ppyolo_2x.yml 1.6 KB

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  1. architecture: YOLOv3
  2. use_gpu: true
  3. max_iters: 500000
  4. log_iter: 100
  5. save_dir: output
  6. snapshot_iter: 10000
  7. metric: COCO
  8. pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_ssld_pretrained.tar
  9. weights: output/ppyolo/model_final
  10. num_classes: 80
  11. use_fine_grained_loss: true
  12. use_ema: true
  13. ema_decay: 0.9998
  14. YOLOv3:
  15. backbone: ResNet
  16. yolo_head: YOLOv3Head
  17. use_fine_grained_loss: true
  18. ResNet:
  19. norm_type: sync_bn
  20. freeze_at: 0
  21. freeze_norm: false
  22. norm_decay: 0.
  23. depth: 50
  24. feature_maps: [3, 4, 5]
  25. variant: d
  26. dcn_v2_stages: [5]
  27. YOLOv3Head:
  28. anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
  29. anchors: [[10, 13], [16, 30], [33, 23],
  30. [30, 61], [62, 45], [59, 119],
  31. [116, 90], [156, 198], [373, 326]]
  32. norm_decay: 0.
  33. coord_conv: true
  34. iou_aware: true
  35. iou_aware_factor: 0.4
  36. scale_x_y: 1.05
  37. spp: true
  38. yolo_loss: YOLOv3Loss
  39. nms: MatrixNMS
  40. drop_block: true
  41. YOLOv3Loss:
  42. ignore_thresh: 0.7
  43. scale_x_y: 1.05
  44. label_smooth: false
  45. use_fine_grained_loss: true
  46. iou_loss: IouLoss
  47. iou_aware_loss: IouAwareLoss
  48. IouLoss:
  49. loss_weight: 2.5
  50. max_height: 608
  51. max_width: 608
  52. IouAwareLoss:
  53. loss_weight: 1.0
  54. max_height: 608
  55. max_width: 608
  56. MatrixNMS:
  57. background_label: -1
  58. keep_top_k: 100
  59. normalized: false
  60. score_threshold: 0.01
  61. post_threshold: 0.01
  62. LearningRate:
  63. base_lr: 0.01
  64. schedulers:
  65. - !PiecewiseDecay
  66. gamma: 0.1
  67. milestones:
  68. - 400000
  69. - 450000
  70. - !LinearWarmup
  71. start_factor: 0.
  72. steps: 4000
  73. OptimizerBuilder:
  74. optimizer:
  75. momentum: 0.9
  76. type: Momentum
  77. regularizer:
  78. factor: 0.0005
  79. type: L2
  80. _READER_: 'ppyolo_reader.yml'