Pre-built reference databases for the rock classification system — load one and start
classifying immediately, no enrolment or index building required.
Each database contains the same 1,844 labelled rock hand-specimen images spanning
igneous, sedimentary, and metamorphic lithologies, fully indexed with ResNet-50, ResNet-18, ** VGG-16 **,VGG-19, and GoogleNet
visual features (avg_pool, 2048-D), spatial HSV colour histograms, per-specimen
textual descriptions, and text embeddings for dual-stream retrieval.
Which file should I download?
| File | Descriptions written by | Text embeddings | Notes |
|---|---|---|---|
QwenVLNet_OfflineTxtEmbd.mat |
Qwen3-VL 235B | built-in offline embedding | Recommended starting point — works on any machine with zero setup |
LlavaNet_OfflineTxtEmbd.mat |
LLaVA | built-in offline embedding | Zero-setup alternative |
QwenVLNet.mat |
Qwen3-VL 235B | external embedding model | Requires the matching Ollama embedding model |
LlavaNet.mat |
LLaVA | external embedding model | Requires the matching Ollama embedding model |
The *_OfflineTxtEmbd variants use the app's built-in deterministic embedding, so
semantic and Dual-Stream retrieval work out of the box. The other two were built with
an external Ollama embedding model; on loading, the app's embedding-consistency probe
will tell you whether your configured embedding model matches, and you can rebuild the
text embeddings from the Manage tab if it does not.
How to load
- Launch the app (
LocalOllamaRAGChat_RockClassificationin MATLAB). - Open Manage Database → Load Database from File and select the downloaded
.mat. - The View Database tab shows the loaded file, sample counts, and processing status.
Visual-only and Pure-CNN classification work immediately with any of the four files.
All databases were built with the single-backbone ResNet-50 pipeline; to use other
backbones or multi-CNN mode, rebuild the search index after loading (Manage tab).
Compatible with the source code at tag v1.0.0.