feat: add link of the onnx sp model in aidge
#1
by loulou2 - opened
README.md
CHANGED
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@@ -163,6 +163,7 @@ To export the desired PyTorch model to ONNX:
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superpoint-pruning export --backbone_0_1 32
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```
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The model pruning configuration can once again be controlled with same flags as shown in the evaluation example.
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## Run TRT inference benchmark
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In case the device supports TensorRT (with the necessary packages installed) and there is a serialized TRT model (here a dummy example of `superpoint.engine`), then the local python benchmark with a TRT wrapper can be run as:
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superpoint-pruning export --backbone_0_1 32
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```
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The model pruning configuration can once again be controlled with same flags as shown in the evaluation example.
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+
As an example, we have published the ONNX export of the `original` model to https://huggingface.co/EclipseAidge/SuperPoint.
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## Run TRT inference benchmark
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In case the device supports TensorRT (with the necessary packages installed) and there is a serialized TRT model (here a dummy example of `superpoint.engine`), then the local python benchmark with a TRT wrapper can be run as:
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