metadata
license: apache-2.0
base_model: facebook/dinov2-small
tags:
- vision
- onnx
- int8
- mobile
- flutter
- retrieval
- site-recognition
WakeUp DINOv2-Small INT8 (ONNX)
ONNX INT8 export of facebook/dinov2-small for the WakeUp Flutter alarm app's "Travel Mode" → Site Recognition feature.
Why DINOv2?
DINOv2 is self-supervised and explicitly optimized for instance-level retrieval (the same object across viewpoints / lighting). It outperforms CLIP-style models on this task by a wide margin. Used here for the Site Recognition mode where the user captures 3-5 photos of a specific object as anchors.
Files
| File | Size | Purpose |
|---|---|---|
dinov2_small_int8.onnx |
~24 MB | Image feature extraction (CLS token) |
model_metadata.json |
— | Normalization params, embedding dim |
Inference
import onnxruntime as ort
sess = ort.InferenceSession("dinov2_small_int8.onnx")
# image: 1x3x224x224 normalized with DINOv2 ImageNet mean/std
embedding = sess.run(None, {"pixel_values": pixel_values})[0] # shape (1, 384), L2-normalized
Anchors and scan results are compared via plain cosine similarity (dot product, since both are unit-norm).
License
Apache 2.0 (inherits from base model).