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Add runtime characteristics to doc (#937)
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docs/source/models.rst

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@@ -319,6 +319,27 @@ keypoints in the following order:
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'right_ankle'
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]
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Runtime characteristics
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-----------------------
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The implementations of the models for object detection, instance segmentation
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and keypoint detection are efficient.
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In the following table, we use 8 V100 GPUs, with CUDA 10.0 and CUDNN 7.4 to
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report the results. During training, we use a batch size of 2 per GPU, and
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during testing a batch size of 1 is used.
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For test time, we report the time for the model evaluation and postprocessing
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(including mask pasting in image), but not the time for computing the
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precision-recall.
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============================== =================== ================== ===========
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Network train time (s / it) test time (s / it) memory (GB)
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============================== =================== ================== ===========
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Faster R-CNN ResNet-50 FPN 0.2288 0.0590 5.2
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Mask R-CNN ResNet-50 FPN 0.2728 0.0903 5.4
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Keypoint R-CNN ResNet-50 FPN 0.3789 0.1242 6.8
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============================== =================== ================== ===========
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Faster R-CNN

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