Sentrix-Code/wakeup-dinov2-small-int8

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).