TrainReader: inputs_def: fields: ['image', 'im_info', 'im_id', 'gt_bbox', 'gt_class', 'is_crowd'] dataset: !COCODataSet image_dir: train2017 anno_path: annotations/instances_train2017.json dataset_dir: dataset/coco sample_transforms: - !DecodeImage to_rgb: true - !RandomFlipImage prob: 0.5 - !NormalizeImage is_channel_first: false is_scale: true mean: [0.485,0.456,0.406] std: [0.229, 0.224,0.225] - !ResizeImage target_size: 800 max_size: 1333 interp: 1 use_cv2: true - !Permute to_bgr: false channel_first: true batch_transforms: - !PadBatch pad_to_stride: 32 use_padded_im_info: false batch_size: 1 shuffle: true worker_num: 2 use_process: false EvalReader: inputs_def: fields: ['image', 'im_info', 'im_id', 'im_shape'] # for voc #fields: ['image', 'im_info', 'im_id', 'im_shape', 'gt_bbox', 'gt_class', 'is_difficult'] dataset: !COCODataSet image_dir: val2017 anno_path: annotations/instances_val2017.json dataset_dir: dataset/coco sample_transforms: - !DecodeImage to_rgb: true with_mixup: false - !NormalizeImage is_channel_first: false is_scale: true mean: [0.485,0.456,0.406] std: [0.229, 0.224,0.225] - !ResizeImage interp: 1 max_size: 1333 target_size: 800 use_cv2: true - !Permute channel_first: true to_bgr: false batch_transforms: - !PadBatch pad_to_stride: 32 use_padded_im_info: true batch_size: 1 shuffle: false drop_empty: false worker_num: 2 TestReader: inputs_def: # set image_shape if needed fields: ['image', 'im_info', 'im_id', 'im_shape'] dataset: !ImageFolder anno_path: annotations/instances_val2017.json sample_transforms: - !DecodeImage to_rgb: true with_mixup: false - !NormalizeImage is_channel_first: false is_scale: true mean: [0.485,0.456,0.406] std: [0.229, 0.224,0.225] - !ResizeImage interp: 1 max_size: 1333 target_size: 800 use_cv2: true - !Permute channel_first: true to_bgr: false batch_transforms: - !PadBatch pad_to_stride: 32 use_padded_im_info: true batch_size: 1 shuffle: false