architecture: BlazeFace max_iters: 320000 pretrain_weights: use_gpu: true snapshot_iter: 10000 log_iter: 20 metric: WIDERFACE save_dir: output weights: output/blazeface_nas/model_final # 1(label_class) + 1(background) num_classes: 2 BlazeFace: backbone: BlazeNet output_decoder: keep_top_k: 750 nms_threshold: 0.3 nms_top_k: 5000 score_threshold: 0.01 min_sizes: [[16.,24.], [32., 48., 64., 80., 96., 128.]] use_density_prior_box: false BlazeNet: blaze_filters: [[12, 12], [12, 12, 2], [12, 12]] double_blaze_filters: [[12, 16, 24, 2], [24, 12, 24], [24, 16, 72, 2], [72, 12, 72]] with_extra_blocks: true lite_edition: false LearningRate: base_lr: 0.001 schedulers: - !PiecewiseDecay gamma: 0.1 milestones: [240000, 300000] OptimizerBuilder: optimizer: momentum: 0.0 type: RMSPropOptimizer regularizer: factor: 0.0005 type: L2 TrainReader: inputs_def: image_shape: [3, 640, 640] fields: ['image', 'gt_bbox', 'gt_class'] dataset: !WIDERFaceDataSet dataset_dir: dataset/wider_face anno_path: wider_face_split/wider_face_train_bbx_gt.txt image_dir: WIDER_train/images sample_transforms: - !DecodeImage to_rgb: true - !NormalizeBox {} - !RandomDistort brightness_lower: 0.875 brightness_upper: 1.125 is_order: true - !ExpandImage max_ratio: 4 prob: 0.5 - !CropImageWithDataAchorSampling anchor_sampler: - [1, 10, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.2, 0.0] batch_sampler: - [1, 50, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0] - [1, 50, 0.3, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0] - [1, 50, 0.3, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0] - [1, 50, 0.3, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0] - [1, 50, 0.3, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 0.0] target_size: 640 - !RandomInterpImage target_size: 640 - !RandomFlipImage is_normalized: true - !Permute {} - !NormalizeImage is_scale: false mean: [104, 117, 123] std: [127.502231, 127.502231, 127.502231] batch_size: 8 use_process: true worker_num: 8 shuffle: true EvalReader: inputs_def: fields: ['image', 'im_id'] dataset: !WIDERFaceDataSet dataset_dir: dataset/wider_face anno_path: wider_face_split/wider_face_val_bbx_gt.txt image_dir: WIDER_val/images sample_transforms: - !DecodeImage to_rgb: true - !NormalizeBox {} - !NormalizeImage is_channel_first: false is_scale: false mean: [123, 117, 104] std: [127.502231, 127.502231, 127.502231] - !Permute {} batch_size: 1 TestReader: inputs_def: fields: ['image', 'im_id', 'im_shape'] dataset: !ImageFolder use_default_label: true sample_transforms: - !DecodeImage to_rgb: true - !NormalizeImage is_channel_first: false is_scale: false mean: [123, 117, 104] std: [127.502231, 127.502231, 127.502231] - !Permute {} batch_size: 1