forked from p71924506/PulseFocusPlatform
154 lines
3.2 KiB
YAML
154 lines
3.2 KiB
YAML
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architecture: SSD
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use_gpu: true
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max_iters: 120000
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snapshot_iter: 10000
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log_iter: 20
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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/VGG16_caffe_pretrained.tar
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save_dir: output
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weights: output/ssd_vgg16_512_voc/model_final
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# 20(label_class) + 1(background)
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num_classes: 21
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SSD:
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backbone: VGG
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multi_box_head: MultiBoxHead
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output_decoder:
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background_label: 0
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keep_top_k: 200
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nms_eta: 1.0
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nms_threshold: 0.45
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nms_top_k: 400
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score_threshold: 0.01
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VGG:
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depth: 16
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with_extra_blocks: true
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normalizations: [20., -1, -1, -1, -1, -1, -1]
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extra_block_filters: [[256, 512, 1, 2, 3], [128, 256, 1, 2, 3], [128, 256, 1, 2, 3], [128, 256, 1, 2, 3], [128, 256, 1, 1, 4]]
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MultiBoxHead:
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base_size: 512
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aspect_ratios: [[2.], [2., 3.], [2., 3.], [2., 3.], [2., 3.], [2.], [2.]]
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min_ratio: 20
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max_ratio: 90
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min_sizes: [20.0, 51.0, 133.0, 215.0, 296.0, 378.0, 460.0]
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max_sizes: [51.0, 133.0, 215.0, 296.0, 378.0, 460.0, 542.0]
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steps: [8, 16, 32, 64, 128, 256, 512]
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offset: 0.5
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flip: true
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kernel_size: 3
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pad: 1
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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: [80000, 100000]
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- !LinearWarmup
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start_factor: 0.3333333333333333
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steps: 500
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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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TrainReader:
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inputs_def:
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image_shape: [3, 512, 512]
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fields: ['image', 'gt_bbox', 'gt_class']
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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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sample_transforms:
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- !DecodeImage
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to_rgb: true
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- !RandomDistort
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brightness_lower: 0.875
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brightness_upper: 1.125
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is_order: true
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- !RandomExpand
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fill_value: [123, 117, 104]
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- !RandomCrop
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allow_no_crop: true
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- !NormalizeBox {}
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- !ResizeImage
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interp: 1
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target_size: 512
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use_cv2: false
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- !RandomFlipImage
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is_normalized: true
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- !Permute
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to_bgr: false
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- !NormalizeImage
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is_scale: false
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mean: [123, 117, 104]
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std: [1, 1, 1]
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batch_size: 8
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shuffle: true
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worker_num: 8
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bufsize: 16
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use_process: true
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EvalReader:
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inputs_def:
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image_shape: [3, 512, 512]
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fields: ['image', 'gt_bbox', 'gt_class', 'im_shape', 'im_id', 'is_difficult']
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dataset:
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!VOCDataSet
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anno_path: test.txt
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dataset_dir: dataset/voc
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use_default_label: true
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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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- !NormalizeBox {}
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- !ResizeImage
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interp: 1
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target_size: 512
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use_cv2: false
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- !Permute
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to_bgr: false
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- !NormalizeImage
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is_scale: false
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mean: [123, 117, 104]
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std: [1, 1, 1]
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batch_size: 32
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worker_num: 8
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bufsize: 16
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TestReader:
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inputs_def:
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image_shape: [3,512,512]
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fields: ['image', 'im_id', 'im_shape']
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dataset:
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!ImageFolder
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anno_path: test.txt
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use_default_label: true
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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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- !ResizeImage
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interp: 1
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max_size: 0
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target_size: 512
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use_cv2: true
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- !Permute
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to_bgr: false
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- !NormalizeImage
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is_scale: false
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mean: [123, 117, 104]
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std: [1, 1, 1]
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batch_size: 1
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