metafile.yml 3.3 KB

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  1. Collections:
  2. - Name: InstaBoost
  3. Metadata:
  4. Training Data: COCO
  5. Training Techniques:
  6. - InstaBoost
  7. - SGD with Momentum
  8. - Weight Decay
  9. Training Resources: 8x V100 GPUs
  10. Paper:
  11. URL: https://arxiv.org/abs/1908.07801
  12. Title: 'Instaboost: Boosting instance segmentation via probability map guided copy-pasting'
  13. README: configs/instaboost/README.md
  14. Code:
  15. URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/datasets/pipelines/instaboost.py#L7
  16. Version: v2.0.0
  17. Models:
  18. - Name: mask-rcnn_r50_fpn_instaboost_4x_coco
  19. In Collection: InstaBoost
  20. Config: configs/instaboost/mask-rcnn_r50_fpn_instaboost-4x_coco.py
  21. Metadata:
  22. Training Memory (GB): 4.4
  23. inference time (ms/im):
  24. - value: 57.14
  25. hardware: V100
  26. backend: PyTorch
  27. batch size: 1
  28. mode: FP32
  29. resolution: (800, 1333)
  30. Epochs: 48
  31. Results:
  32. - Task: Object Detection
  33. Dataset: COCO
  34. Metrics:
  35. box AP: 40.6
  36. - Task: Instance Segmentation
  37. Dataset: COCO
  38. Metrics:
  39. mask AP: 36.6
  40. Weights: https://download.openmmlab.com/mmdetection/v2.0/instaboost/mask_rcnn_r50_fpn_instaboost_4x_coco/mask_rcnn_r50_fpn_instaboost_4x_coco_20200307-d025f83a.pth
  41. - Name: mask-rcnn_r101_fpn_instaboost-4x_coco
  42. In Collection: InstaBoost
  43. Config: configs/instaboost/mask-rcnn_r101_fpn_instaboost-4x_coco.py
  44. Metadata:
  45. Training Memory (GB): 6.4
  46. Epochs: 48
  47. Results:
  48. - Task: Object Detection
  49. Dataset: COCO
  50. Metrics:
  51. box AP: 42.5
  52. - Task: Instance Segmentation
  53. Dataset: COCO
  54. Metrics:
  55. mask AP: 38.0
  56. Weights: https://download.openmmlab.com/mmdetection/v2.0/instaboost/mask_rcnn_r101_fpn_instaboost_4x_coco/mask_rcnn_r101_fpn_instaboost_4x_coco_20200703_235738-f23f3a5f.pth
  57. - Name: mask-rcnn_x101-64x4d_fpn_instaboost-4x_coco
  58. In Collection: InstaBoost
  59. Config: configs/instaboost/mask-rcnn_x101-64x4d_fpn_instaboost-4x_coco.py
  60. Metadata:
  61. Training Memory (GB): 10.7
  62. Epochs: 48
  63. Results:
  64. - Task: Object Detection
  65. Dataset: COCO
  66. Metrics:
  67. box AP: 44.7
  68. - Task: Instance Segmentation
  69. Dataset: COCO
  70. Metrics:
  71. mask AP: 39.7
  72. Weights: https://download.openmmlab.com/mmdetection/v2.0/instaboost/mask_rcnn_x101_64x4d_fpn_instaboost_4x_coco/mask_rcnn_x101_64x4d_fpn_instaboost_4x_coco_20200515_080947-8ed58c1b.pth
  73. - Name: cascade-mask-rcnn_r50_fpn_instaboost_4x_coco
  74. In Collection: InstaBoost
  75. Config: configs/instaboost/cascade-mask-rcnn_r50_fpn_instaboost-4x_coco.py
  76. Metadata:
  77. Training Memory (GB): 6.0
  78. inference time (ms/im):
  79. - value: 83.33
  80. hardware: V100
  81. backend: PyTorch
  82. batch size: 1
  83. mode: FP32
  84. resolution: (800, 1333)
  85. Epochs: 48
  86. Results:
  87. - Task: Object Detection
  88. Dataset: COCO
  89. Metrics:
  90. box AP: 43.7
  91. - Task: Instance Segmentation
  92. Dataset: COCO
  93. Metrics:
  94. mask AP: 38.0
  95. Weights: https://download.openmmlab.com/mmdetection/v2.0/instaboost/cascade_mask_rcnn_r50_fpn_instaboost_4x_coco/cascade_mask_rcnn_r50_fpn_instaboost_4x_coco_20200307-c19d98d9.pth