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README.md | 1 year ago | |
faster_rcnn_R_50_FPN_noaug_1x.yaml | 1 year ago | |
keypoint_rcnn_R_50_FPN_1x.yaml | 1 year ago | |
mask_rcnn_R_50_FPN_noaug_1x.yaml | 1 year ago |
Detectron2 model zoo's experimental settings and a few implementation details are different from Detectron.
The differences in implementation details are shared in
Compatibility with Other Libraries.
The differences in model zoo's experimental settings include:
POOLER_SAMPLING_RATIO=0
instead of 2. This does not significantly affect AP.ROIAlignV2
. This does not significantly affect AP.In this directory, we provide a few configs that do not have the above changes.
They mimic Detectron's behavior as close as possible,
and provide a fair comparison of accuracy and speed against Detectron.
Name | lr sched |
train time (s/iter) |
inference time (s/im) |
train mem (GB) |
box AP |
mask AP |
kp. AP |
model id | download |
---|---|---|---|---|---|---|---|---|---|
Faster R-CNN | 1x | 0.219 | 0.038 | 3.1 | 36.9 | 137781054 | model | metrics | ||
Keypoint R-CNN | 1x | 0.313 | 0.071 | 5.0 | 53.1 | 64.2 | 137781195 | model | metrics | |
Mask R-CNN | 1x | 0.273 | 0.043 | 3.4 | 37.8 | 34.9 | 137781281 | model | metrics |
For speed comparison, see benchmarks.
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Python Cuda C++ Markdown other
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