forked from PulseFocusPlatform/PulseFocusPlatform
134 lines
2.8 KiB
YAML
134 lines
2.8 KiB
YAML
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architecture: YOLOv3
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use_gpu: true
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max_iters: 250000
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log_iter: 20
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save_dir: output
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snapshot_iter: 10000
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metric: COCO
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pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet18_vd_pretrained.tar
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weights: output/ppyolo_tiny/model_final
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num_classes: 80
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use_fine_grained_loss: true
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use_ema: true
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ema_decay: 0.9998
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YOLOv3:
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backbone: ResNet
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yolo_head: YOLOv3Head
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use_fine_grained_loss: true
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ResNet:
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norm_type: sync_bn
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freeze_at: 0
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freeze_norm: false
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norm_decay: 0.
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depth: 18
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feature_maps: [4, 5]
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variant: d
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YOLOv3Head:
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anchor_masks: [[3, 4, 5], [0, 1, 2]]
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anchors: [[10, 14], [23, 27], [37, 58],
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[81, 82], [135, 169], [344, 319]]
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norm_decay: 0.
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conv_block_num: 0
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scale_x_y: 1.05
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yolo_loss: YOLOv3Loss
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nms: MatrixNMS
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drop_block: true
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YOLOv3Loss:
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ignore_thresh: 0.7
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scale_x_y: 1.05
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label_smooth: false
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use_fine_grained_loss: true
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iou_loss: IouLoss
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IouLoss:
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loss_weight: 2.5
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max_height: 608
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max_width: 608
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MatrixNMS:
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background_label: -1
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keep_top_k: 100
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normalized: false
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score_threshold: 0.01
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post_threshold: 0.01
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LearningRate:
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base_lr: 0.004
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schedulers:
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- !PiecewiseDecay
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gamma: 0.1
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milestones:
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- 150000
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- 200000
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- !LinearWarmup
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start_factor: 0.
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steps: 4000
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OptimizerBuilder:
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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: 0.0005
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type: L2
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_READER_: 'ppyolo_reader.yml'
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TrainReader:
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inputs_def:
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fields: ['image', 'gt_bbox', 'gt_class', 'gt_score']
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num_max_boxes: 50
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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: train_data/dataset/coco
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with_background: false
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sample_transforms:
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- !DecodeImage
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to_rgb: True
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with_mixup: True
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- !MixupImage
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alpha: 1.5
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beta: 1.5
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- !ColorDistort {}
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- !RandomExpand
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fill_value: [123.675, 116.28, 103.53]
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- !RandomCrop {}
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- !RandomFlipImage
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is_normalized: false
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- !NormalizeBox {}
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- !PadBox
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num_max_boxes: 50
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- !BboxXYXY2XYWH {}
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batch_transforms:
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- !RandomShape
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sizes: [320, 352, 384, 416, 448, 480, 512, 544, 576, 608]
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random_inter: True
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- !NormalizeImage
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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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is_scale: True
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is_channel_first: false
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- !Permute
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to_bgr: false
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channel_first: True
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# Gt2YoloTarget is only used when use_fine_grained_loss set as true,
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# this operator will be deleted automatically if use_fine_grained_loss
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# is set as false
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- !Gt2YoloTarget
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anchor_masks: [[3, 4, 5], [0, 1, 2]]
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anchors: [[10, 14], [23, 27], [37, 58],
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[81, 82], [135, 169], [344, 319]]
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downsample_ratios: [32, 16]
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batch_size: 32
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shuffle: true
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mixup_epoch: 500
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drop_last: true
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worker_num: 16
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bufsize: 8
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use_process: true
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