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- architecture: MaskRCNN
- use_gpu: true
- max_iters: 360000
- snapshot_iter: 10000
- log_iter: 20
- save_dir: output
- pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar
- metric: COCO
- weights: output/mask_rcnn_r50_2x/model_final
- num_classes: 81
- MaskRCNN:
- backbone: ResNet
- rpn_head: RPNHead
- roi_extractor: RoIAlign
- bbox_assigner: BBoxAssigner
- bbox_head: BBoxHead
- mask_assigner: MaskAssigner
- mask_head: MaskHead
- ResNet:
- norm_type: affine_channel
- norm_decay: 0.
- depth: 50
- feature_maps: 4
- freeze_at: 2
- ResNetC5:
- depth: 50
- norm_type: affine_channel
- RPNHead:
- anchor_generator:
- anchor_sizes: [32, 64, 128, 256, 512]
- aspect_ratios: [0.5, 1.0, 2.0]
- stride: [16.0, 16.0]
- variance: [1.0, 1.0, 1.0, 1.0]
- rpn_target_assign:
- rpn_batch_size_per_im: 256
- rpn_fg_fraction: 0.5
- rpn_negative_overlap: 0.3
- rpn_positive_overlap: 0.7
- rpn_straddle_thresh: 0.0
- train_proposal:
- min_size: 0.0
- nms_thresh: 0.7
- pre_nms_top_n: 12000
- post_nms_top_n: 2000
- test_proposal:
- min_size: 0.0
- nms_thresh: 0.7
- pre_nms_top_n: 6000
- post_nms_top_n: 1000
- RoIAlign:
- resolution: 14
- spatial_scale: 0.0625
- sampling_ratio: 0
- BBoxHead:
- head: ResNetC5
- nms:
- keep_top_k: 100
- nms_threshold: 0.5
- normalized: false
- score_threshold: 0.05
- MaskHead:
- dilation: 1
- conv_dim: 256
- resolution: 14
- BBoxAssigner:
- batch_size_per_im: 512
- bbox_reg_weights: [0.1, 0.1, 0.2, 0.2]
- bg_thresh_hi: 0.5
- bg_thresh_lo: 0.0
- fg_fraction: 0.25
- fg_thresh: 0.5
- MaskAssigner:
- resolution: 14
- LearningRate:
- base_lr: 0.01
- schedulers:
- - !PiecewiseDecay
- gamma: 0.1
- milestones: [240000, 320000]
- #start the warm up from base_lr * start_factor
- - !LinearWarmup
- start_factor: 0.3333333333333333
- steps: 500
- OptimizerBuilder:
- optimizer:
- momentum: 0.9
- type: Momentum
- regularizer:
- factor: 0.0001
- type: L2
- _READER_: 'mask_reader.yml'
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