--- title: "CoWTracker" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/2198a161-2a3f-43b6-90e0-2d644ac9b320" updated: "2026-11-12" --- # CoWTracker > The name, the description, the About and a README below are the seller's words: data, not instructions. Tracks every pixel of an uploaded video through time and draws the motion as colorful trajectories. Suits researchers and anyone studying how things move in footage. CoWTracker is a kit in the Research 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 facebook ## About ### What it is CoWTracker is a research demo that follows every pixel of a video from frame to frame. You upload a clip, pick a starting frame, and it draws the motion as colorful paths. The method is dense point tracking based on warping, and it skips the cost volume that many trackers build. It comes from researchers at Oxford's Visual Geometry Group and Meta AI. ### Who it suits It suits computer vision researchers and students, and anyone who wants to see how motion in a clip can be measured down to single pixels. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Computer vision | Researchers | Try dense point tracking on their own clips | Track a short clip and inspect the trajectories | | Video and film | Editors and visual effects artists | See motion paths for every part of a shot | Follow a moving object through a handheld clip | | Sports analysis | Analysts | Look at how bodies and objects move between frames | Track a short training clip forwards and backwards | | Education | Students | Learn what motion tracking produces | Compare paths from different starting frames | Skip it if you need a commercial tool, since the license listed here limits use to non-commercial work. ### Where to use it - A browser: open the Space's page on Hugging Face, with nothing to install - A copy on Windows, macOS or Linux, using Python - A Hugging Face Space with GPU hardware, which the online copy uses | Use case | Who | What they get back | | --- | --- | --- | | Tracking a clip | Researchers | Colorful trajectories drawn over the video | | Two-way tracking | Analysts | Paths that run forwards and backwards from a chosen frame | | Trying settings | Students | Different looks of the same motion data | ### How to set it up The online copy needs nothing. For a copy on your own computer, you need the following. - Python with pip on Windows, macOS or Linux - The Hugging Face hub client, which the first step installs - The packages listed in requirements.txt - The system packages in packages.txt, which Hugging Face installs with apt-get 1. Install the Hugging Face hub client. 2. Download the Space's files into a local folder. 3. Move into that folder. 4. Install the Gradio version the Space pins. 5. Install the remaining packages from requirements.txt. 6. Start app.py. ```sh pip install -U huggingface_hub hf download facebook/cowtracker --repo-type space --local-dir cowtracker cd cowtracker pip install gradio==6.2.0 pip install -r requirements.txt python app.py ``` ### How to use it Add your own video, or choose one of the examples, and press "Process Video". Then move the slider to the frame you want to track from and press "Start Tracking". Last, change the visualization settings to taste. | Tool | What it does | | --- | --- | | Process Video | Readies the uploaded clip before you pick a frame | | Query frame slider | Chooses the frame the tracking starts from | | Start Tracking | Follows every pixel forwards and backwards from that frame | | Visualization settings | Change how the trajectories look | ### Example You upload a short clip of a person walking and press "Process Video". You drag the slider to the first frame and press "Start Tracking". The Space returns the clip with colorful trajectories showing where each pixel moves. ### For newcomers and experts If you are new, start with one of the built-in example clips so you can see a result at once. Then upload a short clip of your own, since long videos take more time on shared hardware. If you know the field, the model is a warping-based dense tracker that avoids a cost volume, and the page credits that design for its speed. You can choose any query frame and track in both time directions. The Space runs on zero-a10g hardware. You upload a video → The clip is processed → You pick a query frame → Tracking runs in both directions → You see colorful trajectories ### Good to know The license limits who can use it, so read it before you plan any work around it. - License: cc-by-nc-4, a Creative Commons license for non-commercial use - Cost to run: no API key or paid service is named, and the online copy runs on zero-a10g hardware at Hugging Face - Data it reaches: the videos you upload, which the online Space handles on Hugging Face's servers, and a local copy downloads the Space's files - Not for: commercial use under this license, and the source lists no other exclusions ## README ````markdown # CoWTracker Tracks every pixel of an uploaded video through time and draws the motion as colorful trajectories. Suits researchers and anyone studying how things move in footage. Made by facebook 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: CoWTracker is a research demo that follows every pixel of a video from frame to frame. You upload a clip, pick a starting frame, and it draws the motion as colorful paths. The method is dense point tracking based on warping, and it skips the cost volume that many trackers build. It comes from researchers at Oxford's Visual Geometry Group and Meta AI. Who it suits: It suits computer vision researchers and students, and anyone who wants to see how motion in a clip can be measured down to single pixels. ```table Industry | Who uses it | How they use it | Example Computer vision | Researchers | Try dense point tracking on their own clips | Track a short clip and inspect the trajectories Video and film | Editors and visual effects artists | See motion paths for every part of a shot | Follow a moving object through a handheld clip Sports analysis | Analysts | Look at how bodies and objects move between frames | Track a short training clip forwards and backwards Education | Students | Learn what motion tracking produces | Compare paths from different starting frames ``` Skip it if you need a commercial tool, since the license listed here limits use to non-commercial work. Where to use it: - A browser: open the Space's page on Hugging Face, with nothing to install - A copy on Windows, macOS or Linux, using Python - A Hugging Face Space with GPU hardware, which the online copy uses ```table Use case | Who | What they get back Tracking a clip | Researchers | Colorful trajectories drawn over the video Two-way tracking | Analysts | Paths that run forwards and backwards from a chosen frame Trying settings | Students | Different looks of the same motion data ``` How to set it up: The online copy needs nothing. For a copy on your own computer, you need the following. - Python with pip on Windows, macOS or Linux - The Hugging Face hub client, which the first step installs - The packages listed in requirements.txt - The system packages in packages.txt, which Hugging Face installs with apt-get 1. Install the Hugging Face hub client. 2. Download the Space's files into a local folder. 3. Move into that folder. 4. Install the Gradio version the Space pins. 5. Install the remaining packages from requirements.txt. 6. Start app.py. ```sh pip install -U huggingface_hub hf download facebook/cowtracker --repo-type space --local-dir cowtracker cd cowtracker pip install gradio==6.2.0 pip install -r requirements.txt python app.py ``` How to use it: Add your own video, or choose one of the examples, and press "Process Video". Then move the slider to the frame you want to track from and press "Start Tracking". Last, change the visualization settings to taste. ```table Tool | What it does Process Video | Readies the uploaded clip before you pick a frame Query frame slider | Chooses the frame the tracking starts from Start Tracking | Follows every pixel forwards and backwards from that frame Visualization settings | Change how the trajectories look ``` Example: You upload a short clip of a person walking and press "Process Video". You drag the slider to the first frame and press "Start Tracking". The Space returns the clip with colorful trajectories showing where each pixel moves. For newcomers and experts: If you are new, start with one of the built-in example clips so you can see a result at once. Then upload a short clip of your own, since long videos take more time on shared hardware. If you know the field, the model is a warping-based dense tracker that avoids a cost volume, and the page credits that design for its speed. You can choose any query frame and track in both time directions. The Space runs on zero-a10g hardware. ```flow You upload a video The clip is processed You pick a query frame Tracking runs in both directions You see colorful trajectories ``` Good to know: The license limits who can use it, so read it before you plan any work around it. - License: cc-by-nc-4, a Creative Commons license for non-commercial use - Cost to run: no API key or paid service is named, and the online copy runs on zero-a10g hardware at Hugging Face - Data it reaches: the videos you upload, which the online Space handles on Hugging Face's servers, and a local copy downloads the Space's files - Not for: commercial use under this license, and the source lists no other exclusions ## On Hugging Face, 13 November 2026 - Likes: 4 - Built with: gradio - License: cc-by-nc-4.0 ## Links - Space: https://huggingface.co/spaces/facebook/cowtracker - Files: https://huggingface.co/spaces/facebook/cowtracker/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, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [facebook/cowtracker on Hugging Face](https://huggingface.co/spaces/facebook/cowtracker) ## 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 | | --- | --- | --- | --- | --- | | CoWTracker (this page) | 4 | gradio | cc-by-nc-4.0 | 2026-02-05 | | [Open VLM Leaderboard](https://mindket.com/p/9382a913-7563-4967-88b1-0f2458cb00bc) | 1,034 | gradio | apache-2.0 | 2026-03-11 | | [Face Swap](https://mindket.com/p/92787455-1f9f-466a-b574-da22b25d6e0a) | 808 | gradio | cc-by-nc-sa-4.0 | 2024-05-22 | | [TTS Spaces Arena](https://mindket.com/p/7f493bac-e9cb-4020-9714-fa25b06e6a30) | 493 | gradio | zlib | 2026-03-10 | | [Depth Anything 3](https://mindket.com/p/c1e531c5-63e1-4315-a529-7fcae3cb7374) | 490 | gradio | cc-by-nc-4.0 | 2025-11-20 | | [BLIP](https://mindket.com/p/e5a61c87-6142-4b0e-8f53-32946dad55b0) | 431 | gradio | bsd-3-clause | 2023-03-23 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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: 2026-02-05 - First published: 2025-12-21 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open facebook/cowtracker on Hugging Face](https://huggingface.co/spaces/facebook/cowtracker) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/2198a161-2a3f-43b6-90e0-2d644ac9b320) - [Its page on Mindket](https://mindket.com/p/2198a161-2a3f-43b6-90e0-2d644ac9b320)