Automatically creates genre collections for your Plex media

Overview

Plex Auto Genres

Plex Auto Genres is a simple script that will add genre collection tags to your media making it much easier to search for genre specific content

  1. Requirements
  2. Optimal Setup
  3. Getting Started
  4. Automating
  5. Docker Usage
  6. Troubleshooting
Movies example (with cover art set using --set-posters flag.)

Movie Collections

Anime example

Anime Collections

Requirements

  1. Python 3 - Instructions > Windows / Mac / Linux (Not required if using Docker)
  2. TMDB Api Key (Only required for non-anime libraries)

Optimal Setup

  1. Anime / Anime Movies are in their own library on your plex server. (Anime and Anime Movies can share the same library)
  2. Standard TV Shows are in their own library on your plex server.
  3. Standard Movies are in their own library on your plex server.
  4. Proper titles for your media, this makes it easier to find the media. (see https://support.plex.tv/articles/naming-and-organizing-your-tv-show-files/)

For this to work well your plex library should be sorted. Meaning standard and non-standard media should not be in the same Plex library. Anime is an example of non-standard media.

If your anime shows and standard tv shows are in the same library, you can still use this script just choose (standard) as the type. However, doing this could cause incorrect genres added to some or all of your anime media entries.

Here is an example of my plex library setup

Plex Library Example

Getting Started

  1. Read the Optimal Setup section above
  2. Run python3 -m pip install -r requirements.txt to install the required dependencies.
  3. Rename the .env.example file to .env
  4. Rename the config/config.json.example file to config/config.json. The default settings are probably fine.
  5. Edit the .env file and set your plex username, password, and server name. If you are generating collections for standard media (non anime) you will need to also obtain an TMDB Api Key (for movies and tv shows)
    Variable Authentication method Value
    PLEX_USERNAME Username and password Your Plex Username
    PLEX_PASSWORD Username and password Your Plex Password
    PLEX_SERVER_NAME Username and password Your Plex Server Name
    PLEX_BASE_URL Token Your Plex Server base URL
    PLEX_TOKEN Token Your Plex Token
    PLEX_COLLECTION_PREFIX (Optional) Prefix for the created Plex collections. For example, with a value of "*", a collection named "Adventure", the name would instead be "*Adventure".

    Default value : ""
    TMDB_API_KEY Your TMDB api key (not required for anime library tagging)
  6. Optional, If you want to update the poster art of your collections. See posters/README.md

You are now ready to run the script

usage: plex-auto-genres.py [-h] [--library LIBRARY] [--type {anime,standard-movie,standard-tv}] [--set-posters] [--sort] [--rate-anime]
                           [--create-rating-collections] [--query QUERY [QUERY ...]] [--dry] [--no-progress] [-f] [-y]

Adds genre tags (collections) to your Plex media.

optional arguments:
  -h, --help            show this help message and exit
  --library LIBRARY     The exact name of the Plex library to generate genre collections for.
  --type {anime,standard-movie,standard-tv}
                        The type of media contained in the library
  --set-posters         uploads posters located in posters/<type> of matching collections. Supports (.PNG)
  --sort                sort collections by adding the sort prefix character to the collection sort title
  --rate-anime          update media ratings with MyAnimeList ratings
  --create-rating-collections
                        sorts media into collections based off rating
  --query QUERY [QUERY ...]
                        Looks up genre and match info for the given media title.
  --dry                 Do not modify plex collections (debugging feature)
  --no-progress         Do not display the live updating progress bar
  -f, --force           Force proccess on all media (independently of proggress recorded in logs/).
  -y, --yes

examples: 
python plex-auto-genres.py --library "Anime Movies" --type anime
python plex-auto-genres.py --library "Anime Shows" --type anime
python plex-auto-genres.py --library Movies --type standard-movie
python plex-auto-genres.py --library "TV Shows" --type standard-tv

python plex-auto-genres.py --library Movies --type standard-movie --set-posters
python plex-auto-genres.py --library Movies --type standard-movie --sort
python plex-auto-genres.py --library Movies --type standard-movie --create-rating-collections

python plex-auto-genres.py --type anime --query chihayafuru
python plex-auto-genres.py --type standard-movie --query Thor Ragnarok

Example Usage

Automating

I have conveniently included a script to help with automating the process of running plex-auto-genres when combined with any number of cron scheduling tools such as crontab, windows task scheduler, etc.

If you have experience with Docker I reccommend using my docker image which will run on a schedule.

  1. Copy .env.example to .env and update the values
  2. Copy config.json.example to config.json and update the values
  3. Each entry in the run list will be executed when you run this script
  4. Have some cron/scheduling process execute python3 automate.py, I suggest running it manually first to test that its working.

Note: The first run of this script may take a long time (minutes to hours) depending on your library sizes.

Note: Don't be alarmed if you do not see any text output. The terminal output you normally see when running plex-auto-genres.py is redirected to the log file after each executed run in your config.

Docker Usage

  1. Install Docker
  2. Install Docker Compose
  3. Clone or Download this repository
  4. Edit docker/docker-compose.yml
    1. Update the volumes: paths to point to the config,logs,posters directories in this repo.
    2. Update the environment: variables. See Getting Started.
  5. Copy config/config.json.example to config/config.json
    1. Edit the run array examples to match your needs. When the script runs, each library entry in this array will be updated on your Plex server.
  6. Run docker-compose up -d, the script will run immediately then proceed to run on a schedule every night at 1am UTC. Logs will be located at logs/plex-auto-genres-automate.log

Another Docker option of this tool can be found here.

Troubleshooting

  1. If you are not seeing any new collections close your plex client and re-open it.
  2. Delete the generated plex-*-successful.txt and plex-*-failures.txt files if you want the script to generate collections from the beginning. You may want to do this if you delete your collections and need them re-created.
  3. Having the release year in the title of a tv show or movie can cause the lookup to fail in some instances. For example Battlestar Galactica (2003) will fail, but Battlestar Galactica will not.
Owner
Shane Israel
Shane Israel
Vision-and-Language Navigation in Continuous Environments using Habitat

Vision-and-Language Navigation in Continuous Environments (VLN-CE) Project Website — VLN-CE Challenge — RxR-Habitat Challenge Official implementations

Jacob Krantz 132 Jan 02, 2023
Pytorch implementation of forward and inverse Haar Wavelets 2D

Pytorch implementation of forward and inverse Haar Wavelets 2D

Sergei Belousov 9 Oct 30, 2022
DLL: Direct Lidar Localization

DLL: Direct Lidar Localization Summary This package presents DLL, a direct map-based localization technique using 3D LIDAR for its application to aeri

Service Robotics Lab 127 Dec 16, 2022
This package contains a PyTorch Implementation of IB-GAN of the submitted paper in AAAI 2021

The PyTorch implementation of IB-GAN model of AAAI 2021 This package contains a PyTorch implementation of IB-GAN presented in the submitted paper (IB-

Insu Jeon 9 Mar 30, 2022
Whisper is a file-based time-series database format for Graphite.

Whisper Overview Whisper is one of three components within the Graphite project: Graphite-Web, a Django-based web application that renders graphs and

Graphite Project 1.2k Dec 25, 2022
Official implementation of the paper Image Generators with Conditionally-Independent Pixel Synthesis https://arxiv.org/abs/2011.13775

CIPS -- Official Pytorch Implementation of the paper Image Generators with Conditionally-Independent Pixel Synthesis Requirements pip install -r requi

Multimodal Lab @ Samsung AI Center Moscow 201 Dec 21, 2022
Voice control for Garry's Mod

WIP: Talonvoice GMod integrations Very work in progress voice control demo for Garry's Mod. HOWTO Install https://talonvoice.com/ Press https://i.imgu

Meta Construct 5 Nov 15, 2022
CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation

CPT This repository contains code and checkpoints for CPT. CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Gener

fastNLP 341 Dec 29, 2022
Repository of our paper 'Refer-it-in-RGBD' in CVPR 2021

Refer-it-in-RGBD This is the repository of our paper 'Refer-it-in-RGBD: A Bottom-up Approach for 3D Visual Grounding in RGBD Images' in CVPR 2021 Pape

Haolin Liu 34 Nov 07, 2022
[CVPR-2021] UnrealPerson: An adaptive pipeline for costless person re-identification

UnrealPerson: An Adaptive Pipeline for Costless Person Re-identification In our paper (arxiv), we propose a novel pipeline, UnrealPerson, that decreas

ZhangTianyu 70 Oct 10, 2022
Enigma-Plus - Python based Enigma machine simulator with some extra features

Enigma-Plus Python based Enigma machine simulator with some extra features Examp

1 Jan 05, 2022
Code for the Paper: Alexandra Lindt and Emiel Hoogeboom.

Discrete Denoising Flows This repository contains the code for the experiments presented in the paper Discrete Denoising Flows [1]. To give a short ov

Alexandra Lindt 3 Oct 09, 2022
Wordle-solver - Wordle answer generation program in python

🟨 Wordle Solver 🟩 Wordle answer generation program in python ✔️ Requirements U

Dahyun Kang 4 May 28, 2022
Jupyter notebooks for using & learning Keras

deep-learning-with-keras-notebooks 這個github的repository主要是個人在學習Keras的一些記錄及練習。希望在學習過程中發現到一些好的資訊與範例也可以對想要學習使用 Keras來解決問題的同好,或是對深度學習有興趣的在學學生可以有一些方便理解與上手範例

ErhWen Kuo 2.1k Dec 27, 2022
The deployment framework aims to provide a simple, lightweight, fast integrated, pipelined deployment framework that ensures reliability, high concurrency and scalability of services.

savior是一个能够进行快速集成算法模块并支持高性能部署的轻量开发框架。能够帮助将团队进行快速想法验证(PoC),避免重复的去github上找模型然后复现模型;能够帮助团队将功能进行流程拆解,很方便的提高分布式执行效率;能够有效减少代码冗余,减少不必要负担。

Tao Luo 125 Dec 22, 2022
Self-Supervised Learning with Kernel Dependence Maximization

Self-Supervised Learning with Kernel Dependence Maximization This is the code for SSL-HSIC, a self-supervised learning loss proposed in the paper Self

DeepMind 29 Dec 29, 2022
TensorLight - A high-level framework for TensorFlow

TensorLight is a high-level framework for TensorFlow-based machine intelligence applications. It reduces boilerplate code and enables advanced feature

Benjamin Kan 10 Jul 31, 2022
Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model.

Exposure: A White-Box Photo Post-Processing Framework ACM Transactions on Graphics (presented at SIGGRAPH 2018) Yuanming Hu1,2, Hao He1,2, Chenxi Xu1,

Yuanming Hu 719 Dec 29, 2022
A novel Engagement Detection with Multi-Task Training (ED-MTT) system

A novel Engagement Detection with Multi-Task Training (ED-MTT) system which minimizes MSE and triplet loss together to determine the engagement level of students in an e-learning environment.

Onur Çopur 12 Nov 11, 2022
Code repo for "Transformer on a Diet" paper

Transformer on a Diet Reference: C Wang, Z Ye, A Zhang, Z Zhang, A Smola. "Transformer on a Diet". arXiv preprint arXiv (2020). Installation pip insta

cgraywang 31 Sep 26, 2021