ezflow

A modular PyTorch library for optical flow estimation using neural networks

https://github.com/neu-vi/ezflow

Science Score: 64.0%

This score indicates how likely this project is to be science-related based on various indicators:

✓
CITATION.cff file
Found CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
○
DOI references
✓
Academic publication links
Links to: arxiv.org
✓
Committers with academic emails
1 of 6 committers (16.7%) from academic institutions
○
Institutional organization owner
○
JOSS paper metadata
○
Scientific vocabulary similarity
Low similarity (10.3%) to scientific vocabulary

Keywords

modular optical-flow pytorch

Keywords from Contributors

mesh interactive

Last synced: 6 months ago · JSON representation ·

Repository

A modular PyTorch library for optical flow estimation using neural networks

Basic Info

Host: GitHub
Owner: neu-vi
License: mit
Language: Python
Default Branch: main
Homepage: https://ezflow.readthedocs.io/
Size: 595 KB

Statistics

Stars: 136
Watchers: 5
Forks: 8
Open Issues: 25
Releases: 6

Topics

modular optical-flow pytorch

Created over 4 years ago · Last pushed almost 2 years ago

Metadata Files

Readme Contributing License Citation Authors

EzFlow

A modular PyTorch library for optical flow estimation using neural networks

[![Tests](https://github.com/neu-vig/ezflow/actions/workflows/package-test.yml/badge.svg)](https://github.com/neu-vig/ezflow/actions/workflows/package-test.yml) [![Docs](https://readthedocs.org/projects/ezflow/badge/?version=latest)](https://ezflow.readthedocs.io/en/latest/?badge=latest) [![Downloads](https://static.pepy.tech/badge/ezflow)](https://pepy.tech/project/ezflow) **[Documentation](https://ezflow.readthedocs.io/en/latest/)** | **[Tutorials](https://ezflow.readthedocs.io/en/latest/tutorials/index.html)**

Installation

From source (recommended)

```shell

git clone https://github.com/neu-vig/ezflow cd ezflow/ python setup.py install

```

From PyPI

```shell

pip install ezflow

```

Models supported

Datasets supported

Results and Pre-trained checkpoints

DCVNet | model config | paper

| Training Dataset | Training Config | ckpts | Sintel Clean (training) | Sintel Final(training)| KITTI2015 AEPE | KITTI2015 F1-all | |-----------------------------------------|-------------------------------------------------------------------------|----------------------------------------------------------------------------------------|-------------------------|-----------------------|----------------|------------------| | FlyingThings3DSubset + Monkaa + Driving | config | download | 1.90 | 3.35 | 4.75 | 23.41% |
FlowNetC | model config | arXiv

| Training Dataset | Training Config | ckpts | Sintel Clean (training) | Sintel Final(training)| KITTI2015 AEPE | KITTI2015 F1-all | |------------------|-------------------------------------------------------------------------|----------------------------------------------------------------------------------------|-------------------------|-----------------------|----------------|------------------| | Chairs | config | download | 3.41 | 4.94 | 14.84 | 54.23% | | Chairs -> Things | config | download | 2.93 | 4.48 | 12.47 | 45.89% | | Kubric | config | download | 3.57 | 3.96 | 12.11 | 36.35% |

#### PWC-Net | model config | arXiv

| Training Dataset | Training Config | ckpts | Sintel Clean (training) | Sintel Final(training)| KITTI2015 AEPE | KITTI2015 F1-all | |------------------|---------------------------------------------------------------------|-------------------------------------------------------------------------------------|-------------------------|-----------------------|----------------|------------------| | Chairs | config | download | 3.5 | 4.73 | 17.81 | 51.76% | | Chairs -> Things | config | download| 2.06 | 3.43 | 11.04 | 32.68% | | Kubric | config | download | 3.08 | 3.31 | 9.83 | 21.94% |

#### RAFT | model config | arXiv

| Training Dataset | Training Config | ckpts | Sintel Clean (training) | Sintel Final(training)| KITTI2015 AEPE | KITTI2015 F1-all | |------------------|-----------------------------------------------------------------|--------------------------------------------------------------------------------------|-------------------------|-----------------------|----------------|------------------| | Chairs | config | download | 2.23 | 4.56 | 10.45 | 38.93% | | Chairs -> Things | config | download | 1.66 | 2.75 | 5.01 | 16.87% | | Kubric | config | download | 2.12 | 2.54 | 6.01 | 17.35% |

Additional Information

KITTI dataset has been evaluated with a center crop of size 1224 x 370.
FlowNetC and PWC-Net uses padding of size 64 for evaluating the KITTI2015 dataset.
RAFT and DCVNet uses padding of size 8 for evaluating the Sintel and KITTI2015 datasets.

References
RAFT
DICL-Flow
PWC-Net
FlowNetPytorch
VCN
detectron2
CorrelationLayer
ptflow

Owner

Name: neu-vi
Login: neu-vi
Kind: organization
Location: United States of America

Repositories: 3
Profile: https://github.com/neu-vi

Northeastern University, Visual Intelligence Lab

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you find this software useful, please cite it as below."
authors:
- family-names: "Shah"
  given-names: "Neelay"
- family-names: "Goswami"
  given-names: "Prajnan"
- family-names: "Jiang"
  given-names: "Huaizu"
title: "EzFlow: A modular PyTorch library for optical flow estimation using neural networks"
date-released: 2021-11-18
url: "https://github.com/neu-vig/ezflow"
license: MIT

GitHub Events

Total

Watch event: 6
Fork event: 1

Last Year

Watch event: 6
Fork event: 1

Committers

Last synced: about 2 years ago

All Time

Total Commits: 252
Total Committers: 6
Avg Commits per committer: 42.0
Development Distribution Score (DDS): 0.325

Past Year

Commits: 17
Committers: 3
Avg Commits per committer: 5.667
Development Distribution Score (DDS): 0.353

Top Committers

Name	Email	Commits
Neelay Shah	s**9@g**m	170
Prajnan Goswami	8****3	36
dependabot[bot]	4****]	29
Prajnan Goswami	p**s@g**m	15
Neelay Shah	n**h@t**e	1
Huaizu Jiang	p****k	1

Committer Domains (Top 20 + Academic)

tuebingen.mpg.de: 1

Issues and Pull Requests

Last synced: 8 months ago

All Time

Total issues: 24
Total pull requests: 126
Average time to close issues: 5 months
Average time to close pull requests: 21 days
Total issue authors: 5
Total pull request authors: 4
Average comments per issue: 0.92
Average comments per pull request: 0.84
Merged pull requests: 73
Bot issues: 0
Bot pull requests: 54

Past Year

Issues: 0
Pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Issue authors: 0
Pull request authors: 0
Average comments per issue: 0
Average comments per pull request: 0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

NeelayS (14)
prajnan93 (6)
Salvatore-tech (2)
AruniRC (1)
YanjieGuo (1)

Pull Request Authors

dependabot[bot] (56)
NeelayS (36)
prajnan93 (33)
kardevroop (1)

Top Labels

Issue Labels

Pull Request Labels

dependencies (56)

Dependencies

docs/requirements.txt pypi

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Jinja2 ==3.0.1
Markdown ==3.3.4
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requirements.txt pypi

Babel ==2.9.1
Jinja2 ==3.0.1
Markdown ==3.3.4
MarkupSafe ==2.0.1
Pillow *
PySocks ==1.7.1
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absl-py ==0.13.0
alabaster ==0.7.12
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appdirs ==1.4.4
argh ==0.26.2
arrow ==0.15.1
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backports.entry-points-selectable ==1.1.0
binaryornot ==0.4.4
black ==21.7b0
bleach ==3.3.0
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certifi ==2021.5.30
cffi ==1.14.6
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click ==8.0.1
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nodeenv ==1.6.0
numpy *
oauthlib ==3.1.1
olefile ==0.46
omegaconf *
opencv-python ==4.5.3.56
packaging ==21.0
pathspec ==0.9.0
pathtools ==0.1.2
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platformdirs ==2.0.0
pluggy ==0.13.1
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protobuf ==3.17.3
py ==1.10.0
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text-unidecode ==1.3
toml *
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torch >=1.9.0
torchmetrics >=0.5.0
torchvision >=0.10.0
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tox ==3.14.0
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pypa/gh-action-pypi-publish 27b31702a0e7fc50959f5ad993c78deac1bdfc29 composite

environment.yml conda

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ezflow

Science Score: 64.0%

Keywords

Keywords from Contributors

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

EzFlow

A modular PyTorch library for optical flow estimation using neural networks

Installation

From source (recommended)

From PyPI

Models supported

Datasets supported

Results and Pre-trained checkpoints

DCVNet | model config | paper

FlowNetC | model config | arXiv

Additional Information

References

Owner

Citation (CITATION.cff)

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

All Time

Past Year

Top Authors

Issue Authors

Pull Request Authors

Top Labels

Issue Labels

Pull Request Labels

Dependencies