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* Add RepVGG model. * Add RepVGG README * Extract var to top level * Replace hashmap with a match * Add a variant for the model kind + avoid some unnecessary config cloning. --------- Co-authored-by: Laurent <laurent.mazare@gmail.com>
candle-repvgg
A candle implementation of inference using a pre-trained repvgg. This uses a classification head trained on the ImageNet dataset and returns the probabilities for the top-5 classes.
Running an example
$ cargo run --example repvgg --release -- --image candle-examples/examples/yolo-v8/assets/bike.jpg
loaded image Tensor[dims 3, 224, 224; f32]
model built
mountain bike, all-terrain bike, off-roader: 61.70%
bicycle-built-for-two, tandem bicycle, tandem: 33.14%
unicycle, monocycle : 4.88%
crash helmet : 0.15%
moped : 0.04%