README.md

metadata

title: HyperView RESISC45 Geospatial
emoji: 🛰️
colorFrom: green
colorTo: blue
sdk: docker
app_port: 7860
pinned: false
models:
  - hyper3labs/hyper3-clip-v0.5
  - openai/clip-vit-base-patch32
datasets:
  - tanganke/resisc45
tags:
  - hyperview
  - geospatial
  - image-retrieval
  - remote-sensing

HyperView - RESISC45 Geospatial Retrieval Comparison

This demo builds a balanced NWPU-RESISC45 remote-sensing subset and opens HyperView with two pinned scatter panels plus a compact scene-retrieval readout:

• CLIP ViT-B/32 in a Euclidean 2D layout
• Hyper3-CLIP hyper3-clip-v0.5 from hyper-models in a Poincare 2D layout

The readout panel ranks live query examples by where Hyper3-CLIP improves the top-10 neighborhood over CLIP. The demo is designed around remote-sensing review workflows: semantic search over aerial/satellite tiles, scene-neighborhood inspection, and label-QA for coarse operational groups such as transport, built environment, agriculture/vegetation, water/coastal, sports/recreation, and natural terrain.

Industry Story

Use this as the non-retail proof point for Hyper3-CLIP. The buyer-facing story is not generic satellite classification; it is retrieval QA for large imagery archives:

• Search for one scene tile and inspect whether its nearest neighbors stay in the same exact scene class and broader operational group.
• Compare CLIP and Hyper3-CLIP on the same query to surface scene drift, mixed neighborhoods, and coarse-label leakage.
• Map the workflow to geospatial search, agriculture monitoring, insurance and risk review, infrastructure analytics, and remote-sensing dataset QA.

The demo should be positioned as a hierarchy-sensitive retrieval probe for remote-sensing imagery, not as a replacement for specialist remote-sensing classifiers.

The runtime sample is drawn from tanganke/resisc45, using the test split by default and selecting a balanced curated subset of RESISC45 classes that support the landing-page comparison queries. Override GEOSPATIAL_DEMO_LABELS to change the comma-separated class list.

Run locally from the HyperView repo:

uv run python hyperview-spaces/spaces/geospatial-eurosat-clip-hyper3clip/demo.py

Useful overrides:

HYPERVIEW_PORT=6264 GEOSPATIAL_SAMPLES_PER_CLASS=5 \
  uv run python hyperview-spaces/spaces/geospatial-eurosat-clip-hyper3clip/demo.py

Benchmark Context

Internal lightweight retrieval runs currently show Hyper3-CLIP above OpenAI CLIP-B/32 on NWPU-RESISC45 same-class retrieval and coarse parent grouping. Keep the public claim narrow: this is a positive geospatial retrieval probe against OpenAI CLIP-B/32, not a claim that Hyper3-CLIP beats every remote-sensing model.

Deploy Source

This folder deploys to mnm-matin/HyperView-EuroSAT-Geospatial as the live Space. The hyper3labs/HyperView-EuroSAT-Geospatial Space is kept as a commit-synced org mirror, but remains paused.

Hyper3-CLIP weights are loaded through the hyper-models catalog entry for the gated hyper3labs/hyper3-clip-v0.5 model repository at runtime. The Space needs an HF_TOKEN secret with access to that model.