forked from open-mmlab/mmdetection
-
Notifications
You must be signed in to change notification settings - Fork 0
/
metafile.yml
159 lines (152 loc) · 4.98 KB
/
metafile.yml
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
Collections:
- Name: Mask Scoring R-CNN
Metadata:
Training Data: COCO
Training Techniques:
- SGD with Momentum
- Weight Decay
Training Resources: 8x V100 GPUs
Architecture:
- RPN
- FPN
- ResNet
- RoIAlign
Paper:
URL: https://arxiv.org/abs/1903.00241
Title: 'Mask Scoring R-CNN'
README: configs/ms_rcnn/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/detectors/mask_scoring_rcnn.py#L6
Version: v2.0.0
Models:
- Name: ms-rcnn_r50-caffe_fpn_1x_coco
In Collection: Mask Scoring R-CNN
Config: configs/ms_rcnn/ms-rcnn_r50-caffe_fpn_1x_coco.py
Metadata:
Training Memory (GB): 4.5
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 38.2
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 36.0
Weights: https://download.openmmlab.com/mmdetection/v2.0/ms_rcnn/ms_rcnn_r50_caffe_fpn_1x_coco/ms_rcnn_r50_caffe_fpn_1x_coco_20200702_180848-61c9355e.pth
- Name: ms-rcnn_r50-caffe_fpn_2x_coco
In Collection: Mask Scoring R-CNN
Config: configs/ms_rcnn/ms-rcnn_r50-caffe_fpn_2x_coco.py
Metadata:
Epochs: 24
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 38.8
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 36.3
Weights: https://download.openmmlab.com/mmdetection/v2.0/ms_rcnn/ms_rcnn_r50_caffe_fpn_2x_coco/ms_rcnn_r50_caffe_fpn_2x_coco_bbox_mAP-0.388__segm_mAP-0.363_20200506_004738-ee87b137.pth
- Name: ms-rcnn_r101-caffe_fpn_1x_coco
In Collection: Mask Scoring R-CNN
Config: configs/ms_rcnn/ms-rcnn_r101-caffe_fpn_1x_coco.py
Metadata:
Training Memory (GB): 6.5
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 40.4
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 37.6
Weights: https://download.openmmlab.com/mmdetection/v2.0/ms_rcnn/ms_rcnn_r101_caffe_fpn_1x_coco/ms_rcnn_r101_caffe_fpn_1x_coco_bbox_mAP-0.404__segm_mAP-0.376_20200506_004755-b9b12a37.pth
- Name: ms-rcnn_r101-caffe_fpn_2x_coco
In Collection: Mask Scoring R-CNN
Config: configs/ms_rcnn/ms-rcnn_r101-caffe_fpn_2x_coco.py
Metadata:
Epochs: 24
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.1
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 38.1
Weights: https://download.openmmlab.com/mmdetection/v2.0/ms_rcnn/ms_rcnn_r101_caffe_fpn_2x_coco/ms_rcnn_r101_caffe_fpn_2x_coco_bbox_mAP-0.411__segm_mAP-0.381_20200506_011134-5f3cc74f.pth
- Name: ms-rcnn_x101-32x4d_fpn_1x_coco
In Collection: Mask Scoring R-CNN
Config: configs/ms_rcnn/ms-rcnn_x101-32x4d_fpn_1x_coco.py
Metadata:
Training Memory (GB): 7.9
inference time (ms/im):
- value: 90.91
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.8
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 38.7
Weights: https://download.openmmlab.com/mmdetection/v2.0/ms_rcnn/ms_rcnn_x101_32x4d_fpn_1x_coco/ms_rcnn_x101_32x4d_fpn_1x_coco_20200206-81fd1740.pth
- Name: ms-rcnn_x101-64x4d_fpn_1x_coco
In Collection: Mask Scoring R-CNN
Config: configs/ms_rcnn/ms-rcnn_x101-64x4d_fpn_1x_coco.py
Metadata:
Training Memory (GB): 11.0
inference time (ms/im):
- value: 125
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 43.0
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 39.5
Weights: https://download.openmmlab.com/mmdetection/v2.0/ms_rcnn/ms_rcnn_x101_64x4d_fpn_1x_coco/ms_rcnn_x101_64x4d_fpn_1x_coco_20200206-86ba88d2.pth
- Name: ms-rcnn_x101-64x4d_fpn_2x_coco
In Collection: Mask Scoring R-CNN
Config: configs/ms_rcnn/ms-rcnn_x101-64x4d_fpn_2x_coco.py
Metadata:
Training Memory (GB): 11.0
inference time (ms/im):
- value: 125
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 24
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 42.6
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 39.5
Weights: https://download.openmmlab.com/mmdetection/v2.0/ms_rcnn/ms_rcnn_x101_64x4d_fpn_2x_coco/ms_rcnn_x101_64x4d_fpn_2x_coco_20200308-02a445e2.pth