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CSGNet: Neural Shape Parser for Constructive Solid Geometry This repository contains code accompaning the paper: CSGNet: Neural Shape Parser for Constructive Solid Geometry, CVPR 2018.Here we only include the code for 2D CSGNet. Code for 3D is available on this repository.Dependency...
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encoder_net = Encoder() encoder_net.cuda() data_labels_paths = {3: "data/synthetic/one_op/expressions.txt", 5: "data/synthetic/two_ops/expressions.txt", 7: "data/synthetic/three_ops/expressions.txt", 9: "data/synthetic/four_ops/expressions.txt", 11: "data/synthetic/five_ops/expressio...
CSGNet: Neural Shape Parser for Constructive Solid Geometry Supplementary Synthetic 2D shapes. We use the grammar described in the Section 4.1 to create our 2D dataset. The dataset is created by randomly generating programs of le... 被引量: 0发表: 2018年 加载更多研究...
Team Enterprise Explore Marketplace Pricing Sign inSign up Hippogriff/CSGNet Watch6 Star50 Fork14 master CSGNet/config_cad.yml Go to file Copy path 58 lines (39 sloc)1.33 KB RawBlame comment = "Write some meaningful comments that can be used in future to identify the intents of running ...
expression after beam search based decoding from CSGNet. So if the output expressions (of size test_size x beam_width) from the network are already calculated, then you can use this script. """ import argparse import json import os import sys import numpy as np from src.utils import ...
Hippogriff/CSGNetPublic NotificationsYou must be signed in to change notification settings Fork22 Star75 Code Issues1 Pull requests Actions Projects Wiki Security Insights Additional navigation options Files master data docs log src trained_models ...