Command line tool to auto-classify images, renaming them with appropriate address and labels. Uses Node.js and the Google Geocoding and Vision APIs.
image-classifier-ts is stable, with ongoing development (tested on Windows, Ubuntu Linux) following semantic versioning.
The project was started as a way to avoid depending on particular photo software such as Picasa, and also to save time spent on sorting tons of photos!
We use sharp
to resize images during processing. sharp
requires
node-gyp to build, so you will need to
install
Microsoft's windows-build-tools
using this command:_
npm install --global --production windows-build-tools
Install:
note: the processed images will be moved to the output directory. so you may want to point 'input directory' to a *copy of your images directory.*
You can run image-classifier-ts
in one of three ways:
npm i -g image-classifier-ts@latest --production
on Ubuntu, you may need administrator permissions via sudo
:
sudo npm i -g image-classifier-ts@latest --production
To use:
image-classifier-ts <path to image directory> <path to output directory> [-filenameFormat=<file name format>]
Install inside your npm project:
yarn add image-classifier-ts
via bash script:
node_modules/image-classifier-ts/dist/lib/cli.js <input directory> <output directory>
OR via node:
node node_modules/image-classifier-ts/dist/lib/main <input directory> <output directory>
yarn
On Windows: use a bash shell like git bash
.
To test your installation:
./test.sh
To classify your images:
./go.sh <path to image directory> <path to output directory> [-filenameFormat=<file name format>]
example:
./go.sh ../myPhotos ../myPhotos-labelled
To have a 'dry run' where the images are not actually moved, use the 'dryRun' option:
./go.sh ../myPhotos ../myPhotos-labelled -dryRun
To see more detailed usage info:
./go.sh
./go.sh ../my-photos -filenameFormat={year}/{location}/{topLabel}/{combinedLabels}-{fileSizeMb}-{width}x{height}--{filename}
You can specify locations for the photos, by date.
Do this by adding a file named mapDateToLocation.csv
in the same folder as your images.
The approprite location description will be used when renaming the image files.
For an example, see mapDateToLocation.csv
note: if the location is unknown, and the filename format includes {location}
, then the image will NOT be moved.
Install inside your npm project:
yarn add image-classifier-ts
Then in TypeScript, you can import the library:
import * as ic from "image-classifier-ts";
For a working example, see the library test harness.
site | URL |
---|---|
source code (github) | https://github.com/mrseanryan/image-classifier-ts |
github page | https://mrseanryan.github.io/image-classifier-ts/ |
npm | https://www.npmjs.com/package/image-classifier-ts |
see the contributing readme.
This project is based on the excellent seeder project typescript-library-starter.
image-classifier-ts uses the ExifReader library.
Original work by Sean Ryan - mr.sean.ryan(at gmail.com)
This project is licensed under the MIT License - see the LICENSE file for details
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