EasyPHPhotoGallery

Photo Gallery for your own NAS server.

This project use your already existing image folder, and let you organize and share your pictures.

It handle Folders, Tags, Thumbnails, Virtual Albums, Face Detection, and many more to come.

Demo

Demonstration of the tagging process: EPG Tagging on Youtube

Feature

• Albums of your local photos
• On-fly thumbnails resizing and caching with Thumbor
• SlideShow and Fullscreen pictures
• Search / Tagging with TensorFlowJS AI
• Create folder, Delete, Move files
• Upload new photos with shunked transfer
• Create virtual albums
• Provide as Dockerapp for easy install
• Sharing with friends (publicly, limited or private)
• Limit visibility of files only to admin
• Detection and recognition of human faces and regroup pictures by people
• Map of your picture's GPS coordinates
• Fully tested API with PHPUnit
• Fully tested feature with Cypress

BTW: This project doesn't need to move your picture in order to work.

And it doesn't copy your picture binary data during import.

So you can keep your files ordered as you want, and it reduce storage usage. Finally!

Installation

Choose your http port, and the main folder to share cp .env.example .env; vi .env

Launch the project ./dcp-prod up -d

Prepare your config, and edit to set the APP_URL (using the port you choose earlier) cp config/php/src/.env.example config/php/src/.env

Install dependencies source enter.sh ./init.sh

Setup

1. Register a new account with your email

2. Then Connect using this account :

email: admin@easyphpgallery.io password: secret

3. Using the admin account go to "administration" and to set your new user as admin

4. Then disconnect and use your new account to definitively delete the previous admin account for security reasons

Recommandations

To optimize your experience, you can sync your mobile phone photo folder with this app, by using apps like:

https://play.google.com/store/apps/details?id=dk.tacit.android.foldersync.lite&hl=fr

Developpement

Start a developpement server: ./dcp-dev

Source

TensorflowJS tuto => https://github.com/ADLsourceCode/TensorflowJS.git http://jamesthom.as/blog/2018/08/07/machine-learning-in-node-dot-js-with-tensorflow-dot-js/

Donation

Any help is always appreciated ;)