architecture: FasterRCNN train_feed: FasterRCNNTrainFeed eval_feed: FasterRCNNEvalFeed test_feed: FasterRCNNTestFeed max_iters: 180000 snapshot_iter: 10000 use_gpu: true log_smooth_window: 20 save_dir: output pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_vd_pretrained.tar weights: output/faster_rcnn_r101_vd_fpn_1x/model_final metric: COCO num_classes: 81 FasterRCNN: backbone: ResNet fpn: FPN rpn_head: FPNRPNHead roi_extractor: FPNRoIAlign bbox_head: BBoxHead bbox_assigner: BBoxAssigner ResNet: depth: 101 feature_maps: [2, 3, 4, 5] freeze_at: 2 norm_type: affine_channel variant: d FPN: max_level: 6 min_level: 2 num_chan: 256 spatial_scale: [0.03125, 0.0625, 0.125, 0.25] FPNRPNHead: anchor_generator: anchor_sizes: [32, 64, 128, 256, 512] aspect_ratios: [0.5, 1.0, 2.0] stride: [16.0, 16.0] variance: [1.0, 1.0, 1.0, 1.0] anchor_start_size: 32 max_level: 6 min_level: 2 num_chan: 256 rpn_target_assign: rpn_batch_size_per_im: 256 rpn_fg_fraction: 0.5 rpn_negative_overlap: 0.3 rpn_positive_overlap: 0.7 rpn_straddle_thresh: 0.0 train_proposal: min_size: 0.0 nms_thresh: 0.7 post_nms_top_n: 2000 pre_nms_top_n: 2000 test_proposal: min_size: 0.0 nms_thresh: 0.7 post_nms_top_n: 1000 pre_nms_top_n: 1000 FPNRoIAlign: canconical_level: 4 canonical_size: 224 max_level: 5 min_level: 2 box_resolution: 7 sampling_ratio: 2 BBoxAssigner: batch_size_per_im: 512 bbox_reg_weights: [0.1, 0.1, 0.2, 0.2] bg_thresh_hi: 0.5 bg_thresh_lo: 0.0 fg_fraction: 0.25 fg_thresh: 0.5 BBoxHead: head: TwoFCHead nms: keep_top_k: 100 nms_threshold: 0.5 score_threshold: 0.05 TwoFCHead: mlp_dim: 1024 LearningRate: base_lr: 0.01 schedulers: - !PiecewiseDecay gamma: 0.1 milestones: [120000, 160000] - !LinearWarmup start_factor: 0.3333333333333333 steps: 1000 OptimizerBuilder: optimizer: momentum: 0.9 type: Momentum regularizer: factor: 0.0001 type: L2 FasterRCNNTrainFeed: # batch size per device batch_size: 1 dataset: dataset_dir: dataset/coco image_dir: train2017 annotation: annotations/instances_train2017.json batch_transforms: - !PadBatch pad_to_stride: 32 num_workers: 2 FasterRCNNEvalFeed: batch_size: 1 dataset: dataset_dir: dataset/coco annotation: annotations/instances_val2017.json image_dir: val2017 batch_transforms: - !PadBatch pad_to_stride: 32 num_workers: 2 FasterRCNNTestFeed: batch_size: 1 dataset: annotation: dataset/coco/annotations/instances_val2017.json batch_transforms: - !PadBatch pad_to_stride: 32 num_workers: 2