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A not-so-simple slideshow application

Project description

enkan dev

A not-so-simple slideshow application for building rich, weighted photo and video playlists that you can drive with a lean Tkinter UI. enkan reads structured text input, builds a tree of sources, and serves images (and optional video) according to the weighting rules you specify.

Of course, enkan can show you images completely at random, but its real power comes as you delve deeper into weighting and grafting, giving you complete control over the balance of images you see.

For release history, see CHANGELOG.md.

Requirements

  • Python ≥3.11
  • Pillow
  • python-vlc (for video support)
  • matplotlib (for tree visualization)
  • tqdm (progress bars)

Optional:

  • customtkinter (enhanced GUI appearance)
  • Python ≥3.11
  • Pillow
  • python-vlc (for video support)
  • matplotlib (for tree visualization)
  • tqdm (progress bars)

Optional:

  • customtkinter (enhanced GUI appearance)

Installation

Using uv (recommended)

uv tool install enkan

From PyPI

pip install enkan

From source

git clone https://github.com/benzo8/enkan.git
cd enkan
pip install -e .

If you install into a fresh environment, remember to install VLC separately so that python-vlc can find the native libraries.

Features

  • Weighted, fully random, sequential, folder-burst, and controlled-random image providers
  • Tree-based directory organization with grafting
  • Persistent viewing history, including across temporary scope changes
  • Folder-aware subfolder and parent navigation modes
  • EXIF orientation support
  • Image caching and background preload for performance
  • Video playback support (via VLC)
  • Interactive GUI with zoom/pan
  • Rotation persistence to EXIF

Quick Start

  1. Collect your image (and optional video) folders.
  2. Create a text file (for example shows/summer-show.txt) that lists the folders you want to include. You can mix folders, individual files, nested .txt files, and inline weighting rules.
  3. Launch enkan and point it at the file:
enkan --input_file shows/summer-show.txt --run

enkan will parse the file, build an in-memory tree, and open the slideshow window. Use the keyboard controls to navigate and switch providers. Add --auto 8 to advance every eight seconds, or --random to start in completely random mode.

Runtime Providers

enkan currently ships with five runtime image providers:

  • weighted - the default weighted/balanced behavior, using the tree-derived image weights
  • random - pure random selection, ignoring weights
  • sequential - simple linear stepping through the current image set
  • burst - weighted selection of a folder seed, then a short burst of images from that folder
  • controlled_random_weighted (CRW) - a weighted provider with folder-level memory that reduces obvious streaks and repeatedly favors folders that have not been seen for a while

Controlled Random Weighted (CRW)

CRW is deliberately less statistically random than plain weighted selection so that it feels more random to a human viewer.

It keeps the existing image and folder weightings, but adds folder-level memory:

  • recently seen folders are cooled off
  • folders that have not been seen for a while are gradually boosted
  • repeated streaks from the same folder are penalised

The result is usually a slideshow that feels less clumpy than pure weighted random, while still respecting the underlying weighting rules.

.txt Input Files

Text files let you describe complex shows declaratively. General rules:

  • One path per non-empty line. Lines starting with # are comments.
  • Windows paths can use \\ or /. Surround a path with quotes if it contains spaces or commas.
  • You can reference other .txt, .lst, or .tree files. enkan resolves them recursively.
  • Place any number of square-bracket modifiers before the path to alter weighting, grouping, or behaviour.
  • "Level" refers to the tree depth, which mirrors the folder depth (unless grafted), starting from root = 1

Common Modifiers

Syntax Meaning
[r] Set the entire show to run in fully random mode.
[+]keyword Only include files whose path contains keyword. Repeat for multiple must-match terms.
[-]keyword Exclude any path containing keyword. If you give an absolute file or folder, that path is skipped entirely.
[NN%] Multiply a branch's weight by NN% relative to its siblings (e.g. [150%] gives that branch 1.5x the default share).
[NN] For individual images, repeat the image NN times in the weighted pool. Useful for spotlighting a favourite shot.
[%NN%] Reserve NN% of the parent branch's share for this node and divide the remainder among siblings.
[bN] Switch the weighting mode at level "N" to balanced (b). Example: [b2] keeps siblings at level 2 evenly balanced.
[wN[,slope]] Switch the weighting mode at level "N" to weighted (w), using descendant counts to apportion remaining percentage. Negative slopes favour smaller folders, positive slopes flatten toward balanced.
[gN] Graft this branch up to tree level N, letting you bubble deep folders to a shallower menu.
[>group-name] Assign the line to a named group so you can share grafting, proportion, or mode changes. Combine with a * line to define the group (see below).
[f] Treat a directory as a flat bucket: gather every image under it into one node instead of mirroring the folder hierarchy.
[v] / [nv] Force-enable or disable video for this branch (overrides the default or CLI flag).
[m] / [nm] Force the slideshow to mute or unmute when media from this branch plays.
[/] Do not recurse beyond this directory; only its direct files are considered.

Modifiers can appear in any order so long as they precede the path, for example:

[%40%][b3]D:\Media\Family Archive
[150%][v]E:\Clips\Action Cams
[>portraits][g3]F:\Photos\Portrait Sessions

Global Defaults and Groups

Use a line whose path is just * to define global or group-level behaviour:

[b1w2]*                                     # Balanced top level, weighted from level 2 downward
[v][nm]*                                    # Default to video enabled and audio unmuted
[>portraits][g3][%30%][w4,-20]*             # Define the "portraits" group once
[>portraits]F:\Photos\Portrait Sessions     # Apply the group to a folder

A group definition stores graft level, proportion, and mode modifiers. Any line tagged with the same [>group] inherits those settings.

Nesting Other Files

  • Pointing at another .txt file in a line imports everything from that file at the current position. (Only the Global Defaults from the top-level file are honoured.)
  • .lst files are either:
    • plain CSV lines (absolute\path\to\image.jpg,weight). They are useful when you already have a hand-curated weighted list
    • new-line delimited lists of files (absolute\path\to\image.jpg), as produced by irfanView, et al
  • .tree files are binary snapshots produced by --outputtree. enkan reuses them if the embedded version matches; otherwise it falls back to the sibling .txt / .lst source.

CLI Reference

Option Purpose
-i, --input_file One or more .txt, .lst or .tree files, or folder and/or file paths (including [modifiers] if desired) to process.
--run Explicitly launch the slideshow (optional when you omit --output*).
--outputlist [filename] Write a weighted .lst file instead of launching the GUI.
--outputtree [filename] Persist the computed tree to a .tree file for fast reloads instead of lauching the GUI.
--mode Provide a global mode string such as b1w2 to override file defaults.
--random Start in fully random mode (same as [r] in a file).
--auto N Advance automatically every N seconds.
--no-recurse Treat every supplied folder as non-recursive.
--video / --no-video Force-enable or disable video globally.
--no-mute Keep audio tracks unmuted (video default is muted).
--no-background Run loaders in the foreground (useful when debugging).
--test N Run N randomised draws and report the observed distribution. Combine with --histo for a matplotlib histogram.
--test_model, --tm Comma-separated provider suffixes to compare during --test, for example weighted,controlled_random_weighted.
--printtree Emit a text representation of the computed tree.
--testdepth, --histo, --debug Extra diagnostics for tuning your weighting setup.

Hotkeys (active during slideshow)

Key Function
Space Next image
Left Back through history
Right Forward through history
Up Next sequential image
Down Previous sequential image
N Toggle the information line
C Select fully random provider
W Select weighted/balanced provider
D Select controlled-random weighted (CRW) provider
Shift-D Cycle CRW status display: off / friendly / useful / debug
L Select linear / sequential provider
B Select Folder Burst mode
Ctrl-B Reset Folder Burst mode and force a new burst seed
S Toggle Subfolder mode
T Toggle Navigation mode between Branch and Folder
P Follow branch/folder down into Parent Mode
O Follow branch/folder up within Parent Mode
I Step backwards through Parent Mode stack
U Reset Parent Mode
Ctrl-D Clear controlled-random folder memory for the current scope
M Toggle mute
R Rotate image clockwise by 90 degrees
Ctrl-R Try to write current orientation to image EXIF data
Delete Delete current image or video
= / + / - Zoom image
0 Reset Zoom
Shift-Cursor Move viewport around zoomed image
A Toggle Auto-Advance (Timed) Mode

Navigation and Parent Mode

enkan can navigate in two modes:

  • Branch - Parent Mode moves up and down the branches of the tree
  • Folder - Parent Mode moves up and down the folder structure of the disk. If the folder you move to is not in the tree, enkan will need to read all the files below the current folder, whether they are in you input files or not. This can take a lot of time.

Subfolder mode and Parent mode temporarily restrict future selection to a smaller scope, but your viewer history is still preserved across those scope changes. If you explicitly go back, enkan can revisit images you saw before entering the temporary scope.

Working With Lists and Trees

  • Run enkan -i show.txt --outputlist to capture the fully expanded list (including virtual nodes and weights) into show.lst.
  • Run enkan -i show.txt --outputtree to produce show.tree, a binary cache you can ship with a release for faster loading.
  • Combine --printtree and --test while iterating on your .txt files to confirm that proportions and grafting behave the way you expect.
  • Use --tm weighted,controlled_random_weighted with --test when you want to compare plain weighted behavior against CRW distribution on the same dataset.

Tips

  • Keep your .txt files in source control alongside the media curations—they capture the intent of the show far better than flat lists.
  • Use groups to coordinate related folders (for example all portrait shoots) without repeating the same graft and mode modifiers on every line.
  • When emphasising a single standout image, prefer an absolute modifier like [25] on the image line instead of inflating nearby branches.
  • Large libraries benefit from building a .tree once and reusing it until the folder structure changes; enkan automatically regenerates it if the pickle version does not match.

Have fun!

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