ppyolo_eb.yml 1.4 KB

1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374
  1. architecture: YOLOv3
  2. use_gpu: true
  3. max_iters: 500000
  4. save_dir: output
  5. snapshot_iter: 10000
  6. metric: COCO
  7. pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet34_vd_pretrained.tar
  8. weights: output/ppyolo_eb/best_model
  9. num_classes: 80
  10. use_fine_grained_loss: true
  11. log_iter: 1000
  12. use_ema: true
  13. ema_decay: 0.9998
  14. YOLOv3:
  15. backbone: ResNet_EB
  16. yolo_head: EBHead
  17. ResNet_EB:
  18. norm_type: sync_bn
  19. freeze_at: 0
  20. freeze_norm: false
  21. norm_decay: 0.
  22. depth: 34
  23. variant: d
  24. feature_maps: [3, 4, 5]
  25. EBHead:
  26. anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
  27. anchors: [[10, 13], [16, 30], [33, 23],
  28. [30, 61], [62, 45], [59, 119],
  29. [116, 90], [156, 198], [373, 326]]
  30. norm_decay: 0.
  31. yolo_loss: YOLOv3Loss
  32. nms:
  33. background_label: -1
  34. keep_top_k: 100
  35. nms_threshold: 0.45
  36. nms_top_k: 1000
  37. normalized: false
  38. score_threshold: 0.01
  39. YOLOv3Loss:
  40. ignore_thresh: 0.7
  41. label_smooth: false
  42. use_fine_grained_loss: true
  43. iou_loss: IouLoss
  44. IouLoss:
  45. loss_weight: 2.5
  46. max_height: 608
  47. max_width: 608
  48. LearningRate:
  49. base_lr: 0.001
  50. schedulers:
  51. - !PiecewiseDecay
  52. gamma: 0.1
  53. milestones:
  54. - 320000
  55. - 450000
  56. - !LinearWarmup
  57. start_factor: 0.
  58. steps: 4000
  59. OptimizerBuilder:
  60. optimizer:
  61. momentum: 0.9
  62. type: Momentum
  63. regularizer:
  64. factor: 0.0005
  65. type: L2
  66. _READER_: 'ppyolo_reader.yml'