DM-CAD Checkpoints

This repository archives the key trained checkpoints for the undergraduate thesis project:

Research on a Prototype for CAD Command Sequence Generation Based on Multimodal Inputs

The model predicts a DeepCAD latent vector from multi-view CAD renderings, optionally corrected by a text description. The predicted latent is then decoded by the frozen DeepCAD decoder into a parametric CAD command sequence.

Files

Path	Role
checkpoints/resnet18_transformer_text_v1_best.pt	Main final multimodal checkpoint. This is the official thesis checkpoint for image+text inference.
checkpoints/resnet18_transformer_image_v1_best.pt	Final image-only Transformer checkpoint. Useful for pure visual inference and comparison.
deepcad_pretrained/pretrained.tar	DeepCAD pretrained autoencoder package used as the frozen CAD encoder/decoder dependency.
config_summary.json	Extracted checkpoint metadata, training args, and stored metrics.
results/FINAL_THESIS_RESULTS_2026-05-15.md	Human-readable final experiment summary.
results/*.json	Machine-readable evaluation outputs for the final checkpoints.
checksums_sha256.txt	SHA256 checksums for all uploaded files.

Official Checkpoints

The final thesis record selects:

• Image-only: runs/deepcad_latent/resnet18_transformer_v1_ddp2/best.pt
• Multimodal: runs/deepcad_latent/resnet18_transformer_text_v1_ddp2/best.pt
• Enhanced inference: multimodal checkpoint with blend(alpha=0.5)

The later transformer_text_v2 run was not adopted because it did not surpass transformer_text_v1 on test latent MSE.

Main Results

Held-out test set:

Method	Seq Exact	Solid Valid	ACC_cmd	ACC_param	Invalidity	CD mean	CD median
Image-only Transformer Direct	0.1313	0.8135	0.8634	0.7415	0.1865	0.12981	0.03433
Multimodal Transformer Direct	0.1423	0.8450	0.8721	0.7528	0.1550	0.12944	0.02992
Multimodal Transformer Blend 0.5	0.1742	0.9464	0.8620	0.7720	0.0536	0.12508	0.03365

ARE-reference subset:

Method	Seq Exact	Solid Valid	ACC_cmd	ACC_param	Invalidity	CD mean	CD median
Multimodal Transformer Direct	0.1462	0.8480	0.8775	0.7577	0.1520	0.12649	0.02712
Multimodal Transformer Blend 0.5	0.1795	0.9478	0.8680	0.7766	0.0522	0.12248	0.03090

Expected Runtime Context

These checkpoints are project checkpoints rather than standalone Hugging Face Transformers models. They are intended to be used with the original dm-cad2 source code and the DeepCAD dependency code.

Typical evaluation command:

python scripts/evaluate_image_to_cad.py \
  --checkpoint checkpoints/resnet18_transformer_text_v1_best.pt \
  --ids <test_ids.txt> \
  --text-root <text_embedding_root> \
  --data-root <dataset_root> \
  --device cuda \
  --batch-size 64 \
  --num-workers 4 \
  --retrieval-mode blend \
  --blend-alpha 0.5 \
  --retrieval-latent-root <train_latent_root> \
  --check-solid-validity \
  --compute-chamfer \
  --num-cd-points 2000 \
  --output <output.json>

The dataset and latent/text embedding shards are not included in this model repository.

Checkpoint Notes

• Main checkpoint SHA256: 26efa55128cca01fb8d797615fb9470a31e30d4f168ef68a681934f5c5c2ff11
• Image-only checkpoint SHA256: 9192081b95b9823a8199edf605b43e67ae9363c13166ab4d7ef174044359ebbd
• DeepCAD pretrained package SHA256: 511eb29e945f1c84f10b9b60127e27a38c4fa0b968ad160fc58c675bfc8473e4