forked from PulseFocusPlatform/PulseFocusPlatform
158 lines
3.0 KiB
YAML
158 lines
3.0 KiB
YAML
architecture: EfficientDet
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max_iters: 281250
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use_gpu: true
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pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/EfficientNetB0_pretrained.tar
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weights: output/efficientdet_d0/model_final
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log_iter: 20
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snapshot_iter: 10000
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metric: COCO
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save_dir: output
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num_classes: 81
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use_ema: true
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ema_decay: 0.9998
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EfficientDet:
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backbone: EfficientNet
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fpn: BiFPN
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efficient_head: EfficientHead
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anchor_grid: AnchorGrid
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box_loss_weight: 50.
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EfficientNet:
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# norm_type: sync_bn
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# TODO
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norm_type: bn
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scale: b0
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use_se: true
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BiFPN:
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num_chan: 64
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repeat: 3
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levels: 5
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EfficientHead:
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repeat: 3
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num_chan: 64
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prior_prob: 0.01
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num_anchors: 9
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gamma: 1.5
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alpha: 0.25
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delta: 0.1
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output_decoder:
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score_thresh: 0.05 # originally 0.
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nms_thresh: 0.5
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pre_nms_top_n: 1000 # originally 5000
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detections_per_im: 100
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nms_eta: 1.0
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AnchorGrid:
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anchor_base_scale: 4
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num_scales: 3
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aspect_ratios: [[1, 1], [1.4, 0.7], [0.7, 1.4]]
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LearningRate:
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base_lr: 0.16
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schedulers:
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- !CosineDecayWithSkip
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total_steps: 281250
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skip_steps: 938
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- !LinearWarmup
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start_factor: 0.05
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steps: 938
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OptimizerBuilder:
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clip_grad_by_norm: 10.
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optimizer:
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momentum: 0.9
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type: Momentum
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regularizer:
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factor: 0.00004
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type: L2
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TrainReader:
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inputs_def:
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fields: ['image', 'im_id', 'fg_num', 'gt_label', 'gt_target']
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dataset:
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!COCODataSet
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image_dir: train2017
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anno_path: annotations/instances_train2017.json
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dataset_dir: dataset/coco
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sample_transforms:
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- !DecodeImage
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to_rgb: true
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- !RandomFlipImage
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prob: 0.5
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- !NormalizeImage
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is_channel_first: false
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is_scale: true
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mean: [0.485,0.456,0.406]
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std: [0.229, 0.224,0.225]
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- !RandomScaledCrop
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target_dim: 512
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scale_range: [.1, 2.]
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interp: 1
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- !Permute
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to_bgr: false
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channel_first: true
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- !TargetAssign
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image_size: 512
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batch_size: 16
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shuffle: true
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worker_num: 32
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bufsize: 16
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use_process: true
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drop_empty: false
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EvalReader:
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inputs_def:
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fields: ['image', 'im_info', 'im_id']
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dataset:
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!COCODataSet
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image_dir: val2017
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anno_path: annotations/instances_val2017.json
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dataset_dir: dataset/coco
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sample_transforms:
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- !DecodeImage
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to_rgb: true
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with_mixup: false
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- !NormalizeImage
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is_channel_first: false
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is_scale: true
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mean: [0.485,0.456,0.406]
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std: [0.229, 0.224,0.225]
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- !ResizeAndPad
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target_dim: 512
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interp: 1
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- !Permute
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channel_first: true
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to_bgr: false
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drop_empty: false
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batch_size: 16
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shuffle: false
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worker_num: 2
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TestReader:
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inputs_def:
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fields: ['image', 'im_info', 'im_id']
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image_shape: [3, 512, 512]
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dataset:
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!ImageFolder
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anno_path: annotations/instances_val2017.json
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sample_transforms:
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- !DecodeImage
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to_rgb: true
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with_mixup: false
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- !NormalizeImage
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is_channel_first: false
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is_scale: true
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mean: [0.485,0.456,0.406]
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std: [0.229, 0.224,0.225]
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- !ResizeAndPad
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target_dim: 512
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interp: 1
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- !Permute
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channel_first: true
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to_bgr: false
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batch_size: 16
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shuffle: false
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