Science Score: 26.0%

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    Low similarity (7.4%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

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Basic Info
  • Host: GitHub
  • Owner: rOcK310739YjulIus
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 271 MB
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  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed 10 months ago
Metadata Files
Readme Changelog Contributing Funding License Code of conduct Citation Codeowners Security Roadmap Authors Notice Maintainers Dco

README

SFMedu: Structrue From Motion for Education Purpose
Version 2 @ 2014
Written by Jianxiong Xiao (MIT License)

This code demonstrates how a traditional structure from motion pipeline is done and how to compute a dense point cloud by matching propagation in a simplest way. It is mainly designed for teaching a computer vision lecture at Princeton. Please check the slides and the homework assignment together with this code release. Although it is for education purpose, it is implemented in a nice way that it actually works for real photos. It is just probably quite slow compared to more optimized system, such as Bundler from Noah Snavely.

Usage: run SFMedu2.m in Matlab.

Acknowledgement: Thanks for Fisher Yu for bug fixing and feedback. We also thanks many people for making their functions publicly available online. Note that the third party library may have different licenses that you need to follow. We include them for the convenience for the users and don't imply any copyright issues.

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Dependencies

Cargo.toml cargo
ROS/Dockerfile docker
  • jupyter/minimal-notebook latest build
docker-compose.yml docker
  • mongo latest
  • mongo-express latest
build.gradle maven
pom.xml maven
package-lock.json npm
  • 1195 dependencies
pubspec.lock pub
  • async 2.1.0
  • boolean_selector 1.0.4
  • charcode 1.1.2
  • collection 1.14.11
  • flare_dart 1.4.1
  • flare_flutter 1.5.1
  • flutter 0.0.0
  • flutter_test 0.0.0
  • matcher 0.12.5
  • meta 1.1.6
  • path 1.6.2
  • pedantic 1.5.0
  • provider 3.0.0
  • quiver 2.0.2
  • sky_engine 0.0.99
  • source_span 1.5.5
  • stack_trace 1.9.3
  • stream_channel 2.0.0
  • string_scanner 1.0.4
  • term_glyph 1.1.0
  • test_api 0.2.4
  • typed_data 1.1.6
  • vector_math 2.0.8
AWS_EC2/requirements.txt pypi
  • awscli *
  • boto3 ==1.10.50
  • pandas *
  • plotly *
environment.yml pypi
setup.py pypi
  • Pillow *
  • faiss_gpu ==1.6.3
  • h5py *
  • metric-learn *
  • numpy *
  • scikit-learn *
  • scipy *
  • six *
  • torch *
  • torchvision *
.github/workflows/blank.yml actions
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.github/workflows/ci-plus.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
requirements.txt pypi
  • certifi ==2024.7.4
  • chardet ==5.2.0
  • charset-normalizer ==3.3.2
  • idna ==3.7
  • numpy ==2.0.1
  • pandas ==2.2.2
  • python-dateutil ==2.9.0.post0
  • pytz ==2024.1
  • requests ==2.32.3
  • six ==1.16.0
  • tzdata ==2024.1
  • urllib3 ==2.2.2