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- architecture: YOLOv3
- use_gpu: true
- max_iters: 70000
- log_iter: 20
- save_dir: output
- snapshot_iter: 2000
- metric: VOC
- map_type: 11point
- pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar
- weights: output/yolov3_darknet_voc/model_final
- num_classes: 20
- use_fine_grained_loss: true
- YOLOv3:
- backbone: DarkNet
- yolo_head: YOLOv3Head
- DarkNet:
- norm_type: sync_bn
- norm_decay: 0.
- depth: 53
- YOLOv3Head:
- anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
- anchors: [[10, 13], [16, 30], [33, 23],
- [30, 61], [62, 45], [59, 119],
- [116, 90], [156, 198], [373, 326]]
- norm_decay: 0.
- yolo_loss: YOLOv3Loss
- nms:
- background_label: -1
- keep_top_k: 100
- nms_threshold: 0.45
- nms_top_k: 1000
- normalized: false
- score_threshold: 0.01
- YOLOv3Loss:
- ignore_thresh: 0.7
- label_smooth: false
- iou_loss: DiouLossYolo
- DiouLossYolo:
- loss_weight: 5
- LearningRate:
- base_lr: 0.001
- schedulers:
- - !PiecewiseDecay
- gamma: 0.1
- milestones:
- - 55000
- - 62000
- - !LinearWarmup
- start_factor: 0.
- steps: 1000
- OptimizerBuilder:
- optimizer:
- momentum: 0.9
- type: Momentum
- regularizer:
- factor: 0.0005
- type: L2
- _READER_: 'yolov3_reader.yml'
- TrainReader:
- inputs_def:
- fields: ['image', 'gt_bbox', 'gt_class', 'gt_score']
- num_max_boxes: 50
- dataset:
- !VOCDataSet
- dataset_dir: dataset/voc
- anno_path: trainval.txt
- use_default_label: true
- with_background: false
- EvalReader:
- inputs_def:
- fields: ['image', 'im_size', 'im_id', 'gt_bbox', 'gt_class', 'is_difficult']
- num_max_boxes: 50
- dataset:
- !VOCDataSet
- dataset_dir: dataset/voc
- anno_path: test.txt
- use_default_label: true
- with_background: false
- TestReader:
- dataset:
- !ImageFolder
- use_default_label: true
- with_background: false
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