Expand description
Implementation of the DINOv2 models from Meta Research.
This module implements the DINOv2 vision transformer model from Meta AI Research. DINOv2 is a self-supervised learning model that can learn visual features without using any labeled data. See: “DINOv2: Learning Robust Visual Features without Supervision”
§Running an example with color map and CUDA
cargo run \
--features cuda,depth_anything_v2 \
--package candle-examples \
--example depth_anything_v2 \
-- --color-map \
--image candle-examples/examples/yolo-v8/assets/bike.jpg§Running as an ImageNet classifier
The model returns the probability for the image to belong to each of the 1000 ImageNet categories.
cargo run \
--example dinov2 \
--release \
-- --image candle-examples/examples/yolo-v8/assets/bike.jpg
> mountain bike, all-terrain bike, off-roader: 43.67%
> bicycle-built-for-two, tandem bicycle, tandem: 33.20%
> crash helmet : 13.23%
> unicycle, monocycle : 2.44%
> maillot : 2.42%