Stop scrolling through thousands of videos. Classi-Cine is like autocomplete for video selection - it predicts what you want to watch next based on your feedback, helping you rapidly build the perfect playlist for your current mood.
You have a large video collection but finding what matches your current mood is tedious:
- Manually browsing through hundreds or thousands of files
- Remembering which episodes or clips you enjoyed
- No quick way to find "videos like this one"
- Building playlists by hand takes forever
Classi-Cine plays 20-questions with your video collection to rapidly zero in on what you want:
- Point it at your video directories - Let it discover your collection
- It suggests videos, you accept/reject - Like/dislike using VLC controls (stop = accept, pause = reject)
- Watch recommendations improve in real-time - Each decision teaches the AI what you're looking for
- Build your perfect playlist faster - Find content that matches your current mood in minutes, not hours
Perfect for:
- Large media collections (TV series, movies, documentaries, clips)
- Content creators curating references or footage
- Anyone with 100+ videos who wants smart discovery
- Building themed playlists (action movies, comedy episodes, tutorial clips, etc.)
# Install
cargo install classi-cine
# Start building a playlist - the AI will suggest additions
classi-cine build my-playlist.m3u ~/Videos ~/Movies
# The TUI shows AI predictions ranked by relevance
# Press Enter to preview in VLC
# Stop (s) to accept and add to playlist, pause (space) to reject
# Watch suggestions get smarter with each decision!Like autocomplete for text, Classi-Cine learns patterns from your video collection and predicts what you want next:
- Analyzes your entire collection - Understands file names, folder structure, sizes, and ages
- Uses machine learning - Multiple AI classifiers work together to score every video
- Learns from your feedback - Each accept/reject teaches it more about your preferences
- Predicts better matches - Rankings improve in real-time as you build your playlist
Simple VLC Integration:
- Stop video (s key) = "Yes, add this to my playlist"
- Pause video (space) = "No, this doesn't fit"
- Standard M3U playlists work in any media player
VLC is required for video playback.
Ensure you have Rust and Cargo installed. If not, you can install them using rustup.
# Build from the cargo.io crate registry.
$ cargo install classi-cine# Clone this repository
$ git clone https://github.com/mason-larobina/classi-cine.git
# Go into the repository
$ cd classi-cine
# Build and install it locally
$ cargo install --path=.Usage: classi-cine [OPTIONS] <COMMAND>
Commands:
build Build playlist through interactive classification
score Score files using trained classifiers without interactive classification
list-positive List classified files
list-negative
move Move playlist to a new location and rebase paths
help Print this message or the help of the given subcommand(s)
Options:
--log-level <LOG_LEVEL> [default: info]
-h, --help Print helpBuild a playlist through interactive VLC classification:
classi-cine build [OPTIONS] <PLAYLIST> [DIRS]...
Arguments:
<PLAYLIST> M3U playlist file
[DIRS]... Directories to scan for video files
Options:
--video-exts <VIDEO_EXTS> Video file extensions to scan for [default: avi,flv,mov,f4v,flv,m2ts,m4v,mkv,mpg,webm,wmv,mp4]
--windows <WINDOWS> [default: 5]
--file-size-bias <FILE_SIZE_BIAS> Bias scoring based on file sizes (log base, > 1.0). Negative reverses bias
--file-size-offset <FILE_SIZE_OFFSET> Offset to add to file size before log scaling [default: 1048576]
--dir-size-bias <DIR_SIZE_BIAS> Bias scoring based on directory sizes (log base, > 1.0). Negative reverses bias
--dir-size-offset <DIR_SIZE_OFFSET> Offset to add to directory size before log scaling [default: 0]
--file-age-bias <FILE_AGE_BIAS> Bias scoring based on file age (log base, > 1.0). Negative reverses bias
--file-age-offset <FILE_AGE_OFFSET> Offset to add to file age in seconds before log scaling [default: 86400]
--fullscreen Fullscreen VLC playback
--vlc-timeout <VLC_TIMEOUT> Timeout in seconds for VLC startup [default: 60]
--vlc-poll-interval <VLC_POLL_INTERVAL> Polling interval in milliseconds for VLC status checks [default: 100]
--batch <BATCH> Number of entries to classify in each batch iteration [default: 1]
--random-top-n <RANDOM_TOP_N> Select next entry randomly from top-n scored entries
-h, --help Print helpScore files using trained classifiers without interactive classification:
classi-cine score [OPTIONS] <PLAYLIST> [DIRS]...
Arguments:
<PLAYLIST> M3U playlist file
[DIRS]... Directories to scan for video files
Options:
--video-exts <VIDEO_EXTS> Video file extensions to scan for [default: avi,flv,mov,f4v,flv,m2ts,m4v,mkv,mpg,webm,wmv,mp4]
--windows <WINDOWS> [default: 5]
--file-size-bias <FILE_SIZE_BIAS> Bias scoring based on file sizes (log base, > 1.0). Negative reverses bias
--file-size-offset <FILE_SIZE_OFFSET> Offset to add to file size before log scaling [default: 1048576]
--dir-size-bias <DIR_SIZE_BIAS> Bias scoring based on directory sizes (log base, > 1.0). Negative reverses bias
--dir-size-offset <DIR_SIZE_OFFSET> Offset to add to directory size before log scaling [default: 0]
--file-age-bias <FILE_AGE_BIAS> Bias scoring based on file age (log base, > 1.0). Negative reverses bias
--file-age-offset <FILE_AGE_OFFSET> Offset to add to file age in seconds before log scaling [default: 86400]
--include-classified Include already classified files in the score listing
--no-header Skip header output for machine-readable format
--include-size Include file size in bytes in output
--json Output results in JSON format
--reverse Reverse output order (lowest scores first)
--by-dir Group results by directory and aggregate scores
--absolute Display absolute paths instead of relative to current directory
-h, --help Print helpList positively or negatively classified files:
classi-cine list-positive [OPTIONS] <PLAYLIST>
classi-cine list-negative [OPTIONS] <PLAYLIST>
Arguments:
<PLAYLIST> M3U playlist file
Options:
--absolute Display absolute paths instead of relative to current directory
-h, --help Print helpMove playlist to a new location and rebase paths:
classi-cine move <ORIGINAL> <NEW>
Arguments:
<ORIGINAL> Original M3U playlist file
<NEW> New M3U playlist file location
Options:
-h, --help Print helpFor developers and ML enthusiasts, Classi-Cine uses several sophisticated techniques:
Multi-Classifier Architecture:
- Naive Bayes Classifier: Uses byte-pair encoding tokenization to learn patterns from file paths and folder names
- File Size Classifier: Logarithmic scoring based on file sizes (configurable bias for larger/smaller files)
- Directory Size Classifier: Scoring based on number of files in directories
- File Age Classifier: Scoring based on file creation time
- All classifiers use normalized scores that are combined for final ranking
Advanced Tokenization:
- Byte pair encoding learns frequent character sequences from your specific collection
- Language and character set agnostic - works with any naming convention
- Adaptive tokenization learns from your library's patterns
- N-gram analysis for sequence pattern recognition
Performance Optimizations:
- Probabilistic filters and parallel processing for efficient tokenization
- Sharded data structures for multi-core processing
- Background VLC control with multi-threaded communication
- Incremental M3U saves for long classification sessions
VLC Integration:
- Uses VLC's HTTP interface for status monitoring
- Multi-threaded VLC control with background processing
- Automatic process lifecycle management
- Real-time classification feedback loop
We're open to contributions! Enhancements, bug fixes, documentation improvements, and more are all welcome.
This project is licensed under the MIT License. See LICENSE for details.
Made with ❤️ and Rust.