yolov3_darknet.yml 1.1 KB

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  1. architecture: YOLOv3
  2. use_gpu: true
  3. max_iters: 500000
  4. log_iter: 20
  5. save_dir: output
  6. snapshot_iter: 10000
  7. metric: COCO
  8. pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar
  9. weights: output/yolov3_darknet/model_final
  10. num_classes: 80
  11. use_fine_grained_loss: false
  12. YOLOv3:
  13. backbone: DarkNet
  14. yolo_head: YOLOv3Head
  15. DarkNet:
  16. norm_type: sync_bn
  17. norm_decay: 0.
  18. depth: 53
  19. YOLOv3Head:
  20. anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
  21. anchors: [[10, 13], [16, 30], [33, 23],
  22. [30, 61], [62, 45], [59, 119],
  23. [116, 90], [156, 198], [373, 326]]
  24. norm_decay: 0.
  25. yolo_loss: YOLOv3Loss
  26. nms:
  27. background_label: -1
  28. keep_top_k: 100
  29. nms_threshold: 0.45
  30. nms_top_k: 1000
  31. normalized: false
  32. score_threshold: 0.01
  33. YOLOv3Loss:
  34. ignore_thresh: 0.7
  35. label_smooth: true
  36. LearningRate:
  37. base_lr: 0.001
  38. schedulers:
  39. - !PiecewiseDecay
  40. gamma: 0.1
  41. milestones:
  42. - 400000
  43. - 450000
  44. - !LinearWarmup
  45. start_factor: 0.
  46. steps: 4000
  47. OptimizerBuilder:
  48. optimizer:
  49. momentum: 0.9
  50. type: Momentum
  51. regularizer:
  52. factor: 0.0005
  53. type: L2
  54. _READER_: 'yolov3_reader.yml'