add reppoints config and model without gn (#2058)

* add reppoints without gn

* fix

configs/reppoints/README.md

@@ -32,25 +32,26 @@ Another feature of this repo is the demonstration of an `anchor-free detector`,
 
 The results on COCO 2017val are shown in the table below.
 
-| Method | Backbone | Anchor | convert func | Lr schd | box AP | Download |
-| :----: | :------: | :-------: | :------: | :-----: | :----: | :------: |
-| BBox | R-50-FPN | single | -    | 1x      | 36.3|[model](https://drive.google.com/open?id=1TaVAFGZP2i7RwtlQjy3LBH1WI-YRH774) |
-| BBox | R-50-FPN | none     | -    | 1x      | 37.3| [model](https://drive.google.com/open?id=1hpfu-I7gtZnIb0NU2WvUvaZz_dm-THuZ) |
-| RepPoints | R-50-FPN | none     | partial MinMax | 1x      | 38.1| [model](https://drive.google.com/open?id=11zFtdKH-QGz_zH7vlcIih6FQAjV84CWc) |
-| RepPoints | R-50-FPN | none     | MinMax | 1x      | 38.2| [model](https://drive.google.com/open?id=1Cg9818dpkL-9qjmYdkhrY_BRiQFjV4xu)  |
-| RepPoints | R-50-FPN | none     | moment | 1x      | 38.2| [model](https://drive.google.com/open?id=1rQg-lE-5nuqO1bt6okeYkti4Q-EaBsu_) |
-| RepPoints | R-50-FPN | none     | moment | 2x      | 38.6| [model](https://drive.google.com/open?id=1TfR-5geVviKhRoXL9JP6cG3fkN2itbBU) |
-| RepPoints | R-50-FPN | none     | moment | 2x (ms train)   | 40.8| [model](https://drive.google.com/open?id=1oaHTIaP51oB5HJ6GWV3WYK19lMm9iJO6) |
-| RepPoints | R-50-FPN | none     | moment | 2x (ms train&ms test)   | 42.2|          |
-| RepPoints | R-101-FPN | none   | moment | 2x   | 40.3| [model](https://drive.google.com/open?id=1BAmGeUQ_zVQi2u7rgOuPQem2EjXDLgWm) |
-| RepPoints | R-101-FPN | none   | moment | 2x (ms train)   | 42.3| [model](https://drive.google.com/open?id=14Lf0p4fXElXaxFu8stk3hek3bY8tNENX) |
-| RepPoints | R-101-FPN | none   | moment | 2x (ms train&ms test)   | 44.1|          |
-| RepPoints | R-101-FPN-DCN | none   | moment | 2x   | 43.0| [model](https://drive.google.com/open?id=1hpptxpb4QtNuB-HnV5wHbDltPHhlYq4z) |
-| RepPoints | R-101-FPN-DCN | none   | moment | 2x (ms train)   | 44.8| [model](https://drive.google.com/open?id=1fsTckK99HYjOURwcFeHfy5JRRtsCajfX) |
-| RepPoints | R-101-FPN-DCN | none   | moment | 2x (ms train&ms test)   | 46.4|          |
-| RepPoints | X-101-FPN-DCN | none   | moment | 2x   | 44.5| [model](https://drive.google.com/open?id=1Y8vqaqU88-FEqqwl6Zb9exD5O246yrMR) |
-| RepPoints | X-101-FPN-DCN | none   | moment | 2x (ms train)   | 45.6| [model](https://drive.google.com/open?id=1nr9gcVWxzeakbfPC6ON9yvKOuLzj_RrJ) |
-| RepPoints | X-101-FPN-DCN | none   | moment | 2x (ms train&ms test)   | 46.8|          |
+| Method | Backbone | GN | Anchor | convert func | Lr schd | box AP | Download |
+| :----: | :------: | :-------: | :-------: | :------: | :-----: | :----: | :------: |
+| BBox | R-50-FPN | Y | single | -    | 1x      | 36.3|[model](https://drive.google.com/open?id=1TaVAFGZP2i7RwtlQjy3LBH1WI-YRH774) |
+| BBox | R-50-FPN | Y | none     | -    | 1x      | 37.3| [model](https://drive.google.com/open?id=1hpfu-I7gtZnIb0NU2WvUvaZz_dm-THuZ) |
+| RepPoints | R-50-FPN | Y | none     | partial MinMax | 1x      | 38.1| [model](https://drive.google.com/open?id=11zFtdKH-QGz_zH7vlcIih6FQAjV84CWc) |
+| RepPoints | R-50-FPN | Y | none     | MinMax | 1x      | 38.2| [model](https://drive.google.com/open?id=1Cg9818dpkL-9qjmYdkhrY_BRiQFjV4xu)  |
+| RepPoints | R-50-FPN | Y | none     | moment | 1x      | 38.2| [model](https://drive.google.com/open?id=1rQg-lE-5nuqO1bt6okeYkti4Q-EaBsu_) |
+| RepPoints | R-50-FPN | N | none     | moment | 1x      | 36.8| [model](https://open-mmlab.s3.ap-northeast-2.amazonaws.com/mmdetection/models/reppoints/reppoints_moment_r50_no_gn_fpn_1x-66db098e.pth) |
+| RepPoints | R-50-FPN | Y | none     | moment | 2x      | 38.6| [model](https://drive.google.com/open?id=1TfR-5geVviKhRoXL9JP6cG3fkN2itbBU) |
+| RepPoints | R-50-FPN | Y | none     | moment | 2x (ms train)   | 40.8| [model](https://drive.google.com/open?id=1oaHTIaP51oB5HJ6GWV3WYK19lMm9iJO6) |
+| RepPoints | R-50-FPN | Y | none     | moment | 2x (ms train&ms test)   | 42.2|          |
+| RepPoints | R-101-FPN | Y | none   | moment | 2x   | 40.3| [model](https://drive.google.com/open?id=1BAmGeUQ_zVQi2u7rgOuPQem2EjXDLgWm) |
+| RepPoints | R-101-FPN | Y | none   | moment | 2x (ms train)   | 42.3| [model](https://drive.google.com/open?id=14Lf0p4fXElXaxFu8stk3hek3bY8tNENX) |
+| RepPoints | R-101-FPN | Y | none   | moment | 2x (ms train&ms test)   | 44.1|          |
+| RepPoints | R-101-FPN-DCN | Y | none   | moment | 2x   | 43.0| [model](https://drive.google.com/open?id=1hpptxpb4QtNuB-HnV5wHbDltPHhlYq4z) |
+| RepPoints | R-101-FPN-DCN | Y | none   | moment | 2x (ms train)   | 44.8| [model](https://drive.google.com/open?id=1fsTckK99HYjOURwcFeHfy5JRRtsCajfX) |
+| RepPoints | R-101-FPN-DCN | Y | none   | moment | 2x (ms train&ms test)   | 46.4|          |
+| RepPoints | X-101-FPN-DCN | Y | none   | moment | 2x   | 44.5| [model](https://drive.google.com/open?id=1Y8vqaqU88-FEqqwl6Zb9exD5O246yrMR) |
+| RepPoints | X-101-FPN-DCN | Y | none   | moment | 2x (ms train)   | 45.6| [model](https://drive.google.com/open?id=1nr9gcVWxzeakbfPC6ON9yvKOuLzj_RrJ) |
+| RepPoints | X-101-FPN-DCN | Y | none   | moment | 2x (ms train&ms test)   | 46.8|          |
 
 **Notes:**
 

configs/reppoints/reppoints_moment_r50_no_gn_fpn_1x.py

+# model settings
+model = dict(
+    type='RepPointsDetector',
+    pretrained='torchvision://resnet50',
+    backbone=dict(
+        type='ResNet',
+        depth=50,
+        num_stages=4,
+        out_indices=(0, 1, 2, 3),
+        frozen_stages=1,
+        style='pytorch'),
+    neck=dict(
+        type='FPN',
+        in_channels=[256, 512, 1024, 2048],
+        out_channels=256,
+        start_level=1,
+        add_extra_convs=True,
+        num_outs=5),
+    bbox_head=dict(
+        type='RepPointsHead',
+        num_classes=81,
+        in_channels=256,
+        feat_channels=256,
+        point_feat_channels=256,
+        stacked_convs=3,
+        num_points=9,
+        gradient_mul=0.1,
+        point_strides=[8, 16, 32, 64, 128],
+        point_base_scale=4,
+        loss_cls=dict(
+            type='FocalLoss',
+            use_sigmoid=True,
+            gamma=2.0,
+            alpha=0.25,
+            loss_weight=1.0),
+        loss_bbox_init=dict(type='SmoothL1Loss', beta=0.11, loss_weight=0.5),
+        loss_bbox_refine=dict(type='SmoothL1Loss', beta=0.11, loss_weight=1.0),
+        transform_method='moment'))
+# training and testing settings
+train_cfg = dict(
+    init=dict(
+        assigner=dict(type='PointAssigner', scale=4, pos_num=1),
+        allowed_border=-1,
+        pos_weight=-1,
+        debug=False),
+    refine=dict(
+        assigner=dict(
+            type='MaxIoUAssigner',
+            pos_iou_thr=0.5,
+            neg_iou_thr=0.4,
+            min_pos_iou=0,
+            ignore_iof_thr=-1),
+        allowed_border=-1,
+        pos_weight=-1,
+        debug=False))
+test_cfg = dict(
+    nms_pre=1000,
+    min_bbox_size=0,
+    score_thr=0.05,
+    nms=dict(type='nms', iou_thr=0.5),
+    max_per_img=100)
+# dataset settings
+dataset_type = 'CocoDataset'
+data_root = 'data/coco/'
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(type='LoadAnnotations', with_bbox=True),
+    dict(type='Resize', img_scale=(1333, 800), keep_ratio=True),
+    dict(type='RandomFlip', flip_ratio=0.5),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='Pad', size_divisor=32),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']),
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(1333, 800),
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(type='Normalize', **img_norm_cfg),
+            dict(type='Pad', size_divisor=32),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img']),
+        ])
+]
+data = dict(
+    imgs_per_gpu=2,
+    workers_per_gpu=2,
+    train=dict(
+        type=dataset_type,
+        ann_file=data_root + 'annotations/instances_train2017.json',
+        img_prefix=data_root + 'train2017/',
+        pipeline=train_pipeline),
+    val=dict(
+        type=dataset_type,
+        ann_file=data_root + 'annotations/instances_val2017.json',
+        img_prefix=data_root + 'val2017/',
+        pipeline=test_pipeline),
+    test=dict(
+        type=dataset_type,
+        ann_file=data_root + 'annotations/instances_val2017.json',
+        img_prefix=data_root + 'val2017/',
+        pipeline=test_pipeline))
+# optimizer
+optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)
+optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2))
+# learning policy
+lr_config = dict(
+    policy='step',
+    warmup='linear',
+    warmup_iters=500,
+    warmup_ratio=1.0 / 3,
+    step=[8, 11])
+checkpoint_config = dict(interval=1)
+# yapf:disable
+log_config = dict(
+    interval=50,
+    hooks=[
+        dict(type='TextLoggerHook'),
+        # dict(type='TensorboardLoggerHook')
+    ])
+# yapf:enable
+# runtime settings
+total_epochs = 12
+dist_params = dict(backend='nccl')
+log_level = 'INFO'
+work_dir = './work_dirs/reppoints_moment_r50_no_gn_fpn_1x'
+load_from = None
+resume_from = None
+auto_resume = True
+workflow = [('train', 1)]