TrainReader: inputs_def: fields: ['image', 'gt_bbox', 'gt_class', 'gt_score'] num_max_boxes: 50 sample_transforms: - !DecodeImage to_rgb: True with_mixup: True - !MixupImage alpha: 1.5 beta: 1.5 - !ColorDistort {} - !RandomExpand fill_value: [123.675, 116.28, 103.53] - !RandomCrop {} - !RandomFlipImage is_normalized: false - !NormalizeBox {} - !PadBox num_max_boxes: 50 - !BboxXYXY2XYWH {} batch_transforms: - !RandomShape sizes: [320, 352, 384, 416, 448, 480, 512, 544, 576, 608] random_inter: True - !NormalizeImage mean: [0.485, 0.456, 0.406] std: [0.229, 0.224, 0.225] is_scale: True is_channel_first: false - !Permute to_bgr: false channel_first: True # Gt2YoloTarget is only used when use_fine_grained_loss set as true, # this operator will be deleted automatically if use_fine_grained_loss # is set as false - !Gt2YoloTarget anchor_masks: [[6, 7, 8], [3, 4, 5], [0, 1, 2]] anchors: [[10, 13], [16, 30], [33, 23], [30, 61], [62, 45], [59, 119], [116, 90], [156, 198], [373, 326]] downsample_ratios: [32, 16, 8] batch_size: 8 shuffle: true mixup_epoch: 250 drop_last: true worker_num: 4 bufsize: 4 use_process: true EvalReader: inputs_def: fields: ['image', 'im_size', 'im_id'] num_max_boxes: 50 sample_transforms: - !DecodeImage to_rgb: True - !ResizeImage target_size: 608 interp: 2 - !NormalizeImage mean: [0.485, 0.456, 0.406] std: [0.229, 0.224, 0.225] is_scale: True is_channel_first: false - !PadBox num_max_boxes: 50 - !Permute to_bgr: false channel_first: True batch_size: 1 drop_empty: false worker_num: 8 bufsize: 16 TestReader: inputs_def: image_shape: [3, 608, 608] fields: ['image', 'im_size', 'im_id'] sample_transforms: - !DecodeImage to_rgb: True - !ResizeImage target_size: 608 interp: 2 - !NormalizeImage mean: [0.485, 0.456, 0.406] std: [0.229, 0.224, 0.225] is_scale: True is_channel_first: false - !Permute to_bgr: false channel_first: True batch_size: 1