
log_interval	INT	optional

Outputs (3)

Name	Type
trained_model	NEURCADRECON_MODEL
checkpoint_path	STRING
training_log	STRING