June 10, Update: stmfnet
Just to save folks a headache the file is available for download as a model now.
June 06, Update: V4.0
Just a minor improvement, using a double interpolation of SFTMVFI results in higher fidelity of dynamic or fast motion scenes. Video is manually loaded to reduce time when generating high quantities of test runs. Now you can select which videos you want to upscale, will copy the name of the original input video.
Included the context framing node from Kijai's wrapper. Usually leave this off will exponentially increase generation times if on; however, can let you generate much longer videos beyond what your vram will allow you.
Interpolation requires higher VRAM if scaling if greater than 1.0. Changed the scaling factor to float for more control.
Updated nodes if there is any issues feel free to let me know.
https://drive.google.com/file/d/1s5JJdt5X69AO2E2uuaes17aPwlWIQagG/view
Place it in the folder: Custom_nodes\ComfyUI-Frame-Interpolation\ckpts\stmfnet
April 14, Update: V3.3
Updated Nodes.
March 27, Update: V3.2
Small changes to the Torch Compile and Tea Cache for more dynamic outputs using my Lora's.
Workflow is suitable for a 24GB card using the 14B models and a 12GB card using the 1.3B model.
Updates:
***Error within the naming of outputs corrected.
Uploaded a very simple and straightforward Wan I2V workflow. The workflow includes an upscaler with frame interpolation to bring your videos to a cool and smooth 60FPS. No BS just a simple addition. Original WanI2V is based on the workflow example of the amazing work from Kijai linked here: https://github.com/kijai/ComfyUI-WanVideoWrapper/tree/main/example_workflows.
Additionally, I've left the annotations within.
Prev Updates:
Compatible with 12GB memory cards. Tested using a 3060 RTX 12GB using this workflow can comfortably go up to 85 frames. 97 Frames is pushing the absolute limits will take about an hour to generate.
Due to demand this workflow is a small improvement to the Super Simple HV2V for those who don't do postprocessing outside of Comfyui.
Designed for use with Hunyuan Video and trained Lora models, it can upscale videos to true 60 FPS. It combines detailed notes on denoising strength, step optimization, aspect ratio adjustments, frame interpolation, and upscaling to create high-quality, smooth videos.
Order matters:
Generate → Upscale → Interpolate. Upscaling first preserves detail for interpolation.
Adjust parameters based on your Lora’s behavior and hardware limits.
Description
Includes a workflow that brings your Wan2.1 Gens to 60FPS including an upscaler.
FAQ
Comments (10)
Hey, thanks for your effort creating this workflow. I have a 3080TI with 12GB and 32GB RAM. Without changing any settings, I keep failing the workflow with the memory allocation issue. Could you provide something you've generated with this workflow that contains the json?
I'll upload something shortly that currently runs at 15gb Vram and some instructions to save on vram
https://civitai.com/images/64618913 Try this and change the Wanvideo BlockSwap to 38 from 20
You will need to have Triton installed and working for this btw.
Did it work?
@sikasolutionsworldwide709 Yes, I was able to make it work.
@dreadfulpirate Mhh I tried the wf with the recommended change bs 38 but I get allocation issue. I have RTX4070 12GB and 32GB RAM did u change anything else?
@sikasolutionsworldwide709 I will get back to you.
Is there any way to control timeline in I2V Wan? i mean prompt scheduling? if yes, how? frustating the the AI must do all the storytelling
There is a way; however, I haven't played around with that feature yet. Best to start at the base and work up from there I suppose.
Hello! getting this error; The size of tensor a (75) must match the size of tensor b (74) at non-singleton dimension 3, any ideas? Thanks