README.md

metadata

title: HyperView-Jaguar-ReID
emoji: 🐆
colorFrom: yellow
colorTo: green
sdk: docker
app_port: 7860
pinned: false

HyperView - Jaguar Re-ID (MegaDescriptor + Sphere)

This Space runs the Jaguar Re-ID dataset through the MegaDescriptor timm backbone and renders the result with HyperView's spherical 3D layout.

This example now installs the released hyperview[ml]==0.3.1 package from PyPI, which includes the timm-image provider and spherical 3D layout support required by this demo.

This demo uses:

• Hugging Face dataset hyper3labs/jaguar-re-id
• Config default
• Split train
• Image field image
• Label field label
• Sample count 200
• Embedding model hf-hub:BVRA/MegaDescriptor-L-384
• Layout spherical (3D)

Build model

The Dockerfile precomputes the dataset, embeddings, and layout during image build so the runtime container only needs to launch HyperView.

Because MegaDescriptor inference runs during Docker build on CPU, this Space keeps the sample count modest and uses a smaller batch size than the local demo script to stay within typical Hugging Face build limits.

Reuse this example

If you need a simple starter, copy spaces/imagenette-clip-hycoclip first. If your own Space needs a timm backbone or a spherical 3D layout, copy this folder instead and change the constants block at the top of demo.py.

When contributing your own Space back to this repository, add a row to the community table in the root README.md and include your Hugging Face Space ID in the pull request description.

Deploy source

This folder is synchronized to Hugging Face Spaces by GitHub Actions from the hyperview-spaces deployment repository.