metafile.yml 3.9 KB

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  1. Collections:
  2. - Name: YOLOv3
  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. - DarkNet
  11. Paper:
  12. URL: https://arxiv.org/abs/1804.02767
  13. Title: 'YOLOv3: An Incremental Improvement'
  14. README: configs/yolo/README.md
  15. Code:
  16. URL: https://github.com/open-mmlab/mmdetection/blob/v2.4.0/mmdet/models/detectors/yolo.py#L8
  17. Version: v2.4.0
  18. Models:
  19. - Name: yolov3_d53_320_273e_coco
  20. In Collection: YOLOv3
  21. Config: configs/yolo/yolov3_d53_8xb8-320-273e_coco.py
  22. Metadata:
  23. Training Memory (GB): 2.7
  24. inference time (ms/im):
  25. - value: 15.65
  26. hardware: V100
  27. backend: PyTorch
  28. batch size: 1
  29. mode: FP32
  30. resolution: (320, 320)
  31. Epochs: 273
  32. Results:
  33. - Task: Object Detection
  34. Dataset: COCO
  35. Metrics:
  36. box AP: 27.9
  37. Weights: https://download.openmmlab.com/mmdetection/v2.0/yolo/yolov3_d53_320_273e_coco/yolov3_d53_320_273e_coco-421362b6.pth
  38. - Name: yolov3_d53_mstrain-416_273e_coco
  39. In Collection: YOLOv3
  40. Config: configs/yolo/yolov3_d53_8xb8-ms-416-273e_coco.py
  41. Metadata:
  42. Training Memory (GB): 3.8
  43. inference time (ms/im):
  44. - value: 16.34
  45. hardware: V100
  46. backend: PyTorch
  47. batch size: 1
  48. mode: FP32
  49. resolution: (416, 416)
  50. Epochs: 273
  51. Results:
  52. - Task: Object Detection
  53. Dataset: COCO
  54. Metrics:
  55. box AP: 30.9
  56. Weights: https://download.openmmlab.com/mmdetection/v2.0/yolo/yolov3_d53_mstrain-416_273e_coco/yolov3_d53_mstrain-416_273e_coco-2b60fcd9.pth
  57. - Name: yolov3_d53_mstrain-608_273e_coco
  58. In Collection: YOLOv3
  59. Config: configs/yolo/yolov3_d53_8xb8-ms-608-273e_coco.py
  60. Metadata:
  61. Training Memory (GB): 7.4
  62. inference time (ms/im):
  63. - value: 20.79
  64. hardware: V100
  65. backend: PyTorch
  66. batch size: 1
  67. mode: FP32
  68. resolution: (608, 608)
  69. Epochs: 273
  70. Results:
  71. - Task: Object Detection
  72. Dataset: COCO
  73. Metrics:
  74. box AP: 33.7
  75. Weights: https://download.openmmlab.com/mmdetection/v2.0/yolo/yolov3_d53_mstrain-608_273e_coco/yolov3_d53_mstrain-608_273e_coco_20210518_115020-a2c3acb8.pth
  76. - Name: yolov3_d53_fp16_mstrain-608_273e_coco
  77. In Collection: YOLOv3
  78. Config: configs/yolo/yolov3_d53_8xb8-amp-ms-608-273e_coco.py
  79. Metadata:
  80. Training Memory (GB): 4.7
  81. inference time (ms/im):
  82. - value: 20.79
  83. hardware: V100
  84. backend: PyTorch
  85. batch size: 1
  86. mode: FP16
  87. resolution: (608, 608)
  88. Epochs: 273
  89. Results:
  90. - Task: Object Detection
  91. Dataset: COCO
  92. Metrics:
  93. box AP: 33.8
  94. Weights: https://download.openmmlab.com/mmdetection/v2.0/yolo/yolov3_d53_fp16_mstrain-608_273e_coco/yolov3_d53_fp16_mstrain-608_273e_coco_20210517_213542-4bc34944.pth
  95. - Name: yolov3_mobilenetv2_8xb24-320-300e_coco
  96. In Collection: YOLOv3
  97. Config: configs/yolo/yolov3_mobilenetv2_8xb24-320-300e_coco.py
  98. Metadata:
  99. Training Memory (GB): 3.2
  100. Epochs: 300
  101. Results:
  102. - Task: Object Detection
  103. Dataset: COCO
  104. Metrics:
  105. box AP: 22.2
  106. Weights: https://download.openmmlab.com/mmdetection/v2.0/yolo/yolov3_mobilenetv2_320_300e_coco/yolov3_mobilenetv2_320_300e_coco_20210719_215349-d18dff72.pth
  107. - Name: yolov3_mobilenetv2_8xb24-ms-416-300e_coco
  108. In Collection: YOLOv3
  109. Config: configs/yolo/yolov3_mobilenetv2_8xb24-ms-416-300e_coco.py
  110. Metadata:
  111. Training Memory (GB): 5.3
  112. Epochs: 300
  113. Results:
  114. - Task: Object Detection
  115. Dataset: COCO
  116. Metrics:
  117. box AP: 23.9
  118. Weights: https://download.openmmlab.com/mmdetection/v2.0/yolo/yolov3_mobilenetv2_mstrain-416_300e_coco/yolov3_mobilenetv2_mstrain-416_300e_coco_20210718_010823-f68a07b3.pth