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What you can do with Brandpose

BrandPose is a personal project that estimates where shoppers look in a store, using an ordinary fixed security camera and open source AI models (YOLO11, Gaze-LLE, Depth Anything V2).

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escudero/brandpose on GitHub

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What do you want to do?

3 use cases

  • Measure shelf attention from a fixed store camera video

    Run the gaze pipeline on a fixed-camera clip to rank which shelf zones draw attention.

    View prompt
    Using the repo escudero/brandpose, run scripts/gaze_sim_v2.py on the fixed-camera video at <video path> with --max-seconds 60, using the flags in the README. Report the number of estimated gazes, shoppers and zones with attention, and the output folder. Verify that outputs/v2 contains results and that the attention figures are labeled as model estimates, not ground truth.

  • Render the full promo video with zones, depth and soundtrack

    Rebuild the demo pipeline: extraction, zones, depth, render and synthesized audio.

    View prompt
    Using the repo escudero/brandpose, follow docs/experiments/2026-10-14-promo-v2.md to run the promo pipeline in scripts/promo/ on the ACTi demo video. Report the output video path and the stage that failed, if any. Verify that the zone ranking in the rendered report matches the zones in config/zones_acti.json.

  • Rebuild the store in Blender and render a shopper's view

    Calibrate the camera to marked corners, model the fixtures in Blender and render one shopper's view.

    View prompt
    Using the repo escudero/brandpose, follow docs/experiments/2026-10-18-blender-pov.md to calibrate the camera with scripts/blender/calib.py, then render the shopper's view with scripts/blender/pov.py for <person ID>. Report the output video path and the calibration result. Verify with scripts/blender/overlay.py that the fixtures match the image before accepting the render.

How to use Brandpose

  1. Check you have what it needs: Python 3.13; FFmpeg installed and on the system; About 10 GB of free disk space.
  2. Open escudero/brandpose on GitHub and read the README and license.
  3. Clone the repo, then run python3 -m venv .venv && .venv/bin/pip install -r requirements.txt inside it.
  4. Download the demo video with .venv/bin/yt-dlp -f "bv*[height<=1080][ext=mp4]+ba[ext=m4a]" -o "data/videos/youtube/yt_%(id)s.%(ext)s" "https://www.youtube.com/watch?v=-1bRhYjw1qE", or place your own fixed-camera video in data/videos/. (inferred, check the README)
  5. Run cd scripts and then ../.venv/bin/python gaze_sim_v2.py ../data/videos/youtube/yt_-1bRhYjw1qE.mp4 ../outputs/v2 --crop --model gazelle_dinov2_vitl14_inout --smooth 0.5 --suppress-self --track-every-frame --max-seconds 60. (inferred, check the README)
  6. Open the results in outputs/v2 and compare the zone ranking with your own rough count of a few minutes of footage.

These steps come from our top use case, Measure shelf attention from a fixed store camera video, which also has a copy-paste agent prompt.

Brandpose alternatives · Best AI repos for Data and analytics

About this repo

  • Who it is forWritten for analysts, developers and AI agents who want to measure shelf attention from fixed-camera footage, and who accept that the results are unverified model estimates.
  • Why it is hot
  • LanguagePython
  • Sourcegithub.com/escudero/brandpose · Back to Hot repos

Requirements

  • Python 3.13
  • FFmpeg installed and on the system
  • About 10 GB of free disk space
  • A machine able to run the models; the README reports tests on a Mac M2 Pro with 16 GB using MPS acceleration
  • Blender 5.2 only if you want the 3D store and shopper's view
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Questions about Brandpose

What is Brandpose?

BrandPose is a personal project that estimates where shoppers look in a store, using an ordinary fixed security camera and open source AI models (YOLO11, Gaze-LLE, Depth Anything V2). It is an open-source project on GitHub: https://github.com/escudero/brandpose.

Who is Brandpose for?

Written for analysts, developers and AI agents who want to measure shelf attention from fixed-camera footage, and who accept that the results are unverified model estimates.

What can I do with Brandpose?

3 use cases so far, for example: Measure shelf attention from a fixed store camera video; Render the full promo video with zones, depth and soundtrack; Rebuild the store in Blender and render a shopper's view. Each has steps and a copy-paste agent prompt.

What do I need to run Brandpose?

Python 3.13; FFmpeg installed and on the system; About 10 GB of free disk space; A machine able to run the models; the README reports tests on a Mac M2 Pro with 16 GB using MPS acceleration.

What are alternatives to Brandpose?

Other hot AI repos in Data and analytics: Kronos, DBT Charts, Idx, Open Lakehouse Compute Fabric, Zepp Bridge.

Is Brandpose safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.