metafile.yml 8.5 KB

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  1. Models:
  2. - Name: faster-rcnn_s50_fpn_syncbn-backbone+head_ms-range-1x_coco
  3. In Collection: Faster R-CNN
  4. Config: configs/resnest/faster-rcnn_s50_fpn_syncbn-backbone+head_ms-range-1x_coco.py
  5. Metadata:
  6. Training Memory (GB): 4.8
  7. Epochs: 12
  8. Training Data: COCO
  9. Training Techniques:
  10. - SGD with Momentum
  11. - Weight Decay
  12. Training Resources: 8x V100 GPUs
  13. Architecture:
  14. - ResNeSt
  15. Results:
  16. - Task: Object Detection
  17. Dataset: COCO
  18. Metrics:
  19. box AP: 42.0
  20. Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/faster_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco/faster_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco_20200926_125502-20289c16.pth
  21. Paper:
  22. URL: https://arxiv.org/abs/2004.08955
  23. Title: 'ResNeSt: Split-Attention Networks'
  24. README: configs/resnest/README.md
  25. Code:
  26. URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273
  27. Version: v2.7.0
  28. - Name: faster-rcnn_s101_fpn_syncbn-backbone+head_ms-range-1x_coco
  29. In Collection: Faster R-CNN
  30. Config: configs/resnest/faster-rcnn_s101_fpn_syncbn-backbone+head_ms-range-1x_coco.py
  31. Metadata:
  32. Training Memory (GB): 7.1
  33. Epochs: 12
  34. Training Data: COCO
  35. Training Techniques:
  36. - SGD with Momentum
  37. - Weight Decay
  38. Training Resources: 8x V100 GPUs
  39. Architecture:
  40. - ResNeSt
  41. Results:
  42. - Task: Object Detection
  43. Dataset: COCO
  44. Metrics:
  45. box AP: 44.5
  46. Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/faster_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco/faster_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco_20201006_021058-421517f1.pth
  47. Paper:
  48. URL: https://arxiv.org/abs/2004.08955
  49. Title: 'ResNeSt: Split-Attention Networks'
  50. README: configs/resnest/README.md
  51. Code:
  52. URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273
  53. Version: v2.7.0
  54. - Name: mask-rcnn_s50_fpn_syncbn-backbone+head_ms-1x_coco
  55. In Collection: Mask R-CNN
  56. Config: configs/resnest/mask-rcnn_s50_fpn_syncbn-backbone+head_ms-1x_coco.py
  57. Metadata:
  58. Training Memory (GB): 5.5
  59. Epochs: 12
  60. Training Data: COCO
  61. Training Techniques:
  62. - SGD with Momentum
  63. - Weight Decay
  64. Training Resources: 8x V100 GPUs
  65. Architecture:
  66. - ResNeSt
  67. Results:
  68. - Task: Object Detection
  69. Dataset: COCO
  70. Metrics:
  71. box AP: 42.6
  72. - Task: Instance Segmentation
  73. Dataset: COCO
  74. Metrics:
  75. mask AP: 38.1
  76. Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/mask_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco/mask_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco_20200926_125503-8a2c3d47.pth
  77. Paper:
  78. URL: https://arxiv.org/abs/2004.08955
  79. Title: 'ResNeSt: Split-Attention Networks'
  80. README: configs/resnest/README.md
  81. Code:
  82. URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273
  83. Version: v2.7.0
  84. - Name: mask-rcnn_s101_fpn_syncbn-backbone+head_ms-1x_coco
  85. In Collection: Mask R-CNN
  86. Config: configs/resnest/mask-rcnn_s101_fpn_syncbn-backbone+head_ms-1x_coco.py
  87. Metadata:
  88. Training Memory (GB): 7.8
  89. Epochs: 12
  90. Training Data: COCO
  91. Training Techniques:
  92. - SGD with Momentum
  93. - Weight Decay
  94. Training Resources: 8x V100 GPUs
  95. Architecture:
  96. - ResNeSt
  97. Results:
  98. - Task: Object Detection
  99. Dataset: COCO
  100. Metrics:
  101. box AP: 45.2
  102. - Task: Instance Segmentation
  103. Dataset: COCO
  104. Metrics:
  105. mask AP: 40.2
  106. Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/mask_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco/mask_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco_20201005_215831-af60cdf9.pth
  107. Paper:
  108. URL: https://arxiv.org/abs/2004.08955
  109. Title: 'ResNeSt: Split-Attention Networks'
  110. README: configs/resnest/README.md
  111. Code:
  112. URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273
  113. Version: v2.7.0
  114. - Name: cascade-rcnn_s50_fpn_syncbn-backbone+head_ms-range-1x_coco
  115. In Collection: Cascade R-CNN
  116. Config: configs/resnest/cascade-rcnn_s50_fpn_syncbn-backbone+head_ms-range-1x_coco.py
  117. Metadata:
  118. Epochs: 12
  119. Training Data: COCO
  120. Training Techniques:
  121. - SGD with Momentum
  122. - Weight Decay
  123. Training Resources: 8x V100 GPUs
  124. Architecture:
  125. - ResNeSt
  126. Results:
  127. - Task: Object Detection
  128. Dataset: COCO
  129. Metrics:
  130. box AP: 44.5
  131. Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/cascade_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco/cascade_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco_20201122_213640-763cc7b5.pth
  132. Paper:
  133. URL: https://arxiv.org/abs/2004.08955
  134. Title: 'ResNeSt: Split-Attention Networks'
  135. README: configs/resnest/README.md
  136. Code:
  137. URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273
  138. Version: v2.7.0
  139. - Name: cascade-rcnn_s101_fpn_syncbn-backbone+head_ms-range-1x_coco
  140. In Collection: Cascade R-CNN
  141. Config: configs/resnest/cascade-rcnn_s101_fpn_syncbn-backbone+head_ms-range-1x_coco.py
  142. Metadata:
  143. Training Memory (GB): 8.4
  144. Epochs: 12
  145. Training Data: COCO
  146. Training Techniques:
  147. - SGD with Momentum
  148. - Weight Decay
  149. Training Resources: 8x V100 GPUs
  150. Architecture:
  151. - ResNeSt
  152. Results:
  153. - Task: Object Detection
  154. Dataset: COCO
  155. Metrics:
  156. box AP: 46.8
  157. Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/cascade_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco/cascade_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco_20201005_113242-b9459f8f.pth
  158. Paper:
  159. URL: https://arxiv.org/abs/2004.08955
  160. Title: 'ResNeSt: Split-Attention Networks'
  161. README: configs/resnest/README.md
  162. Code:
  163. URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273
  164. Version: v2.7.0
  165. - Name: cascade-mask-rcnn_s50_fpn_syncbn-backbone+head_ms-1x_coco
  166. In Collection: Cascade R-CNN
  167. Config: configs/resnest/cascade-mask-rcnn_s50_fpn_syncbn-backbone+head_ms-1x_coco.py
  168. Metadata:
  169. Epochs: 12
  170. Training Data: COCO
  171. Training Techniques:
  172. - SGD with Momentum
  173. - Weight Decay
  174. Training Resources: 8x V100 GPUs
  175. Architecture:
  176. - ResNeSt
  177. Results:
  178. - Task: Object Detection
  179. Dataset: COCO
  180. Metrics:
  181. box AP: 45.4
  182. - Task: Instance Segmentation
  183. Dataset: COCO
  184. Metrics:
  185. mask AP: 39.5
  186. Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/cascade_mask_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco/cascade_mask_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco_20201122_104428-99eca4c7.pth
  187. Paper:
  188. URL: https://arxiv.org/abs/2004.08955
  189. Title: 'ResNeSt: Split-Attention Networks'
  190. README: configs/resnest/README.md
  191. Code:
  192. URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273
  193. Version: v2.7.0
  194. - Name: cascade-mask-rcnn_s101_fpn_syncbn-backbone+head_ms-1x_coco
  195. In Collection: Cascade R-CNN
  196. Config: configs/resnest/cascade-mask-rcnn_s101_fpn_syncbn-backbone+head_ms-1x_coco.py
  197. Metadata:
  198. Training Memory (GB): 10.5
  199. Epochs: 12
  200. Training Data: COCO
  201. Training Techniques:
  202. - SGD with Momentum
  203. - Weight Decay
  204. Training Resources: 8x V100 GPUs
  205. Architecture:
  206. - ResNeSt
  207. Results:
  208. - Task: Object Detection
  209. Dataset: COCO
  210. Metrics:
  211. box AP: 47.7
  212. - Task: Instance Segmentation
  213. Dataset: COCO
  214. Metrics:
  215. mask AP: 41.4
  216. Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/cascade_mask_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco/cascade_mask_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco_20201005_113243-42607475.pth
  217. Paper:
  218. URL: https://arxiv.org/abs/2004.08955
  219. Title: 'ResNeSt: Split-Attention Networks'
  220. README: configs/resnest/README.md
  221. Code:
  222. URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273
  223. Version: v2.7.0