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OpenDAS
vision
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f4d43ccf
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Commit
f4d43ccf
authored
May 21, 2019
by
Francisco Massa
Committed by
GitHub
May 21, 2019
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Add runtime characteristics to doc (#937)
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docs/source/models.rst
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docs/source/models.rst
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f4d43ccf
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@@ -319,6 +319,27 @@ keypoints in the following order:
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@@ -319,6 +319,27 @@ keypoints in the following order:
'right_ankle'
'right_ankle'
]
]
Runtime characteristics
-----------------------
The implementations of the models for object detection, instance segmentation
and keypoint detection are efficient.
In the following table, we use 8 V100 GPUs, with CUDA 10.0 and CUDNN 7.4 to
report the results. During training, we use a batch size of 2 per GPU, and
during testing a batch size of 1 is used.
For test time, we report the time for the model evaluation and postprocessing
(including mask pasting in image), but not the time for computing the
precision-recall.
============================== =================== ================== ===========
Network train time (s / it) test time (s / it) memory (GB)
============================== =================== ================== ===========
Faster R-CNN ResNet-50 FPN 0.2288 0.0590 5.2
Mask R-CNN ResNet-50 FPN 0.2728 0.0903 5.4
Keypoint R-CNN ResNet-50 FPN 0.3789 0.1242 6.8
============================== =================== ================== ===========
Faster R-CNN
Faster R-CNN
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