metafile.yml 4.8 KB

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  1. Collections:
  2. - Name: RepLKNet
  3. Metadata:
  4. Training Data: ImageNet-1k
  5. Architecture:
  6. - Large-Kernel Convolution
  7. - VGG-style Neural Network
  8. Paper:
  9. URL: https://arxiv.org/abs/2203.06717
  10. Title: 'Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs'
  11. README: configs/replknet/README.md
  12. Code:
  13. URL: https://github.com/open-mmlab/mmpretrain/blob/v1.0.0rc3/mmcls/models/backbones/replknet.py
  14. Version: v1.0.0rc3
  15. Models:
  16. - Name: replknet-31B_3rdparty_in1k
  17. In Collection: RepLKNet
  18. Config: configs/replknet/replknet-31B_32xb64_in1k.py
  19. Metadata:
  20. FLOPs: 15636547584
  21. Parameters: 79864168
  22. Results:
  23. - Dataset: ImageNet-1k
  24. Task: Image Classification
  25. Metrics:
  26. Top 1 Accuracy: 83.48
  27. Top 5 Accuracy: 96.57
  28. Weights: https://download.openmmlab.com/mmclassification/v0/replknet/replknet-31B_3rdparty_in1k_20221118-fd08e268.pth
  29. Converted From:
  30. Weights: https://drive.google.com/u/0/uc?id=1azQUiCxK9feYVkkrPqwVPBtNsTzDrX7S&export=download
  31. Code: https://github.com/DingXiaoH/RepLKNet-pytorch/blob/main/replknet.py
  32. - Name: replknet-31B_3rdparty_in1k-384px
  33. In Collection: RepLKNet
  34. Config: configs/replknet/replknet-31B_32xb64_in1k-384px.py
  35. Metadata:
  36. FLOPs: 45952303104
  37. Parameters: 79864168
  38. Results:
  39. - Dataset: ImageNet-1k
  40. Task: Image Classification
  41. Metrics:
  42. Top 1 Accuracy: 84.84
  43. Top 5 Accuracy: 97.34
  44. Weights: https://download.openmmlab.com/mmclassification/v0/replknet/replknet-31B_3rdparty_in1k-384px_20221118-03a170ce.pth
  45. Converted From:
  46. Weights: https://drive.google.com/u/0/uc?id=1vo-P3XB6mRLUeDzmgv90dOu73uCeLfZN&export=download
  47. Code: https://github.com/DingXiaoH/RepLKNet-pytorch/blob/main/replknet.py
  48. - Name: replknet-31B_in21k-pre_3rdparty_in1k
  49. In Collection: RepLKNet
  50. Config: configs/replknet/replknet-31B_32xb64_in1k.py
  51. Metadata:
  52. Training Data:
  53. - ImageNet-21k
  54. - ImageNet-1k
  55. FLOPs: 15636547584
  56. Parameters: 79864168
  57. Results:
  58. - Dataset: ImageNet-1k
  59. Task: Image Classification
  60. Metrics:
  61. Top 1 Accuracy: 85.20
  62. Top 5 Accuracy: 97.56
  63. Weights: https://download.openmmlab.com/mmclassification/v0/replknet/replknet-31B_in21k-pre_3rdparty_in1k_20221118-54ed5c46.pth
  64. Converted From:
  65. Weights: https://drive.google.com/u/0/uc?id=1DslZ2voXZQR1QoFY9KnbsHAeF84hzS0s&export=download
  66. Code: https://github.com/DingXiaoH/RepLKNet-pytorch/blob/main/replknet.py
  67. - Name: replknet-31B_in21k-pre_3rdparty_in1k-384px
  68. In Collection: RepLKNet
  69. Config: configs/replknet/replknet-31B_32xb64_in1k-384px.py
  70. Metadata:
  71. Training Data:
  72. - ImageNet-21k
  73. - ImageNet-1k
  74. FLOPs: 45952303104
  75. Parameters: 79864168
  76. Results:
  77. - Dataset: ImageNet-1k
  78. Task: Image Classification
  79. Metrics:
  80. Top 1 Accuracy: 85.99
  81. Top 5 Accuracy: 97.75
  82. Weights: https://download.openmmlab.com/mmclassification/v0/replknet/replknet-31B_in21k-pre_3rdparty_in1k-384px_20221118-76c92b24.pth
  83. Converted From:
  84. Weights: https://drive.google.com/u/0/uc?id=1Sc46BWdXXm2fVP-K_hKKU_W8vAB-0duX&export=download
  85. Code: https://github.com/DingXiaoH/RepLKNet-pytorch/blob/main/replknet.py
  86. - Name: replknet-31L_in21k-pre_3rdparty_in1k-384px
  87. In Collection: RepLKNet
  88. Config: configs/replknet/replknet-31L_32xb64_in1k-384px.py
  89. Metadata:
  90. Training Data:
  91. - ImageNet-21k
  92. - ImageNet-1k
  93. FLOPs: 97240006656
  94. Parameters: 172671016
  95. Results:
  96. - Dataset: ImageNet-1k
  97. Task: Image Classification
  98. Metrics:
  99. Top 1 Accuracy: 86.63
  100. Top 5 Accuracy: 98.00
  101. Weights: https://download.openmmlab.com/mmclassification/v0/replknet/replknet-31L_in21k-pre_3rdparty_in1k-384px_20221118-dc3fc07c.pth
  102. Converted From:
  103. Weights: https://drive.google.com/u/0/uc?id=1JYXoNHuRvC33QV1pmpzMTKEni1hpWfBl&export=download
  104. Code: https://github.com/DingXiaoH/RepLKNet-pytorch/blob/main/replknet.py
  105. - Name: replknet-XL_meg73m-pre_3rdparty_in1k-320px
  106. In Collection: RepLKNet
  107. Config: configs/replknet/replknet-XL_32xb64_in1k-320px.py
  108. Metadata:
  109. Training Data:
  110. - MegData-73M
  111. - ImageNet-1k
  112. FLOPs: 129570201600
  113. Parameters: 335435752
  114. Results:
  115. - Dataset: ImageNet-1k
  116. Task: Image Classification
  117. Metrics:
  118. Top 1 Accuracy: 87.57
  119. Top 5 Accuracy: 98.39
  120. Weights: https://download.openmmlab.com/mmclassification/v0/replknet/replknet-XL_meg73m-pre_3rdparty_in1k-320px_20221118-88259b1d.pth
  121. Converted From:
  122. Weights: https://drive.google.com/u/0/uc?id=1tPC60El34GntXByIRHb-z-Apm4Y5LX1T&export=download
  123. Code: https://github.com/DingXiaoH/RepLKNet-pytorch/blob/main/replknet.py