architecture: FasterRCNN train_feed: FasterRCNNTrainFeed eval_feed: FasterRCNNEvalFeed test_feed: FasterRCNNTestFeed use_gpu: true max_iters: 180000 log_smooth_window: 20 save_dir: output snapshot_iter: 10000 pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_cos_pretrained.tar metric: COCO weights: output/faster_rcnn_r50_1x/model_final FasterRCNN: backbone: ResNet rpn_head: RPNHead roi_extractor: RoIAlign bbox_head: BBoxHead bbox_assigner: BBoxAssigner ResNet: norm_type: affine_channel depth: 50 feature_maps: 4 freeze_at: 2 ResNetC5: norm_type: affine_channel RPNHead: 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] 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 use_random: true train_proposal: min_size: 0.0 nms_thresh: 0.7 pre_nms_top_n: 12000 post_nms_top_n: 2000 test_proposal: min_size: 0.0 nms_thresh: 0.7 pre_nms_top_n: 6000 post_nms_top_n: 1000 RoIAlign: resolution: 14 sampling_ratio: 0 spatial_scale: 0.0625 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 num_classes: 81 BBoxHead: head: ResNetC5 nms: keep_top_k: 100 nms_threshold: 0.5 score_threshold: 0.05 num_classes: 81 LearningRate: base_lr: 0.01 schedulers: - !PiecewiseDecay gamma: 0.1 milestones: [12000, 16000] - !LinearWarmup start_factor: 0.3333333333333333 steps: 500 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 annotation: annotations/instances_train2017.json image_dir: train2017 drop_last: false num_workers: 2 FasterRCNNEvalFeed: batch_size: 1 dataset: dataset_dir: dataset/coco annotation: annotations/instances_val2017.json image_dir: val2017 num_workers: 2 FasterRCNNTestFeed: batch_size: 1 dataset: annotation: annotations/instances_val2017.json