metafile.yml 5.0 KB

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