Andrea Pozzetti
e114ecefdf
Split Cadrille and CAD-Recode nodes from the CADabra monorepo. Multi-modal CAD reconstruction from point clouds, images, or text. Original source: https://github.com/PozzettiAndrea/ComfyUI-CADabra
63 lines
1.6 KiB
Python
63 lines
1.6 KiB
Python
"""
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CAD-Recode Integration for ComfyUI-CADabra
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Paper: CAD-Recode: Reverse Engineering CAD Code from Point Clouds (ICCV 2025)
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Authors: Rukhovich et al., University of Luxembourg
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Project: https://cad-recode.github.io/
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GitHub: https://github.com/filaPro/cad-recode
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CAD-Recode transforms 3D point clouds into executable CadQuery Python code,
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achieving state-of-the-art performance on DeepCAD, Fusion360, and CC3D benchmarks.
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Usage:
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from utils.cadrecode import CADRecode, generate_code, execute_cadquery_code
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# Load model
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model = CADRecode.from_pretrained('filapro/cad-recode-v1.5')
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tokenizer = load_tokenizer()
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# Generate code from point cloud
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code = generate_code(model, tokenizer, point_cloud)
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# Execute safely
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success, result, stl_path = execute_cadquery_code(code)
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"""
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from .model import CADRecode, FourierPointEncoder
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from .inference import (
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generate_code,
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normalize_point_cloud,
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sample_points_fps,
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sample_points_random,
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mesh_to_point_cloud,
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prepare_input,
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load_tokenizer,
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)
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from .execution import (
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execute_cadquery_code,
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execute_cadquery_code_persistent,
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validate_cadquery_code,
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cleanup_temp_files,
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)
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__all__ = [
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# Model
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'CADRecode',
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'FourierPointEncoder',
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# Inference
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'generate_code',
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'normalize_point_cloud',
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'sample_points_fps',
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'sample_points_random',
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'mesh_to_point_cloud',
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'prepare_input',
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'load_tokenizer',
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# Execution
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'execute_cadquery_code',
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'execute_cadquery_code_persistent',
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'validate_cadquery_code',
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'cleanup_temp_files',
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]
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__version__ = '1.0.0'
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