Package Health Score

51 / 100

security
Security review needed
popularity
Recognized
maintenance
Inactive
community
Sustainable

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Popularity

Recognized

GitHub Stars: 307
Forks: 85
Contributors: 20

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package pycocoevalcap, we found that it has been starred 307 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Nov 18, 2020
Direct Vulnerabilities: 0
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0
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0
M
0
L
Indirect Vulnerabilities: 0
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0
H
0
M
0
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License Risk: 0
H
0
M
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

BSD-2-Clause

Security Policy

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Maintenance

Inactive

Commit Frequency

No Recent Commits

Open Issues: 11
Open PR: 2
Last Release: 4 years ago
Last Commit: 2 years ago

Further analysis of the maintenance status of pycocoevalcap based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Inactive.

An important project maintenance signal to consider for pycocoevalcap is that it hasn't seen any new versions released to PyPI in the past 12 months, and could be considered as a discontinued project, or that which receives low attention from its maintainers.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Sustainable

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 20
Funding: No

With more than 10 contributors for the pycocoevalcap repository, this is possibly a sign for a growing and inviting community.

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Package

Python Versions Compatibility: >=3

Age: 4 years
Latest Release: 4 years ago
Dependencies: 1 Direct / 12 Total
Versions: 1
Maintainers: 0
Wheels: OS Independent

Readme

Microsoft COCO Caption Evaluation

Evaluation codes for MS COCO caption generation.

Description

This repository provides Python 3 support for the caption evaluation metrics used for the MS COCO dataset.

The code is derived from the original repository that supports Python 2.7: https://github.com/tylin/coco-caption.
Caption evaluation depends on the COCO API that natively supports Python 3.

Requirements

Java 1.8.0
Python 3

Installation

To install pycocoevalcap and the pycocotools dependency (https://github.com/cocodataset/cocoapi), run:

pip install pycocoevalcap

Usage

See the example script: example/coco_eval_example.py

Files

eval.py: The file includes COCOEavlCap class that can be used to evaluate results on COCO.
tokenizer: Python wrapper of Stanford CoreNLP PTBTokenizer
bleu: Bleu evalutation codes
meteor: Meteor evaluation codes
rouge: Rouge-L evaluation codes
cider: CIDEr evaluation codes
spice: SPICE evaluation codes

Setup

SPICE requires the download of Stanford CoreNLP 3.6.0 code and models. This will be done automatically the first time the SPICE evaluation is performed.
Note: SPICE will try to create a cache of parsed sentences in ./spice/cache/. This dramatically speeds up repeated evaluations. The cache directory can be moved by setting 'CACHE_DIR' in ./spice. In the same file, caching can be turned off by removing the '-cache' argument to 'spice_cmd'.

References

Microsoft COCO Captions: Data Collection and Evaluation Server
PTBTokenizer: We use the Stanford Tokenizer which is included in Stanford CoreNLP 3.4.1.
BLEU: BLEU: a Method for Automatic Evaluation of Machine Translation
Meteor: Project page with related publications. We use the latest version (1.5) of the Code. Changes have been made to the source code to properly aggreate the statistics for the entire corpus.
Rouge-L: ROUGE: A Package for Automatic Evaluation of Summaries
CIDEr: CIDEr: Consensus-based Image Description Evaluation
SPICE: SPICE: Semantic Propositional Image Caption Evaluation

Developers

Xinlei Chen (CMU)
Hao Fang (University of Washington)
Tsung-Yi Lin (Cornell)
Ramakrishna Vedantam (Virgina Tech)

Acknowledgement

David Chiang (University of Norte Dame)
Michael Denkowski (CMU)
Alexander Rush (Harvard University)

pycocoevalcap dependencies

pycocotools

FAQs

What is pycocoevalcap?

MS-COCO Caption Evaluation for Python 3. Visit Snyk Advisor to see a full health score report for pycocoevalcap, including popularity, security, maintenance & community analysis.

Is pycocoevalcap popular?

The python package pycocoevalcap receives a total of 67,387 weekly downloads. As such, pycocoevalcap popularity was classified as a recognized. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is pycocoevalcap well maintained?

We found indications that pycocoevalcap is an Inactive project. See the full package health analysis to learn more about the package maintenance status.

Is pycocoevalcap safe to use?

While scanning the latest version of pycocoevalcap, we found that a security review is needed. A total of 0 vulnerabilities or license issues were detected. See the full security scan results.

Last updated on 25 December-2024, at 00:29 (UTC).

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pycocoevalcap

MS-COCO Caption Evaluation for Python 3 For more information about how to use this package see README

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Microsoft COCO Caption Evaluation

Description

Requirements

Installation

Usage

Files

Setup

References

Developers

Acknowledgement

pycocoevalcap dependencies

FAQs

What is pycocoevalcap?

Is pycocoevalcap popular?

Is pycocoevalcap well maintained?

Is pycocoevalcap safe to use?

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Readme

Microsoft COCO Caption Evaluation

Description

Requirements

Installation

Usage

Files

Setup

References

Developers

Acknowledgement

pycocoevalcap dependencies

FAQs

What is pycocoevalcap?

Is pycocoevalcap popular?

Is pycocoevalcap well maintained?

Is pycocoevalcap safe to use?

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