forked from PulseFocusPlatform/PulseFocusPlatform
144 lines
3.1 KiB
YAML
144 lines
3.1 KiB
YAML
architecture: SSD
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pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/ssd_mobilenet_v1_voc.tar
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use_gpu: false
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use_xpu: true
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max_iters: 3000
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snapshot_iter: 500
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log_iter: 1
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metric: VOC
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map_type: 11point
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save_dir: output
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weights: output/ssd_mobilenet_v1_roadsign_kunlun/model_final
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num_classes: 5
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SSD:
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backbone: MobileNet
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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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MobileNet:
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norm_decay: 0.
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conv_group_scale: 1
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conv_learning_rate: 0.1
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extra_block_filters: [[256, 512], [128, 256], [128, 256], [64, 128]]
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with_extra_blocks: true
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MultiBoxHead:
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aspect_ratios: [[2.], [2., 3.], [2., 3.], [2., 3.], [2., 3.], [2., 3.]]
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base_size: 300
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flip: true
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max_ratio: 90
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max_sizes: [[], 150.0, 195.0, 240.0, 285.0, 300.0]
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min_ratio: 20
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min_sizes: [60.0, 105.0, 150.0, 195.0, 240.0, 285.0]
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offset: 0.5
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LearningRate:
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schedulers:
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- !PiecewiseDecay
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milestones: [2000, 3000, 4000, 5000]
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values: [0.0001, 0.00005, 0.000025, 0.00001, 0.000001]
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OptimizerBuilder:
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optimizer:
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momentum: 0.0
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type: RMSPropOptimizer
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regularizer:
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factor: 0.00005
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type: L2
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TrainReader:
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inputs_def:
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image_shape: [3, 300, 300]
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fields: ['image', 'gt_bbox', 'gt_class']
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dataset:
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!VOCDataSet
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anno_path: train.txt
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dataset_dir: dataset/roadsign_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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- !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: [127.5, 127.5, 127.5]
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- !RandomCrop
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allow_no_crop: false
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- !NormalizeBox {}
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- !ResizeImage
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interp: 1
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target_size: 300
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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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- !NormalizeImage
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is_scale: false
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mean: [127.5, 127.5, 127.5]
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std: [127.502231, 127.502231, 127.502231]
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batch_size: 32
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shuffle: true
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drop_last: true
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worker_num: 8
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bufsize: 16
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use_process: false
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EvalReader:
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inputs_def:
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image_shape: [3, 300, 300]
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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: valid.txt
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dataset_dir: dataset/roadsign_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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- !NormalizeBox {}
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- !ResizeImage
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interp: 1
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target_size: 300
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use_cv2: false
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- !Permute {}
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- !NormalizeImage
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is_scale: false
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mean: [127.5, 127.5, 127.5]
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std: [127.502231, 127.502231, 127.502231]
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batch_size: 32
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worker_num: 8
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bufsize: 16
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use_process: false
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TestReader:
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inputs_def:
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image_shape: [3,300,300]
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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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- !ResizeImage
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interp: 1
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max_size: 0
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target_size: 300
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use_cv2: true
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- !Permute {}
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- !NormalizeImage
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is_scale: false
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mean: [127.5, 127.5, 127.5]
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std: [127.502231, 127.502231, 127.502231]
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batch_size: 1
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