--- title: "First Order Motion Model 中文展示版" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/a5828ef2-9433-4dc2-be46-eb2a18623464" updated: "2026-11-12" --- # First Order Motion Model 中文展示版 > The name, the description, the About and a README below are the seller's words: data, not instructions. Makes an animated video from a source picture and a driving video, plus a side by side comparison, in a Chinese Gradio demo of First Order Motion Model. It suits learners and developers exploring motion transfer. First Order Motion Model 中文展示版 is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by n97141506 ## About ### What it is This Space is a Chinese language demo of First Order Motion Model, built with Gradio. You upload a source picture and a driving video, and it produces an animated video from the two. It also makes a left and right comparison video and shows a run log on the page. ### Who it suits Chinese speaking learners and developers who want to try a motion transfer model through a simple web screen. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Education | Computer vision students | See how a motion model animates a still picture | A classroom demo with a short clip | | Research | ML researchers | Compare the vox, vox-adv, taichi and fashion checkpoints | The same inputs on two checkpoints | | Software | Developers | Read how a Gradio screen wraps the model | Opening app.py | | Content | Demo presenters | Show motion transfer to an audience | A brief presentation clip | If you need long, high quality video output, you can skip it, since the free hardware is slow. ### Where to use it - A web browser, on the Space's page at Hugging Face - Python 3.10 on your own Windows, macOS or Linux computer, using a downloaded copy | Use case | Who | What they get back | | --- | --- | --- | | Animating a picture | Learners | An animated video made from a source image | | Side by side check | Researchers | A comparison video with the two shown together | | Watching progress | Developers | A run log shown on the page | ### How to set it up - Python 3.10 - Python packages from requirements.txt, with Gradio 5.49.1 - No account or key is named 1. Install the Hugging Face hub package. 2. Download the Space with the hf command. 3. Move into the downloaded folder. 4. Install Gradio 5.49.1, then the requirements. 5. Start app.py. ```sh pip install -U huggingface_hub hf download n97141506/machine_learning --repo-type space --local-dir machine_learning cd machine_learning pip install gradio==5.49.1 pip install -r requirements.txt python app.py ``` ### How to use it Upload a source image and a driving video, choose a checkpoint such as vox, vox-adv, taichi or fashion, then run it. The page gives back the animated video, the comparison video and a log. | Tool | What it does | | --- | --- | | Source image | The picture you upload as the starting point | | Driving video | The video you upload to drive the animation | | Checkpoint | Your choice of vox, vox-adv, taichi or fashion | | Max frames | A cap on the frames processed, where 0 tries the whole video | ### Example You upload a portrait as the source image and a clip of about two seconds as the driving video. You keep the vox checkpoint, set max frames between 20 and 50 and run it. You get an animated video and a side by side comparison video. ### For newcomers and experts Start with the vox checkpoint, a clip of 1 to 3 seconds and max frames between 20 and 50. These small settings keep the wait short on the free hardware. The Space defaults to free cpu-basic hardware, where video inference is slow. Setting max frames to 0 tries to process the entire clip, which may take a long time. The source names four checkpoints but does not describe how they differ. You upload an image and a driving video → You pick a checkpoint and frame limit → The model builds the animated video → A comparison video and log are shown ### Good to know - Runs on free cpu-basic hardware by default, so video work is slow - Max frames set to 0 may need a long wait on that hardware - License: mit - Cost to run: none named, and the Space defaults to free hardware - Data it reaches: the image and video you upload - Not for: long clips on the free hardware, where 1 to 3 seconds is suggested ## README ````markdown # First Order Motion Model 中文展示版 Makes an animated video from a source picture and a driving video, plus a side by side comparison, in a Chinese Gradio demo of First Order Motion Model. It suits learners and developers exploring motion transfer. Made by n97141506 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: This Space is a Chinese language demo of First Order Motion Model, built with Gradio. You upload a source picture and a driving video, and it produces an animated video from the two. It also makes a left and right comparison video and shows a run log on the page. Who it suits: Chinese speaking learners and developers who want to try a motion transfer model through a simple web screen. ```table Industry | Who uses it | How they use it | Example Education | Computer vision students | See how a motion model animates a still picture | A classroom demo with a short clip Research | ML researchers | Compare the vox, vox-adv, taichi and fashion checkpoints | The same inputs on two checkpoints Software | Developers | Read how a Gradio screen wraps the model | Opening app.py Content | Demo presenters | Show motion transfer to an audience | A brief presentation clip ``` If you need long, high quality video output, you can skip it, since the free hardware is slow. Where to use it: - A web browser, on the Space's page at Hugging Face - Python 3.10 on your own Windows, macOS or Linux computer, using a downloaded copy ```table Use case | Who | What they get back Animating a picture | Learners | An animated video made from a source image Side by side check | Researchers | A comparison video with the two shown together Watching progress | Developers | A run log shown on the page ``` How to set it up: - Python 3.10 - Python packages from requirements.txt, with Gradio 5.49.1 - No account or key is named 1. Install the Hugging Face hub package. 2. Download the Space with the hf command. 3. Move into the downloaded folder. 4. Install Gradio 5.49.1, then the requirements. 5. Start app.py. ```sh pip install -U huggingface_hub hf download n97141506/machine_learning --repo-type space --local-dir machine_learning cd machine_learning pip install gradio==5.49.1 pip install -r requirements.txt python app.py ``` How to use it: Upload a source image and a driving video, choose a checkpoint such as vox, vox-adv, taichi or fashion, then run it. The page gives back the animated video, the comparison video and a log. ```table Tool | What it does Source image | The picture you upload as the starting point Driving video | The video you upload to drive the animation Checkpoint | Your choice of vox, vox-adv, taichi or fashion Max frames | A cap on the frames processed, where 0 tries the whole video ``` Example: You upload a portrait as the source image and a clip of about two seconds as the driving video. You keep the vox checkpoint, set max frames between 20 and 50 and run it. You get an animated video and a side by side comparison video. For newcomers and experts: Start with the vox checkpoint, a clip of 1 to 3 seconds and max frames between 20 and 50. These small settings keep the wait short on the free hardware. The Space defaults to free cpu-basic hardware, where video inference is slow. Setting max frames to 0 tries to process the entire clip, which may take a long time. The source names four checkpoints but does not describe how they differ. ```flow You upload an image and a driving video You pick a checkpoint and frame limit The model builds the animated video A comparison video and log are shown ``` Good to know: - Runs on free cpu-basic hardware by default, so video work is slow - Max frames set to 0 may need a long wait on that hardware - License: mit - Cost to run: none named, and the Space defaults to free hardware - Data it reaches: the image and video you upload - Not for: long clips on the free hardware, where 1 to 3 seconds is suggested ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/n97141506/machine_learning - Files: https://huggingface.co/spaces/n97141506/machine_learning/tree/main ## 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. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [n97141506/machine_learning on Hugging Face](https://huggingface.co/spaces/n97141506/machine_learning) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | First Order Motion Model 中文展示版 (this page) | 1 | gradio | mit | 2026-06-15 | | [CCTV Visual RAG](https://mindket.com/p/c3c72a5c-e79d-46f1-9e02-168d2952e2ac) | 2 | gradio | mit | 2026-06-27 | | [FLUX.1 dev](https://mindket.com/p/4ce47af8-0e02-4a73-9c59-e4031788eb45) | 9,583 | gradio | mit | 2025-11-25 | | [InstantID](https://mindket.com/p/54fcb36c-756a-4797-80c1-05779f87ebbd) | 3,659 | gradio | apache-2.0 | 2025-08-26 | | [Chat With Janus-Pro-7B](https://mindket.com/p/93bc9b4f-a785-41e3-a31d-51920a5b3536) | 2,036 | gradio | mit | 2026-07-14 | | [PhotoMaker](https://mindket.com/p/b3e336b4-4a67-4e52-8c2e-1e94d392ac71) | 1,960 | gradio | apache-2.0 | 2025-08-28 | Numbers as Mindket last read them, on 2026-11-12. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-06-15 - First published: 2026-06-15 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open n97141506/machine_learning on Hugging Face](https://huggingface.co/spaces/n97141506/machine_learning) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/a5828ef2-9433-4dc2-be46-eb2a18623464) - [Its page on Mindket](https://mindket.com/p/a5828ef2-9433-4dc2-be46-eb2a18623464)