Tyson Ibele has unveiled version 1.111 of TyFlow, introducing the new tyDiffusion module which integrates Stable Diffusion directly into 3ds Max. Check it out!
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This feature is available for both tyFlow Pro and Free users, and it is compatible with 3ds Max 2023 and later. Accessible from any viewport shading context menu, tyDiffusion includes automated installation of necessary modules and a selection of popular models.
Main Features.
Key features of tyDiffusion include the ability to bake generated images onto models, advanced support for IP-Adapter, ControlNet, Upscaling, and extensive Prompt and LORA stylization. It fully supports AnimateDiff, prompt scheduling, and frame interpolation, provides 1:1 translation to ComfyUI Nodes, and includes a built-in asset library for ControlNet animation. Additionally, an experimental tyDiffusionTexGen modifier is included.
Additional Improvements.
Beyond the headline features, this release includes several less prominent but significant improvements. The tyCache export settings now include a “pivot” export channel, enhancing compatibility with Multifracture meshes. The Birth Flow and Flow Update operators can import pivot-modification data from tyCaches, improving data consistency.
The Alembic point cloud exporter has a new name preset menu and custom float/vector prefixes options. The Terrain Display operator prints grid height information to the MAXScript Listener, facilitating Unreal Engine conversion. The Terrain Tile operator has new naming convention options, and the Export Terrain operator supports Unreal Engine-compatible resample resolutions. Additionally, the Actor Animation operator now includes a start/stop animation loop and normalized time modes, and the “editor_close()” MAXScript function has been added to tyFlow objects.
Watch the video presentation of this promising new AI tool for 3DS Max below:
For more details and to download the plugin, visit the TyFlow website.
tyFlow is an unofficial replacement for 3ds Max's Particle Flow. It is not merely an upgrade to Particle Flow - rather, it was created from scratch with a design philosophy focused on squeezing as much speed and power out of modern multi-core systems as possible.
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