forked from PulseFocusPlatform/PulseFocusPlatform
90 lines
1.7 KiB
YAML
90 lines
1.7 KiB
YAML
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architecture: YOLOv3
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use_gpu: true
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max_iters: 70000
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log_iter: 20
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save_dir: output
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snapshot_iter: 2000
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metric: VOC
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map_type: 11point
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pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet34_pretrained.tar
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weights: output/yolov3_r34_voc/model_final
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num_classes: 20
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use_fine_grained_loss: false
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YOLOv3:
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backbone: ResNet
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yolo_head: YOLOv3Head
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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: 34
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feature_maps: [3, 4, 5]
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YOLOv3Head:
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anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]]
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anchors: [[10, 13], [16, 30], [33, 23],
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[30, 61], [62, 45], [59, 119],
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[116, 90], [156, 198], [373, 326]]
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norm_decay: 0.
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yolo_loss: YOLOv3Loss
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nms:
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background_label: -1
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keep_top_k: 100
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nms_threshold: 0.45
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nms_top_k: 1000
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normalized: false
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score_threshold: 0.01
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YOLOv3Loss:
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ignore_thresh: 0.7
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label_smooth: false
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LearningRate:
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base_lr: 0.001
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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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- 55000
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- 62000
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- !LinearWarmup
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start_factor: 0.
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steps: 1000
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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_: 'yolov3_reader.yml'
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TrainReader:
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dataset:
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!VOCDataSet
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dataset_dir: dataset/voc
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anno_path: trainval.txt
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use_default_label: true
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with_background: false
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EvalReader:
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inputs_def:
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fields: ['image', 'im_size', 'im_id', 'gt_bbox', 'gt_class', 'is_difficult']
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num_max_boxes: 50
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dataset:
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!VOCDataSet
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dataset_dir: dataset/voc
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anno_path: test.txt
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use_default_label: true
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with_background: false
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TestReader:
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dataset:
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!ImageFolder
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use_default_label: true
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with_background: false
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