This model is an instance segmentation network for 80 classes of objects. It is a Cascade mask R-CNN with ResNet101 backbone and deformable convolutions, FPN, RPN, detection and segmentation heads.
|COCO val2017 box AP (max short side 800, max long side 1344)||45.8%|
|COCO val2017 mask AP (max short side 800, max long side 1344)||39.7%|
|COCO val2017 box AP (max height 800, max width 1344)||43.55%|
|COCO val2017 mask AP (max height 800, max width 1344)||38.14%|
|Max objects to detect||100|
Average Precision (AP) is defined and measured according to standard COCO evaluation procedure.
1, 3, 800, 1344 in the format
1, C, H, W, where:
C- number of channels
H- image height
W- image width
The expected channel order is
100- Contiguous integer class ID for every detected object.
100, 5- Bounding boxes around every detected objects in (top_left_x, top_left_y, bottom_right_x, bottom_right_y) format and its confidence score in range [0, 1].
100, 28, 28]- Segmentation heatmaps for every output bounding box.
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