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---
title: Image Embedding Explorer (Precalculated Demo)
emoji: πŸ”
colorFrom: green
colorTo: gray
sdk: docker
app_port: 7860
pinned: false
license: mit
short_description: Filter, project, and cluster precalculated image embeddings
tags:
- biodiversity
- embeddings
- bioclip
- clustering
- dimensionality-reduction
- umap
- tsne
- visualization
- imageomics
datasets:
- imageomics/TreeOfLife-200M-Embeddings
models:
- imageomics/bioclip-2
---
# Image Embedding Explorer β€” Precalculated Demo
Hosted demo of the [emb-explorer](https://github.com/Imageomics/emb-explorer)
precalculated embeddings app. Pick a curated BioCLIP 2 dataset (Darwin's
finches or wolves), project it to 2D, color by metadata, and cluster.
## How it works
- The app code (`apps/` + `shared/`) is deployed manually from the
`feature/hf-space-precalculated-demo` branch of
[emb-explorer](https://github.com/Imageomics/emb-explorer). The Dockerfile
builds straight from the pushed files.
- Dependencies are a precalc-only subset (`requirements-space.txt`); the
embedding-generation stack (torch / open-clip) is intentionally excluded.
- The curated demo data lives in the [`imageomics/TreeOfLife-200M-Embeddings`](https://huggingface.co/datasets/imageomics/TreeOfLife-200M-Embeddings)
dataset (under `demo_subset/`), **mounted read-only at `/data`** via a Space
volume. Files are fetched lazily, so the full TreeOfLife-200M embeddings can
be mounted without consuming disk.
## Volume mount (one-time setup, out of band)
```bash
hf spaces volumes set netzhang/emb-explorer-demo \
-v hf://datasets/imageomics/TreeOfLife-200M-Embeddings:/data
```
The app reads `/data/demo_subset/<dataset>/bioclip-2_float16/emb_*.parquet`
(controlled by the `EMB_EXPLORER_DEMO_DATA_ROOT` env var, default `/data`).