Skip to content

Conversation

@HavenCTO
Copy link
Contributor

@HavenCTO HavenCTO commented Jan 5, 2026

Funscript Haven analyzes video content using computer vision techniques to detect motion patterns and automatically generate funscript files compatible with interactive devices. The plugin integrates seamlessly with StashApp, allowing you to queue scenes for processing by simply adding a tag.

Added README.md for Funscript Haven plugin detailing features, installation, usage, configuration, and troubleshooting.
This is a new plugin for StashApp that generates funscript files from video scenes using optical flow analysis. It includes functions for processing video, managing tags, and generating multi-axis funscripts.
Added Funscript Haven plugin configuration with processing settings and parameters.
This file contains configuration settings for the Funscript Haven plugin, including tag configurations, processing settings, mode settings, multi-axis settings, and marker settings.
Updated plugin settings to use integer values (0-10) for parameters such as detrend_window, norm_window, multi_axis_intensity, random_speed, auto_home_delay, and auto_home_duration, matching StashApp UI requirements. Adjusted internal logic to convert these integers to appropriate float values where needed. Updated documentation, config, and YAML to reflect these changes and clarified conversion behavior for users. Also fixed references to the correct config file and improved error handling and dependency management.
Added robust video file validation using OpenCV and ffprobe before processing. Enhanced VideoReader initialization with multiple fallback strategies to handle problematic video streams and improve compatibility, including better error logging and handling for various failure scenarios.
Introduces detection and configuration for Intel Arc GPUs to enable AV1 hardware-accelerated decoding via VAAPI. Adds fallback to software decoding if hardware acceleration fails, with improved error handling and logging throughout the video processing pipeline.
Introduces a fetch_frames_opencv function to extract frames using OpenCV when decord fails, improving compatibility with problematic video files. Updates process_video and related logic to use this fallback, including property extraction and threaded frame fetching.
Adds checks and logging for cases where frame extraction fails or yields insufficient frames when using OpenCV fallback. Enforces software decoding to avoid AV1 hardware errors and ensures early abort if initial frames cannot be fetched, improving robustness and compatibility.
@DogmaDragon DogmaDragon merged commit 359ebe7 into stashapp:main Jan 5, 2026
1 check passed
@DogmaDragon DogmaDragon added the type:plugin Plugins label Jan 5, 2026
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

Projects

None yet

Development

Successfully merging this pull request may close these issues.

2 participants