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
This repo holds code for TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

TransUNet This repo holds code for TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation Usage

1.4k Jan 04, 2023
This program will stylize your photos with fast neural style transfer.

Neural Style Transfer (NST) Using TensorFlow Demo TensorFlow TensorFlow is an end-to-end open source platform for machine learning. It has a comprehen

Ismail Boularbah 1 Aug 08, 2022
details on efforts to dump the Watermelon Games Paprium cart

Reminder, if you like these repos, fork them so they don't disappear https://github.com/ArcadeHustle/WatermelonPapriumDump/fork Big thanks to Fonzie f

Hustle Arcade 29 Dec 11, 2022
A general python framework for visual object tracking and video object segmentation, based on PyTorch

PyTracking A general python framework for visual object tracking and video object segmentation, based on PyTorch. 📣 Two tracking/VOS papers accepted

2.6k Jan 04, 2023
Official implementation of the network presented in the paper "M4Depth: A motion-based approach for monocular depth estimation on video sequences"

M4Depth This is the reference TensorFlow implementation for training and testing depth estimation models using the method described in M4Depth: A moti

Michaël Fonder 76 Jan 03, 2023
We will release the code of "ConTNet: Why not use convolution and transformer at the same time?" in this repo

ConTNet Introduction ConTNet (Convlution-Tranformer Network) is proposed mainly in response to the following two issues: (1) ConvNets lack a large rec

93 Nov 08, 2022
A series of Jupyter notebooks with Chinese comment that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

Hands-on-Machine-Learning 目的 这份笔记旨在帮助中文学习者以一种较快较系统的方式入门机器学习, 是在学习Hands-on Machine Learning with Scikit-Learn and TensorFlow这本书的 时候做的个人笔记: 此项目的可取之处 原书的

Baymax 1.5k Dec 21, 2022
Attentive Implicit Representation Networks (AIR-Nets)

Attentive Implicit Representation Networks (AIR-Nets) Preprint | Supplementary | Accepted at the International Conference on 3D Vision (3DV) teaser.mo

29 Dec 07, 2022
This is a project based on retinaface face detection, including ghostnet and mobilenetv3

English | 简体中文 RetinaFace in PyTorch Chinese detailed blog:https://zhuanlan.zhihu.com/p/379730820 Face recognition with masks is still robust---------

pogg 59 Dec 21, 2022
Bidimensional Leaderboards: Generate and Evaluate Language Hand in Hand

Bidimensional Leaderboards: Generate and Evaluate Language Hand in Hand Introduction We propose a generalization of leaderboards, bidimensional leader

4 Dec 03, 2022
Repositório da disciplina de APC, no segundo semestre de 2021

NOTAS FINAIS: https://github.com/fabiommendes/apc2018/blob/master/nota-final.pdf Algoritmos e Programação de Computadores Este é o Git da disciplina A

16 Dec 16, 2022
Implementation of the master's thesis "Temporal copying and local hallucination for video inpainting".

Temporal copying and local hallucination for video inpainting This repository contains the implementation of my master's thesis "Temporal copying and

David Álvarez de la Torre 1 Dec 02, 2022
AbelNN: Deep Learning Python module from scratch

AbelNN: Deep Learning Python module from scratch I have implemented several neural networks from scratch using only Numpy. I have designed the module

Abel 2 Apr 12, 2022
Automatic voice-synthetised summaries of latest research papers on arXiv

PaperWhisperer PaperWhisperer is a Python application that keeps you up-to-date with research papers. How? It retrieves the latest articles from arXiv

Valerio Velardo 124 Dec 20, 2022
The code for our NeurIPS 2021 paper "Kernelized Heterogeneous Risk Minimization".

Kernelized-HRM Jiashuo Liu, Zheyuan Hu The code for our NeurIPS 2021 paper "Kernelized Heterogeneous Risk Minimization"[1]. This repo contains the cod

Liu Jiashuo 8 Nov 20, 2022
Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

Kai Zhang 2k Dec 31, 2022
Code for SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes (NeurIPS 2021)

SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes (NeurIPS 2021) SyncTwin is a treatment effect estimation method tailored for observat

Zhaozhi Qian 3 Nov 03, 2022
Scripts and misc. stuff related to the PortSwigger Web Academy

PortSwigger Web Academy Notes Mostly scripts to automate the exploits. Going in the order of the recomended learning path - starting with SQLi. Commun

pageinsec 17 Dec 30, 2022
The source code for CATSETMAT: Cross Attention for Set Matching in Bipartite Hypergraphs

catsetmat The source code for CATSETMAT: Cross Attention for Set Matching in Bipartite Hypergraphs To be able to run it, add catsetmat to PYTHONPATH H

2 Dec 19, 2022
Pre-training of Graph Augmented Transformers for Medication Recommendation

G-Bert Pre-training of Graph Augmented Transformers for Medication Recommendation Intro G-Bert combined the power of Graph Neural Networks and BERT (B

101 Dec 27, 2022