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reformat yolact readme benchmarking section (#211)
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examples/dbolya-yolact/README.md

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@@ -113,17 +113,21 @@ python eval.py --trained_model weights/model.onnx --score 0.6 --benchmark
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# using a valid YOLACT SparseZoo stubs
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# python eval.py --trained_model SPARSEZOO_STUB \
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# --benchmark
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python eval.py --trained_model \
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zoo:cv/segmentation/yolact-darknet53/pytorch/dbolya/coco/base-none \
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--score 0.6 --benchmark
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python eval.py \
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--trained_model zoo:cv/segmentation/yolact-darknet53/pytorch/dbolya/coco/base-none \
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--score 0.6 \
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--batch_size 1 \
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--benchmark
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# Using DeepSparse on the COCO validation set for fixed num of iterations
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# python eval.py --trained_model PRETRAINED_ONNX_WEIGHTS \
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# --score SCORE_THRESHOLD --warm_up_iterations WARM_UP_ITERATIONS \
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# --num_iterations NUM_ITERATIONS \
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# --benchmark
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python eval.py --trained_model weights/model.onnx \
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--score 0.6 --warm_up_iterations 10 \
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python eval.py \
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--trained_model weights/model.onnx \
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--score 0.6 \
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--warm_up_iterations 10 \
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--num_iterations 100 \
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--benchmark
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```

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