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| -rw-r--r-- | candle-examples/examples/onnx/README.md | 37 |
1 files changed, 33 insertions, 4 deletions
diff --git a/candle-examples/examples/onnx/README.md b/candle-examples/examples/onnx/README.md index fd705fb6..d6ca4d37 100644 --- a/candle-examples/examples/onnx/README.md +++ b/candle-examples/examples/onnx/README.md @@ -1,10 +1,39 @@ ## Using ONNX models in Candle -This example demonstrates how to run ONNX based models in Candle, the model -being used here is a small sequeezenet variant. +This example demonstrates how to run [ONNX](https://github.com/onnx/onnx) based models in Candle. -You can run the example with the following command: +It contains small variants of two models, [SqueezeNet](https://arxiv.org/pdf/1602.07360.pdf) (default) and [EfficientNet](https://arxiv.org/pdf/1905.11946.pdf). + +You can run the examples with following commands: + +```bash +cargo run --example onnx --features=onnx --release -- --image candle-examples/examples/yolo-v8/assets/bike.jpg +``` + +Use the `--which` flag to specify explicitly which network to use, i.e. ```bash -cargo run --example squeezenet-onnx --release -- --image candle-examples/examples/yolo-v8/assets/bike.jpg +$ cargo run --example onnx --features=onnx --release -- --which squeeze-net --image candle-examples/examples/yolo-v8/assets/bike.jpg + + Finished release [optimized] target(s) in 0.21s + Running `target/release/examples/onnx --which squeeze-net --image candle-examples/examples/yolo-v8/assets/bike.jpg` +loaded image Tensor[dims 3, 224, 224; f32] +unicycle, monocycle : 83.23% +ballplayer, baseball player : 3.68% +bearskin, busby, shako : 1.54% +military uniform : 0.78% +cowboy hat, ten-gallon hat : 0.76% +``` + +```bash +$ cargo run --example onnx --features=onnx --release -- --which efficient-net --image candle-examples/examples/yolo-v8/assets/bike.jpg + + Finished release [optimized] target(s) in 0.20s + Running `target/release/examples/onnx --which efficient-net --image candle-examples/examples/yolo-v8/assets/bike.jpg` +loaded image Tensor[dims 224, 224, 3; f32] +bicycle-built-for-two, tandem bicycle, tandem : 99.16% +mountain bike, all-terrain bike, off-roader : 0.60% +unicycle, monocycle : 0.17% +crash helmet : 0.02% +alp : 0.02% ``` |