Update bundles

bundles/version.json

@@ -1,5 +1,5 @@
 {
-  "updated_at": "2025-01-21T00:46:33.606318+00:00",
+  "updated_at": "2025-01-21T04:33:16.372757+00:00",
   "folders": [
     "custom_formats",
     "profiles",

bundles/wiki.json

@@ -2,7 +2,7 @@
   {
     "_id": "EEi",
     "content": "This metric is aimed at identifying and ranking release groups based on their propensity to release encodes that meet certain compression ratios, with particular focus on HEVC releases where optimal efficiency occurs in specific bitrate ranges. By ranking these groups, we effectively prioritize releases that maximize HEVC's compression capabilities while maintaining quality at minimal file sizes.\n\n## What is a Compression Ratio?\n\nA compression ratio is a (made up) metric that evaluates encodes against their sources. We express this as the encoded file size as a percentage of its source size (typically a remux or WEB-DL).\n\nFor example:\n\n| Movie   | Source (Remux) | Encode | Compression Ratio |\n| ------- | -------------- | ------ | ----------------- |\n| Movie A | 40 GB          | 10 GB  | 25%               |\n| Movie B | 30 GB          | 6 GB   | 20%               |\n| Movie C | 50 GB          | 15 GB  | 30%               |\n\n## Why Is This Important?\n\nUnderstanding compression ratios helps balance two competing needs: maintaining high video quality while minimizing file size. Modern codecs like HEVC have a \"sweet spot\" where they deliver excellent quality with significant size savings. Finding this optimal point is crucial because:\n\n- Storage and bandwidth are always limited resources\n- Going beyond certain bitrates provides diminishing quality returns\n- Different codecs have different efficiency curves\n- Release groups need clear standards for quality vs. size trade-offs\n\n## What Ratio is Best?\n\nThere's no one-size-fits-all answer when it comes to choosing the perfect compression ratio. The \"best\" ratio depends entirely on the end user's priorities and constraints. At 1080p:\n\n- Space-conscious users might prefer smaller files around 5-10% of source size, accepting quality trade-offs\n- Quality-focused users might push towards 30-40% of source size for more transparent results\n- Most users find a sweet spot in the middle, balancing quality and size\n  However, there are clear technical limits where going larger becomes pointless - this is where we get to our maximum ratios of 40% and 60% for 1080p and 2160p, respectively?\n\n## Why Set Maximum Ratios of 40% and 60%?\n\nThe compression ratio ceilings are set based on different factors for 1080p and 2160p content:\n\n### 1080p (40% Maximum)\n\nThe 40% ceiling for 1080p exists because we can roughly measure where h265 stops being more efficient than h264. We do this using two key video quality metrics:\n\n- **VMAF,** developed by Netflix, analyzes how humans perceive video quality and scores it from 0-100\n- **BD-Rate** tells us how much smaller one encode is compared to another while maintaining the same quality level\n\nUsing these tools together shows us that:\n\n- HEVC achieves 20-40% smaller files in the mid-bitrate range (~2-10 Mbps for 1080p)\n- These space savings are consistent across different quality levels\n- Beyond this point, both old and new codecs saturate at near transparent quality, making HEVC's advantages disappear\n- At ratios above 40%, x264 becomes the preferred choice as encodes are easier to produce and typically undergo more rigorous quality control\n\n### 2160p (60% Maximum)\n\nThe 60% ceiling for 2160p content is based on different considerations:\n\n- This is approximately where transparency becomes achievable for most 2160p content\n- Higher ratios provide diminishing returns in perceived quality\n- At this compression level, most content achieves VMAF scores above 95\n- Storage efficiency becomes particularly important at 2160p due to the larger base file sizes\n- The relationship between bitrate and perceived quality is non-linear, with improvements becoming increasingly subtle beyond this point\n\nGive these articles a read to better understand how VMAF and BD-Rate tell us how efficient a codec is:\n\n- https://medium.com/innovation-labs-blog/bjontegaard-delta-rate-metric-c8c82c1bc42c\n- https://www.mdpi.com/2079-9292/13/5/953\n\n## How Do We Apply This Index?\n\nThe ranking system works by calculating how close each Release Group / Streaming Service comes to achieving a user's desired compression ratio. This is done through a few key steps:\n\n1. **Delta Calculation**: We calculate the absolute difference (delta) between a group's average compression ratio and the target ratio. For example, if a group averages 25% compression and our target is 20%, their delta would be |25 - 20| = 5 percentage points.\n\n2. **K-means Clustering**: We use k-means clustering to automatically group release groups into tiers based on their deltas. K-means works by:\n   - Starting with k random cluster centers\n   - Assigning each group to its nearest center\n   - Recalculating centers based on group assignments\n   - Repeating until stable\n\n# Example Rankings\n\n## 1080p Examples\n\n### Example 1: Users prioritizing storage efficiency (10% target)\n\nUsers might choose this very aggressive compressionLine truncated
-    "last_modified": "2025-01-21T00:46:31.582396+00:00",
+    "last_modified": "2025-01-21T04:33:14.361612+00:00",
     "title": "Encode Efficiency Index",
     "slug": "EEi",
     "author": "santiagosayshey",
@@ -15,8 +15,8 @@
   },
   {
     "_id": "home",
-    "content": "# Hello!\n\nWelcome to Dictionarry! This project aims to wiki-fy and simplify media automation in Radarr / Sonarr through extensive, data driven documentation, custom formats and quality profiles.\n\n## Motivation\n\nNavigating the world of **niche quality terms** like \"Remux\", or \"HEVC\" or \"Dolby Vision\" can be quite daunting when all you want to do is setup a media server to watch some content. If often **feels like you need a masters in audio / video just to grab the latest blockbuster.** Dictionarry aims not to explain these concepts in detail, but **abstract them into more approachable ideas** that don't require extensive knowledge or experience. \n\n### How?\n\nDictionarry leverages two key features of Radarr and Sonarr to simplify media automation:\n\n1. **Custom Formats** - Think of these as smart filters that scan release titles for specific patterns. They help identify important characteristics of your media, such as:\n   - Video quality (4K, HDR, Dolby Vision)\n   - Audio formats (Atmos, DTS, TrueHD)\n   - Source types (Remux, Web-DL, Blu-ray)\n   - Potential issues (upscaled content, poor encodes)\n\n2. **Quality Profiles** - These act like a scoring system that ranks releases based on their Custom Format matches. You can:\n   - Prioritize what matters most to you\n   - Automatically upgrade to better versions\n   - Avoid problematic releases\n\nThink of Dictionarry as your personal car-buying expert: Instead of researching every technical specification and test-driving dozens of vehicles, you get access to a curated showroom of pre-vetted options that match what you're looking for. Whether you want:\n\n- **2160p Remux** - Maximum quality 4K HDR remuxes with lossless audio and Dolby Vision\n- **2160p Quality** - Transparent 4K HDR encodes selected using the Encode Efficiency Index\n- **1080p Quality** - Transparent 1080p encodes optimized using the Golden Popcorn Performance Index\n- **1080p Efficient** - Efficient x265 1080p Encodes optimized to save space using the Encode Efficiency Index \n- And More....\n\nDictionarry's database of tested profiles and formats handles the technical decisions for you.\n\n### Profilarr\n\nThe database by itself, does nothing. Custom Formats and Quality Profiles need to be imported and configured in your individual arr installations. Rather than leaving you to manually create everything yourself based on this site, we've created **Profilarr** to automate this process.\n\nProfilarr is a configuration management tool for Radarr and Sonarr that can interface with ANY remote configuration database (not just Dictionarry's!). It automatically:\n\n- Pulls new updates from your chosen database\n- Compiles the database format into specific arr formats\n- Imports them to your arr installations\n- Manages version control of your configurations\n\nBuilt on top of git, Profilarr treats your configurations like code, allowing you to:\n\n- Track changes over time\n- Maintain your own customizations while still receiving database updates\n- Resolve conflicts between local / remote changes when they arise\n\nThe architecture was specifically built like this to put user choice first. We believe that:\n\n- Your media setup should reflect your needs, not our opinions\n- Updates should enhance your configuration, not override it\n- Different users have different requirements (storage constraints, hardware capabilities, quality preferences)\n- The ability to customize should never be sacrificed for convenience\n\nProfilarr empowers you to use Dictionarry's database (or anyone elses!) as a foundation while maintaining the freedom to adapt it to your specific needs.\n\n## Getting Started\n\nFrom here you have multiple options:\n\n- You can browse the wiki articles / development logs to learn more about our process / philosophy\n- You can head to the Profile Recommender to find a profile that suits you\n- You can view the Profile master list to look at all our profiles\n- You can get started with setting up Profilarr / connecting to a database / importing configs",
-    "last_modified": "2025-01-21T00:46:31.582396+00:00",
+    "content": "# Hello!\n\nWelcome to Dictionarry! This project aims to wiki-fy and **simplify media automation** in Radarr / Sonarr through extensive, data driven documentation, custom formats and quality profiles.\n\n## Motivation\n\nNavigating the world of media automation and coming across quality terms like \"Remux\", or \"HEVC\" or \"Dolby Vision\" can be quite daunting when all you want to do is setup a media server to watch some content. If often **feels like you need a masters in audio / video just to grab the latest blockbuster.** Dictionarry aims not to explain these concepts in detail, but **abstract them into more approachable ideas** that don't require extensive knowledge or experience.\n\nDictionarry leverages two key features of Radarr and Sonarr to simplify media automation:\n\n1. Custom Formats - Think of these as smart filters that scan release titles for specific patterns. They help **identify important characteristics** of your media, such as:\n\n   - Video quality (4K, HDR, Dolby Vision)\n   - Audio formats (Atmos, DTS, TrueHD)\n   - Source types (Remux, Web-DL, Blu-ray)\n   - Potential issues (upscaled content, poor encodes)\n\n2. Quality Profiles - These act like a scoring system that **ranks releases** based on their Custom Format matches. You can:\n   - Prioritize what matters most to you\n   - Automatically upgrade to better versions\n   - Avoid problematic releases\n\nThink of Dictionarry as your personal car-buying expert: Instead of researching every technical specification and test-driving dozens of vehicles, you get access to a curated showroom of pre-vetted options that match what you're looking for. Whether you want:\n\n- 2160p Remux - _Maximum quality_ 4K HDR remuxes with lossless audio and Dolby Vision\n- 2160p Quality - _Transparent 4K_ HDR encodes selected using the Encode Efficiency Index\n- 1080p Quality - _Transparent 1080p_ encodes optimized using the Golden Popcorn Performance Index\n- 1080p Efficient - _Efficient x265 1080p_ Encodes optimized to save space using the Encode Efficiency Index\n- And More....\n\nDictionarry's database of tested profiles and formats handles the technical decisions for you.\n\n## Profilarr\n\nThe database by itself does nothing. Custom Formats and Quality Profiles **need to be imported** and configured in your individual arr installations. Rather than leaving you to manually create everything yourself based on our guides, we've created **Profilarr** to automate this process.\n\nProfilarr is a **configuration management tool** for Radarr and Sonarr that can interface with **ANY remote configuration database** (not just Dictionarry's!). It automatically:\n\n- _Pulls_ new updates from your chosen database\n- _Compiles_ the database format into specific arr formats\n- _Imports_ them to your arr installations\n- Manages version control of your configurations\n\nBuilt on top of git, Profilarr treats your configurations like code, allowing you to:\n\n- Track changes over time\n- Maintain your own customizations while still receiving database updates\n- Resolve conflicts between local / remote changes when they arise\n\nThe architecture was specifically built like this to **put user choice first**. We believe that:\n\n- **Your media setup should reflect your needs, not our opinions**\n- Updates should enhance your configuration, not override it\n- Different users have different requirements (storage constraints, hardware capabilities, quality preferences)\n- The ability to customize should never be sacrificed for convenience\n\nProfilarr empowers you to use Dictionarry's database (or anyone elses!) as a foundation while maintaining the freedom to adapt it to your specific needs.",
+    "last_modified": "2025-01-21T04:33:14.361612+00:00",
     "title": "home",
     "slug": "home",
     "author": "santiagosayshey",
@@ -29,7 +29,7 @@
   {
     "_id": "GPPi",
     "content": "## What are Golden Popcorns?\n\n**_Golden Popcorns_** are _very high quality encodes_, marked as such by one of the best private torrent trackers. These releases are manually reviewed by a dedicated, experienced team of _Golden Popcorn_ checkers. Golden Popcorns are the simplest way to quantify a subjective _best_ encode.\n\n## The Decision Engine\n\nThe Golden Popcorn Performance Index, or GPPI, is a calculated metric, pivotal to the [Transparent](../Profiles/1080p%20Transparent.md) profile's decision-making process. It's engineered to rank release groups based on their propensity to release a Golden Popcorn encode at any given resolution $r$.\n\n## Formula\n\nOn first glance, it seems the most obvious way to determine which release groups are most likely to release golden popcorns is to find their Golden Popcorn Ratio, i.e. The number of Golden Popcorns divided by the total number of encodes for any given resolution _r_.\n\nHowever, If we were to take Golden Popcorn ratio at face value, we might incorrectly prioritise a release group who has a high GP ratio, but a low number of encodes. On the opposite spectrum, if we take the raw number of Golden Popcorns for any group, we might incorrectly prioritise a group with a low GP ratio.\n\nSo instead, we multiply the number of Golden Popcorns at resolution $r$ for a given release group, by a factor of said release group's Golden Popcorn Ratio. This essentially limits both metrics as a factor of each other.\n\nFor any given resolution _r_, the GPPI is defined as:\n\n$$\n\\begin{aligned}\n\\text{GPPI}_r &= GPE_r \\cdot \\left( \\frac{GPE_r}{E_r} \\right) \\\\\n              &= \\frac{GPE_r^2}{E_r}\n\\end{aligned}\n$$\n\nWhere:\n\n- $\\text{GPPI}_r$ is the Golden Popcorn Performance Index at resolution $r$\n- $GPE_r$ is the number of Golden Popcorns at resolution $r$\n- $E_r$ is the total number of encodes at resolution $r$",
-    "last_modified": "2025-01-21T00:46:31.582396+00:00",
+    "last_modified": "2025-01-21T04:33:14.361612+00:00",
     "title": "Golden Popcorn Performance Index",
     "slug": "GPPi",
     "author": "santiagosayshey",