Libra R-CNN Detection Model

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Paper: Libra R-CNN: Towards Balanced Learning for Object Detection.
Link: https://arxiv.org/abs/1904.02701
Introduction: It integrates two novel components: balanced feature pyramid, and balanced L1 loss, respectively for reducing the imbalance at feature, and objective level. Benefitted from the overall balanced design, Libra R-CNN significantly improves the detection performance. Without bells and whistles, it achieves 2.5 points and 2.0 points higher Average Precision (AP) than FPN Faster R-CNN and RetinaNet respectively on MSCOCO.

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Models of VOC dataset are evaluated with native resolutions with shorter side >= 600 but longer side <= 1000 without changing aspect ratios.

detection module	map
faster_rcnn_resnet50_v1b_voc	78.3
libra_rcnn_voc	80.9

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ImportError: Unable to import modules due to missing mxnet & torch. You should install at least one deep learning framework.
why get this error wehen workflow_run.

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The code and weight of balance FPN module will re-upload. when i slove the bug as follows.
ImportError: Unable to import modules due to missing mxnet & torch. You should install at least one deep learning framework.
why get this error wehen workflow_run.