更换文档检测模型

paddle_detection/configs/retinanet/_base_/optimizer_1x.yml

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+epoch: 12
+
+LearningRate:
+  base_lr: 0.01
+  schedulers:
+  - !PiecewiseDecay
+    gamma: 0.1
+    milestones: [8, 11]
+  - !LinearWarmup
+    start_factor: 0.001
+    steps: 500
+
+OptimizerBuilder:
+  optimizer:
+    momentum: 0.9
+    type: Momentum
+  regularizer:
+    factor: 0.0001
+    type: L2

paddle_detection/configs/retinanet/_base_/optimizer_2x.yml

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+epoch: 24
+
+LearningRate:
+  base_lr: 0.01
+  schedulers:
+  - !PiecewiseDecay
+    gamma: 0.1
+    milestones: [16, 22]
+  - !LinearWarmup
+    start_factor: 0.001
+    steps: 500
+
+OptimizerBuilder:
+  optimizer:
+    momentum: 0.9
+    type: Momentum
+  regularizer:
+    factor: 0.0001
+    type: L2

paddle_detection/configs/retinanet/_base_/retinanet_r50_fpn.yml

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+architecture: RetinaNet
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
+
+RetinaNet:
+  backbone: ResNet
+  neck: FPN
+  head: RetinaHead
+
+ResNet:
+  depth: 50
+  variant: b
+  norm_type: bn
+  freeze_at: 0
+  return_idx: [1,2,3]
+  num_stages: 4
+
+FPN:
+  out_channel: 256
+  spatial_scales: [0.125, 0.0625, 0.03125]
+  extra_stage: 2
+  has_extra_convs: true
+  use_c5: false
+
+RetinaHead:
+  conv_feat:
+    name: RetinaFeat
+    feat_in: 256
+    feat_out: 256
+    num_convs: 4
+    norm_type: null
+    use_dcn: false
+  anchor_generator:
+    name: RetinaAnchorGenerator
+    octave_base_scale: 4
+    scales_per_octave: 3
+    aspect_ratios: [0.5, 1.0, 2.0]
+    strides: [8.0, 16.0, 32.0, 64.0, 128.0]
+  bbox_assigner:
+    name: MaxIoUAssigner
+    positive_overlap: 0.5
+    negative_overlap: 0.4
+    allow_low_quality: true
+  loss_class:
+    name: FocalLoss
+    gamma: 2.0
+    alpha: 0.25
+    loss_weight: 1.0
+  loss_bbox:
+    name: SmoothL1Loss
+    beta: 0.0
+    loss_weight: 1.0
+  nms:
+    name: MultiClassNMS
+    nms_top_k: 1000
+    keep_top_k: 100
+    score_threshold: 0.05
+    nms_threshold: 0.5

paddle_detection/configs/retinanet/_base_/retinanet_reader.yml

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+worker_num: 2
+TrainReader:
+  sample_transforms:
+    - Decode: {}
+    - RandomResize: {target_size: [[640, 1333], [672, 1333], [704, 1333], [736, 1333], [768, 1333], [800, 1333]], keep_ratio: True, interp: 1}
+    - RandomFlip: {}
+    - NormalizeImage: {is_scale: True, mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225]}
+    - Permute: {}
+  batch_transforms:
+    - PadBatch: {pad_to_stride: 32}
+  batch_size: 2
+  shuffle: True
+  drop_last: True
+  collate_batch: False
+
+
+EvalReader:
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: [800, 1333], keep_ratio: True, interp: 1}
+    - NormalizeImage: {is_scale: True, mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225]}
+    - Permute: {}
+  batch_transforms:
+    - PadBatch: {pad_to_stride: 32}
+  batch_size: 8
+
+
+TestReader:
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: [800, 1333], keep_ratio: True, interp: 1}
+    - NormalizeImage: {is_scale: True, mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225]}
+    - Permute: {}
+  batch_transforms:
+    - PadBatch: {pad_to_stride: 32}
+  batch_size: 1