diff --git a/mmdet/models/detectors/mask_rcnn.py b/mmdet/models/detectors/mask_rcnn.py index 684598aa013300c66a07f2282a73c3dcb364af13..25a363e398f6c0d01e2f8bd53e05c9046a5275ac 100644 --- a/mmdet/models/detectors/mask_rcnn.py +++ b/mmdet/models/detectors/mask_rcnn.py @@ -15,13 +15,20 @@ class MaskRCNN(TwoStageDetector): test_cfg, pretrained=None): super(MaskRCNN, self).__init__( - backbone=backbone, - neck=neck, - rpn_head=rpn_head, - bbox_roi_extractor=bbox_roi_extractor, - bbox_head=bbox_head, - mask_roi_extractor=mask_roi_extractor, - mask_head=mask_head, - train_cfg=train_cfg, - test_cfg=test_cfg, - pretrained=pretrained) + backbone=backbone, + neck=neck, + rpn_head=rpn_head, + bbox_roi_extractor=bbox_roi_extractor, + bbox_head=bbox_head, + mask_roi_extractor=mask_roi_extractor, + mask_head=mask_head, + train_cfg=train_cfg, + test_cfg=test_cfg, + pretrained=pretrained) + + def show_result(self, data, result, img_norm_cfg, **kwargs): + # TODO: show segmentation masks + assert isinstance(result, tuple) + assert len(result) == 2 # (bbox_results, segm_results) + super(MaskRCNN, self).show_result(data, result[0], img_norm_cfg, + **kwargs) diff --git a/tools/configs/r50_fpn_frcnn_1x.py b/tools/configs/r50_fpn_frcnn_1x.py index 82082df0087a7d0690bee0a79528de317f4737f5..6ab3dbc36173d19ff74e9b0cfcdab2d8d045f342 100644 --- a/tools/configs/r50_fpn_frcnn_1x.py +++ b/tools/configs/r50_fpn_frcnn_1x.py @@ -76,7 +76,7 @@ test_cfg = dict( max_num=2000, nms_thr=0.7, min_bbox_size=0), - rcnn=dict(score_thr=1e-3, max_per_img=100, nms_thr=0.5)) + rcnn=dict(score_thr=0.05, max_per_img=100, nms_thr=0.5)) # dataset settings dataset_type = 'CocoDataset' data_root = '../data/coco/' diff --git a/tools/configs/r50_fpn_maskrcnn_1x.py b/tools/configs/r50_fpn_maskrcnn_1x.py index ad618573299324d1eec584203fbc3cedd043d2f8..677176c56b642bda0dff3486185687e027a336c9 100644 --- a/tools/configs/r50_fpn_maskrcnn_1x.py +++ b/tools/configs/r50_fpn_maskrcnn_1x.py @@ -89,7 +89,7 @@ test_cfg = dict( nms_thr=0.7, min_bbox_size=0), rcnn=dict( - score_thr=1e-3, max_per_img=100, nms_thr=0.5, mask_thr_binary=0.5)) + score_thr=0.05, max_per_img=100, nms_thr=0.5, mask_thr_binary=0.5)) # dataset settings dataset_type = 'CocoDataset' data_root = '../data/coco/'