Mindket

Smooth Gen

Newversion 1 · updated

Overview

Smooths stop-motion footage and the gaps between generated images, using the RIFE and Adetailer models. For animators and image-generation users who want steadier motion between frames.

Smooth Gen is a kit in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.

At a glance

You need
  • Python 3.12
  • Windows, macOS or Linux
  • The packages listed in requirements.txt
Runs in
  • A web browser, on the page of the Space at Hugging Face
  • Windows, macOS or Linux, as a local copy run with Python 3.12
Start with
pip install -U huggingface_hub
hf download alrobles/smooth_gen --repo-type space --local-dir smooth_gen
cd smooth_gen

Platform

WindowsOperating system
macOSOperating system
LinuxOperating system

About

What it is

Smooth Gen evens out stop-motion animation and the jumps between generated images. It is a small Gradio app that names two models, RIFE and Adetailer, in its setup. The README is a single line, so the exact controls are not described there.

Who it suits

It suits animators and AI-image users whose sequences look jumpy from one frame to the next. It also suits developers who want a compact example of a Gradio app that runs on a GPU Space.

IndustryWho uses itHow they use itExample
AnimationStop-motion artistsSoften the jumps between photographed framesLoad a short clip and compare it with the original
Creative AIImage-generation usersLink generated images into a steadier sequenceSmooth a run of images that share one subject
Social mediaShort-video makersMake quick clips look less choppyPrepare a loop for posting
SoftwareGradio developersRead a compact app built on two named modelsCopy the folder and run it locally

Anyone who wants to generate new images from a prompt can skip it, since this app works on frames you already have.

Where to use it

The app runs in two places.

  • A web browser, on the page of the Space at Hugging Face
  • Windows, macOS or Linux, as a local copy run with Python 3.12
Use caseWhoWhat they get back
Stop-motion smoothingAnimatorsA steadier sequence from choppy frames
Generation gapsImage-generation usersA smoother link between generated images
App studyDevelopersA short repository with the app file and its packages

How to set it up

The online page needs nothing installed. A local copy needs the following.

  • Python 3.12
  • Windows, macOS or Linux
  • The packages listed in requirements.txt
  1. Install Python 3.12.
  2. Install the Hugging Face hub package and download a copy of the Space.
  3. Move into the new folder and install Gradio 6.31.0 and the packages in requirements.txt.
  4. Start the app with python app.py.
pip install -U huggingface_hub
hf download alrobles/smooth_gen --repo-type space --local-dir smooth_gen
cd smooth_gen
pip install gradio==6.31.0
pip install -r requirements.txt
python app.py

How to use it

Open the page in a browser, load the frames or images you want smoothed, and run it. On a local copy, this command starts the page.

python app.py
ToolWhat it does
RIFEA model the Space names, used to fill the gaps between frames
AdetailerA second model the Space names, used to refine the images
app.pyHolds the Gradio page
requirements.txtLists the Python packages the app needs

Example

You have a stop-motion clip with visible jumps between frames. You load it into the page and run it, and you get back a smoother sequence to compare with the original.

For newcomers and experts

If you are new to this, start with a short clip of only a few frames. Run it once and watch the motion, then judge whether the gaps look softer.

If you know the field, the Space names two models, r3gm/RIFE and Bingsu/adetailer, and runs on a ZeroGPU Space with A10G hardware. The repository has only the app file, the requirements and the README, so the pipeline order and settings are best read from app.py itself.

  1. Load frames or images
  2. RIFE fills the gaps between them
  3. Adetailer refines the images
  4. A smoother sequence comes back

Good to know

The Space page gives one line of description and no usage guide. Read app.py to see what each control does.

  • License: MIT
  • Cost to run: none named
  • Data it reaches: the frames or images you give it, and the two models it names
  • Hardware: ZeroGPU with an A10G at Hugging Face

README and files

README

Smooth Gen

Smooths stop-motion footage and the gaps between generated images, using the RIFE and Adetailer models. For animators and image-generation users who want steadier motion between frames.

Made by alrobles on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face.

About

What it is: Smooth Gen evens out stop-motion animation and the jumps between generated images. It is a small Gradio app that names two models, RIFE and Adetailer, in its setup. The README is a single line, so the exact controls are not described there.

Who it suits: It suits animators and AI-image users whose sequences look jumpy from one frame to the next. It also suits developers who want a compact example of a Gradio app that runs on a GPU Space.

Industry | Who uses it | How they use it | Example
Animation | Stop-motion artists | Soften the jumps between photographed frames | Load a short clip and compare it with the original
Creative AI | Image-generation users | Link generated images into a steadier sequence | Smooth a run of images that share one subject
Social media | Short-video makers | Make quick clips look less choppy | Prepare a loop for posting
Software | Gradio developers | Read a compact app built on two named models | Copy the folder and run it locally

Anyone who wants to generate new images from a prompt can skip it, since this app works on frames you already have.

Where to use it: The app runs in two places.

  • A web browser, on the page of the Space at Hugging Face
  • Windows, macOS or Linux, as a local copy run with Python 3.12
Use case | Who | What they get back
Stop-motion smoothing | Animators | A steadier sequence from choppy frames
Generation gaps | Image-generation users | A smoother link between generated images
App study | Developers | A short repository with the app file and its packages

How to set it up: The online page needs nothing installed. A local copy needs the following.

  • Python 3.12
  • Windows, macOS or Linux
  • The packages listed in requirements.txt
  1. Install Python 3.12.
  2. Install the Hugging Face hub package and download a copy of the Space.
  3. Move into the new folder and install Gradio 6.31.0 and the packages in requirements.txt.
  4. Start the app with python app.py.
pip install -U huggingface_hub
hf download alrobles/smooth_gen --repo-type space --local-dir smooth_gen
cd smooth_gen
pip install gradio==6.31.0
pip install -r requirements.txt
python app.py

How to use it: Open the page in a browser, load the frames or images you want smoothed, and run it. On a local copy, this command starts the page.

python app.py
Tool | What it does
RIFE | A model the Space names, used to fill the gaps between frames
Adetailer | A second model the Space names, used to refine the images
app.py | Holds the Gradio page
requirements.txt | Lists the Python packages the app needs

Example: You have a stop-motion clip with visible jumps between frames. You load it into the page and run it, and you get back a smoother sequence to compare with the original.

For newcomers and experts: If you are new to this, start with a short clip of only a few frames. Run it once and watch the motion, then judge whether the gaps look softer.

If you know the field, the Space names two models, r3gm/RIFE and Bingsu/adetailer, and runs on a ZeroGPU Space with A10G hardware. The repository has only the app file, the requirements and the README, so the pipeline order and settings are best read from app.py itself.

Load frames or images
RIFE fills the gaps between them
Adetailer refines the images
A smoother sequence comes back

Good to know: The Space page gives one line of description and no usage guide. Read app.py to see what each control does.

  • License: MIT
  • Cost to run: none named
  • Data it reaches: the frames or images you give it, and the two models it names
  • Hardware: ZeroGPU with an A10G at Hugging Face

On Hugging Face, 13 November 2026

  • Likes: 1
  • Built with: gradio
  • License: mit

Links

Try it

Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself.

Files
README.md  4 KB

1 file, 4 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-12

Compare with similar

Listed Hugging Face Spaces in the same category that share the most tags with this one.

ProductLikesBuilt withLicenseLast change
Smooth Gen This page1gradiomit
MusicGenShares gradio5,116gradiocc-by-nc-4.0
Kokoro TTSShares gradio3,556gradioapache-2.0
Background RemovalShares gradio2,988gradiomit
Omni Image EditorShares gradio2,922gradiomit
Diffusers Image OutpaintShares gradio2,565gradioapache-2.0
Numbers as Mindket last read them, on 2026-11-12.

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