forked from PulseFocusPlatform/PulseFocusPlatform
124 lines
2.7 KiB
YAML
124 lines
2.7 KiB
YAML
architecture: FaceBoxes
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pretrain_weights:
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use_gpu: true
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max_iters: 320000
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snapshot_iter: 10000
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log_iter: 20
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metric: WIDERFACE
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save_dir: output
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weights: output/faceboxes_lite/model_final
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# 1(label_class) + 1(background)
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num_classes: 2
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FaceBoxes:
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backbone: FaceBoxNet
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densities: [[2, 1, 1], [1, 1]]
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fixed_sizes: [[16., 32., 64.], [96., 128.]]
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output_decoder:
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keep_top_k: 750
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nms_threshold: 0.3
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nms_top_k: 5000
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score_threshold: 0.01
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FaceBoxNet:
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with_extra_blocks: true
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lite_edition: true
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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: [240000, 300000]
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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: 0.0005
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type: L2
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TrainReader:
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batch_size: 8
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use_process: True
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worker_num: 8
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shuffle: true
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inputs_def:
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image_shape: [3, 640, 640]
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fields: ['image', 'gt_bbox', 'gt_class']
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dataset:
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!WIDERFaceDataSet
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dataset_dir: dataset/wider_face
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anno_path: wider_face_split/wider_face_train_bbx_gt.txt
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image_dir: WIDER_train/images
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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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- !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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- !ExpandImage
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max_ratio: 4
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prob: 0.5
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- !CropImageWithDataAchorSampling
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anchor_sampler:
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- [1, 10, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.2, 0.0]
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batch_sampler:
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- [1, 50, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0]
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- [1, 50, 0.3, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0]
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- [1, 50, 0.3, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0]
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- [1, 50, 0.3, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0]
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- [1, 50, 0.3, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0]
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target_size: 640
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- !RandomInterpImage
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target_size: 640
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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: [104, 117, 123]
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std: [127.502231, 127.502231, 127.502231]
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EvalReader:
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batch_size: 1
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use_process: false
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inputs_def:
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fields: ['image', 'im_id']
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dataset:
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!WIDERFaceDataSet
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dataset_dir: dataset/wider_face
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anno_path: wider_face_split/wider_face_val_bbx_gt.txt
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image_dir: WIDER_val/images
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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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- !NormalizeImage
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is_channel_first: false
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is_scale: false
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mean: [123, 117, 104]
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std: [127.502231, 127.502231, 127.502231]
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- !Permute {}
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TestReader:
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inputs_def:
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fields: ['image', 'im_id', 'im_shape']
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dataset:
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!ImageFolder
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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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- !NormalizeImage
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is_channel_first: false
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is_scale: false
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mean: [123, 117, 104]
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std: [127.502231, 127.502231, 127.502231]
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- !Permute {}
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batch_size: 1
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