image_optim | Optimize images using multiple utilities | Computer Vision library

by toy Ruby Version: v0.31.3 License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | image_optim Summary

image_optim is a Ruby library typically used in Artificial Intelligence, Computer Vision applications. image_optim has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

Command line tool and ruby interface to optimize (lossless compress, optionally lossy) jpeg, png, gif and svg images using external utilities:. Documentation for latest gem version and master branch. A test application with latest image_optim and image_optim_pack is available on heroku:

Support

Quality

Security

License

Reuse

Support

image_optim has a medium active ecosystem.

It has 1469 star(s) with 111 fork(s). There are 35 watchers for this library.

It had no major release in the last 6 months.

There are 34 open issues and 103 have been closed. On average issues are closed in 498 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of image_optim is v0.31.3

Quality

image_optim has 0 bugs and 0 code smells.

Security

image_optim has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

image_optim code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

image_optim is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

image_optim releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

image_optim saves you 1951 person hours of effort in developing the same functionality from scratch.

It has 4618 lines of code, 194 functions and 68 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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image_optim Key Features

No Key Features are available at this moment for image_optim.

image_optim Examples and Code Snippets

No Code Snippets are available at this moment for image_optim.

Community Discussions

Trending Discussions on image_optim

Recursively compressing images in a folder-structure, preserving the folder-structure

QUESTION

Recursively compressing images in a folder-structure, preserving the folder-structure

Asked 2021-May-27 at 04:47

I have this folder-strucutre, with really heavy high-quality images in each subfolder

...

ANSWER

Answered 2021-May-27 at 04:47

Instead of pre-mkdiring directories, you can create the required directories on the fly. Recursion solutions look elegant to me then compared to loops. Here is a straight-forward approach. I echoed the file names and directories to keep track of whats going on. I am not ffmpeg pro, I used cp instead but should work fine for your use case.

Shell script:

Source https://stackoverflow.com/questions/67659689

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install image_optim

You may also want to install image_optim_pack (see Binaries pack).
Simplest way for image_optim to locate binaries is to install them in common location present in PATH (see Binaries installation). If you cannot install to common location, then install to custom one and add it to PATH. Specify custom bin location using XXX_BIN environment variable (JPEGOPTIM_BIN, OPTIPNG_BIN, …).
before command: PATH="/custom/location:$PATH" image_optim *.jpg for example: PATH="/Applications/ImageOptim.app/Contents/MacOS:$PATH" image_optim *.jpg
inside script: ENV['PATH'] = "/custom/location:#{ENV['PATH']}"; ImageOptim.optimize_images([…]) for example: ENV['PATH'] = "/Applications/ImageOptim.app/Contents/MacOS:#{ENV['PATH']}"; ImageOptim.optimize_images([…])
Easiest way to get latest versions of most binaries for image_optim for Linux, Mac OS X, FreeBSD and OpenBSD is by installing image_optim_pack gem. Check installation instructions in Gem installation section.
Unless it is available in your chosen package manager, can be installed using cargo:.
If you installed the dependencies via brew, pngout should be installed already. Otherwise, you can install pngout by downloading and installing the binary versions.
svgo is available from NPM.
Download and install the jpeg-recompress binary from the JPEG-Archive Releases page, or follow the instructions to build from source.

Support

List of contributors to image_optim. If you would like to contribute - that is great and you are very welcome. Please check few notes in file CONTRIBUTING.markdown.

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