random_seed: 42 yolov4_config { big_anchor_shape: "[(330.35, 323.84), (556.80, 291.84), (561.23, 480.00)]" mid_anchor_shape: "[(60.69, 53.33), (113.50, 96.24), (232.00, 189.71)]" small_anchor_shape: "[(9.67, 11.85), (22.00, 20.44), (35.00, 35.56)]" box_matching_iou: 0.25 arch: "cspdarknet" nlayers: 53 arch_conv_blocks: 2 loss_loc_weight: 0.8 loss_neg_obj_weights: 100.0 loss_class_weights: 0.5 label_smoothing: 0.0 big_grid_xy_extend: 0.05 mid_grid_xy_extend: 0.1 small_grid_xy_extend: 0.2 freeze_bn: false #freeze_blocks: 0 force_relu: false } training_config { batch_size_per_gpu: 1 num_epochs: 80 enable_qat: false checkpoint_interval: 10 learning_rate { soft_start_cosine_annealing_schedule { min_learning_rate: 1e-7 max_learning_rate: 1e-4 soft_start: 0.3 } } regularizer { type: L1 weight: 3e-5 } optimizer { adam { epsilon: 1e-7 beta1: 0.9 beta2: 0.999 amsgrad: false } } pretrain_model_path: "/workspace/tlt-experiments/yolo_v4/pretrained_cspdarknet53/tlt_pretrained_object_detection_vcspdarknet53/cspdarknet_53.hdf5" } eval_config { average_precision_mode: SAMPLE batch_size: 1 matching_iou_threshold: 0.5 } nms_config { confidence_threshold: 0.4 clustering_iou_threshold: 0.5 top_k: 200 } augmentation_config { hue: 0.1 saturation: 1.5 exposure:1.5 vertical_flip:0 horizontal_flip: 0.5 jitter: 0.3 output_width: 640 output_height: 640 randomize_input_shape_period: 0 mosaic_prob: 0.5 mosaic_min_ratio:0.2 } dataset_config { data_sources: { label_directory_path: "/workspace/tlt-experiments/data/training/label_2" image_directory_path: "/workspace/tlt-experiments/data/training/image_2" } include_difficult_in_training: true target_class_mapping { key: "label1" value: "label1" } validation_data_sources: { label_directory_path: "/workspace/tlt-experiments/data/val/label" image_directory_path: "/workspace/tlt-experiments/data/val/image" } }