metafile.yml 5.5 KB

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  1. Collections:
  2. - Name: FoveaBox
  3. Metadata:
  4. Training Data: COCO
  5. Training Techniques:
  6. - SGD with Momentum
  7. - Weight Decay
  8. Training Resources: 4x V100 GPUs
  9. Architecture:
  10. - FPN
  11. - ResNet
  12. Paper:
  13. URL: https://arxiv.org/abs/1904.03797
  14. Title: 'FoveaBox: Beyond Anchor-based Object Detector'
  15. README: configs/foveabox/README.md
  16. Code:
  17. URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/detectors/fovea.py#L6
  18. Version: v2.0.0
  19. Models:
  20. - Name: fovea_r50_fpn_4xb4-1x_coco
  21. In Collection: FoveaBox
  22. Config: configs/foveabox/fovea_r50_fpn_4xb4-1x_coco.py
  23. Metadata:
  24. Training Memory (GB): 5.6
  25. inference time (ms/im):
  26. - value: 41.49
  27. hardware: V100
  28. backend: PyTorch
  29. batch size: 1
  30. mode: FP32
  31. resolution: (800, 1333)
  32. Epochs: 12
  33. Results:
  34. - Task: Object Detection
  35. Dataset: COCO
  36. Metrics:
  37. box AP: 36.5
  38. Weights: https://download.openmmlab.com/mmdetection/v2.0/foveabox/fovea_r50_fpn_4x4_1x_coco/fovea_r50_fpn_4x4_1x_coco_20200219-ee4d5303.pth
  39. - Name: fovea_r50_fpn_4xb4-2x_coco
  40. In Collection: FoveaBox
  41. Config: configs/foveabox/fovea_r50_fpn_4xb4-2x_coco.py
  42. Metadata:
  43. Training Memory (GB): 5.6
  44. inference time (ms/im):
  45. - value: 41.49
  46. hardware: V100
  47. backend: PyTorch
  48. batch size: 1
  49. mode: FP32
  50. resolution: (800, 1333)
  51. Epochs: 24
  52. Results:
  53. - Task: Object Detection
  54. Dataset: COCO
  55. Metrics:
  56. box AP: 37.2
  57. Weights: https://download.openmmlab.com/mmdetection/v2.0/foveabox/fovea_r50_fpn_4x4_2x_coco/fovea_r50_fpn_4x4_2x_coco_20200203-2df792b1.pth
  58. - Name: fovea_r50_fpn_gn-head-align_4xb4-2x_coco
  59. In Collection: FoveaBox
  60. Config: configs/foveabox/fovea_r50_fpn_gn-head-align_4xb4-2x_coco.py
  61. Metadata:
  62. Training Memory (GB): 8.1
  63. inference time (ms/im):
  64. - value: 51.55
  65. hardware: V100
  66. backend: PyTorch
  67. batch size: 1
  68. mode: FP32
  69. resolution: (800, 1333)
  70. Epochs: 24
  71. Results:
  72. - Task: Object Detection
  73. Dataset: COCO
  74. Metrics:
  75. box AP: 37.9
  76. Weights: https://download.openmmlab.com/mmdetection/v2.0/foveabox/fovea_align_r50_fpn_gn-head_4x4_2x_coco/fovea_align_r50_fpn_gn-head_4x4_2x_coco_20200203-8987880d.pth
  77. - Name: fovea_r50_fpn_gn-head-align_ms-640-800-4xb4-2x_coco
  78. In Collection: FoveaBox
  79. Config: configs/foveabox/fovea_r50_fpn_gn-head-align_ms-640-800-4xb4-2x_coco.py
  80. Metadata:
  81. Training Memory (GB): 8.1
  82. inference time (ms/im):
  83. - value: 54.64
  84. hardware: V100
  85. backend: PyTorch
  86. batch size: 1
  87. mode: FP32
  88. resolution: (800, 1333)
  89. Epochs: 24
  90. Results:
  91. - Task: Object Detection
  92. Dataset: COCO
  93. Metrics:
  94. box AP: 40.4
  95. Weights: https://download.openmmlab.com/mmdetection/v2.0/foveabox/fovea_align_r50_fpn_gn-head_mstrain_640-800_4x4_2x_coco/fovea_align_r50_fpn_gn-head_mstrain_640-800_4x4_2x_coco_20200205-85ce26cb.pth
  96. - Name: fovea_r101_fpn_4xb4-1x_coco
  97. In Collection: FoveaBox
  98. Config: configs/foveabox/fovea_r101_fpn_4xb4-1x_coco.py
  99. Metadata:
  100. Training Memory (GB): 9.2
  101. inference time (ms/im):
  102. - value: 57.47
  103. hardware: V100
  104. backend: PyTorch
  105. batch size: 1
  106. mode: FP32
  107. resolution: (800, 1333)
  108. Epochs: 12
  109. Results:
  110. - Task: Object Detection
  111. Dataset: COCO
  112. Metrics:
  113. box AP: 38.6
  114. Weights: https://download.openmmlab.com/mmdetection/v2.0/foveabox/fovea_r101_fpn_4x4_1x_coco/fovea_r101_fpn_4x4_1x_coco_20200219-05e38f1c.pth
  115. - Name: fovea_r101_fpn_4xb4-2x_coco
  116. In Collection: FoveaBox
  117. Config: configs/foveabox/fovea_r101_fpn_4xb4-2x_coco.py
  118. Metadata:
  119. Training Memory (GB): 11.7
  120. Epochs: 24
  121. Results:
  122. - Task: Object Detection
  123. Dataset: COCO
  124. Metrics:
  125. box AP: 40.0
  126. Weights: https://download.openmmlab.com/mmdetection/v2.0/foveabox/fovea_r101_fpn_4x4_2x_coco/fovea_r101_fpn_4x4_2x_coco_20200208-02320ea4.pth
  127. - Name: fovea_r101_fpn_gn-head-align_4xb4-2x_coco
  128. In Collection: FoveaBox
  129. Config: configs/foveabox/fovea_r101_fpn_gn-head-align_4xb4-2x_coco.py
  130. Metadata:
  131. Training Memory (GB): 11.7
  132. inference time (ms/im):
  133. - value: 68.03
  134. hardware: V100
  135. backend: PyTorch
  136. batch size: 1
  137. mode: FP32
  138. resolution: (800, 1333)
  139. Epochs: 24
  140. Results:
  141. - Task: Object Detection
  142. Dataset: COCO
  143. Metrics:
  144. box AP: 40.0
  145. Weights: https://download.openmmlab.com/mmdetection/v2.0/foveabox/fovea_align_r101_fpn_gn-head_4x4_2x_coco/fovea_align_r101_fpn_gn-head_4x4_2x_coco_20200208-c39a027a.pth
  146. - Name: fovea_r101_fpn_gn-head-align_ms-640-800-4xb4-2x_coco
  147. In Collection: FoveaBox
  148. Config: configs/foveabox/fovea_r101_fpn_gn-head-align_ms-640-800-4xb4-2x_coco.py
  149. Metadata:
  150. Training Memory (GB): 11.7
  151. inference time (ms/im):
  152. - value: 68.03
  153. hardware: V100
  154. backend: PyTorch
  155. batch size: 1
  156. mode: FP32
  157. resolution: (800, 1333)
  158. Epochs: 24
  159. Results:
  160. - Task: Object Detection
  161. Dataset: COCO
  162. Metrics:
  163. box AP: 42.0
  164. Weights: https://download.openmmlab.com/mmdetection/v2.0/foveabox/fovea_align_r101_fpn_gn-head_mstrain_640-800_4x4_2x_coco/fovea_align_r101_fpn_gn-head_mstrain_640-800_4x4_2x_coco_20200208-649c5eb6.pth