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- architecture: YOLOv3
- use_gpu: true
- max_iters: 500000
- log_iter: 20
- save_dir: output
- snapshot_iter: 10000
- metric: COCO
- pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/MobileNetV3_large_x1_0_pretrained.tar
- weights: output/yolov3_mobilenet_v3/model_final
- num_classes: 80
- use_fine_grained_loss: false
- YOLOv3:
- backbone: MobileNetV3
- yolo_head: YOLOv3Head
- MobileNetV3:
- norm_type: sync_bn
- norm_decay: 0.
- model_name: large
- scale: 1.
- extra_block_filters: []
- feature_maps: [1, 2, 3, 4, 6]
- 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
- LearningRate:
- base_lr: 0.001
- schedulers:
- - !PiecewiseDecay
- gamma: 0.1
- milestones:
- - 400000
- - 450000
- - !LinearWarmup
- start_factor: 0.
- steps: 4000
- OptimizerBuilder:
- optimizer:
- momentum: 0.9
- type: Momentum
- regularizer:
- factor: 0.0005
- type: L2
- _READER_: 'yolov3_reader.yml'
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