Add sparse rcnn config (#3719)

* add sparse rcnn config

* update

* update

configs/sparse_rcnn/README.md

+# Sparse R-CNN: End-to-End Object Detection with Learnable Proposals
+
+
+## Introduction
+Sparse RCNN is a purely sparse method for object detection in images.
+
+
+## Model Zoo
+
+| Backbone        | Proposals | lr schedule | Box AP | download   | config |
+| :-------------- | :-----: | :------------: | :-----: | :-----: | :-----: |
+| ResNet50-FPN | 100 | 3x |  43.0  | [download](https://paddledet.bj.bcebos.com/models/sparse_rcnn_r50_fpn_3x_pro100_coco.pdparams) | [config](./sparse_rcnn_r50_fpn_3x_pro100_coco.yml) |
+| ResNet50-FPN | 300 | 3x |  44.6  | [download](https://paddledet.bj.bcebos.com/models/sparse_rcnn_r50_fpn_3x_pro300_coco.pdparams) | [config](./sparse_rcnn_r50_fpn_3x_pro300_coco.yml) |
+
+## Citations
+```
+@misc{sun2021sparse,
+      title={Sparse R-CNN: End-to-End Object Detection with Learnable Proposals},
+      author={Peize Sun and Rufeng Zhang and Yi Jiang and Tao Kong and Chenfeng Xu and Wei Zhan and Masayoshi Tomizuka and Lei Li and Zehuan Yuan and Changhu Wang and Ping Luo},
+      year={2021},
+      eprint={2011.12450},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
+```

configs/sparse_rcnn/_base_/optimizer_3x.yml

+epoch: 36
+
+LearningRate:
+  base_lr: 0.000025
+  schedulers:
+  - !PiecewiseDecay
+    gamma: 0.1
+    milestones: [28, 34]
+  - !LinearWarmup
+    start_factor: 0.01
+    steps: 1000
+
+OptimizerBuilder:
+  clip_grad_by_norm: 1.0
+  optimizer:
+    type: AdamW
+    weight_decay: 0.0001

configs/sparse_rcnn/_base_/sparse_rcnn_r50_fpn.yml

+architecture: SparseRCNN
+pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams
+
+SparseRCNN:
+  backbone: ResNet
+  neck: FPN
+  head: SparseRCNNHead
+  postprocess: SparsePostProcess
+
+ResNet:
+  # index 0 stands for res2
+  depth: 50
+  norm_type: bn
+  freeze_at: 0
+  return_idx: [0,1,2,3]
+  num_stages: 4
+
+FPN:
+  out_channel: 256
+
+SparseRCNNHead:
+  head_hidden_dim: 256
+  head_dim_feedforward: 2048
+  nhead: 8
+  head_dropout: 0.0
+  head_cls: 1
+  head_reg: 3
+  head_dim_dynamic: 64
+  head_num_dynamic: 2
+  head_num_heads: 6
+  deep_supervision: true
+  num_proposals: 100
+  loss_func: SparseRCNNLoss
+
+SparseRCNNLoss:
+  losses: ["labels", "boxes"]
+  focal_loss_alpha: 0.25
+  focal_loss_gamma: 2.0
+  class_weight: 2.0
+  l1_weight: 5.0
+  giou_weight: 2.0
+
+SparsePostProcess:
+  num_proposals: 100

configs/sparse_rcnn/_base_/sparse_rcnn_reader.yml

+worker_num: 4
+use_process: true
+
+TrainReader:
+  sample_transforms:
+  - Decode: {}
+  - RandomResize: {target_size: [[480, 1333], [512, 1333], [544, 1333], [576, 1333], [608, 1333], [640, 1333], [672, 1333], [704, 1333], [736, 1333], [768, 1333], [800, 1333]], keep_ratio: true, interp: 1}
+  - RandomFlip: {prob: 0.5}
+  - NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
+  - Permute: {}
+  batch_transforms:
+  - PadBatch: {pad_to_stride: 32}
+  - Gt2SparseRCNNTarget: {}
+  batch_size: 4
+  shuffle: true
+  drop_last: true
+  collate_batch: false
+  use_process: true
+
+EvalReader:
+  sample_transforms:
+  - Decode: {}
+  - Resize: {interp: 1, target_size: [800, 1333], keep_ratio: True}
+  - NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
+  - Permute: {}
+  batch_transforms:
+  - PadBatch: {pad_to_stride: 32}
+  - Gt2SparseRCNNTarget: {}
+  batch_size: 1
+  shuffle: false
+  drop_last: false
+  use_process: true
+
+TestReader:
+  sample_transforms:
+  - Decode: {}
+  - Resize: {interp: 1, target_size: [800, 1333], keep_ratio: True}
+  - NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
+  - Permute: {}
+  batch_transforms:
+  - PadBatch: {pad_to_stride: 32}
+  - Gt2SparseRCNNTarget: {train: false}
+  batch_size: 1
+  shuffle: false

configs/sparse_rcnn/sparse_rcnn_r50_fpn_3x_pro100_coco.yml

+_BASE_: [
+  '../datasets/coco_detection.yml',
+  '../runtime.yml',
+  '_base_/sparse_rcnn_r50_fpn.yml',
+  '_base_/optimizer_3x.yml',
+  '_base_/sparse_rcnn_reader.yml',
+]
+
+num_classes: 80
+weights: output/sparse_rcnn_r50b_fpn_pro100/model_final

configs/sparse_rcnn/sparse_rcnn_r50_fpn_3x_pro300_coco.yml

+_BASE_: [
+  '../datasets/coco_detection.yml',
+  '../runtime.yml',
+  '_base_/sparse_rcnn_r50_fpn.yml',
+  '_base_/optimizer_3x.yml',
+  '_base_/sparse_rcnn_reader.yml',
+]
+
+num_classes: 80
+weights: output/sparse_rcnn_r50b_fpn_pro300/model_final
+
+snapshot_epoch: 1
+
+
+SparseRCNNHead:
+  num_proposals: 300
+
+SparsePostProcess:
+  num_proposals: 300