add C4 benchmarks (#651)

* use_sigmoid_cls -> cls_sigmoid_loss; use_focal_loss -> cls_focal_loss

* fix flake8 error

* cls_sigmoid_loss - > use_sigmoid_cls

* rename c4 configs

* update model zoo with c4 benchmark

* reorder c4 benchmarks

* update model zoo

configs/cascade_mask_rcnn_r50_c4_1x.py → configs/cascade_mask_rcnn_r50_caffe_c4_1x.py

@@ -230,7 +230,7 @@ log_config = dict(
 total_epochs = 12
 dist_params = dict(backend='nccl')
 log_level = 'INFO'
-work_dir = './work_dirs/cascade_mask_rcnn_r50_c4_1x'
+work_dir = './work_dirs/cascade_mask_rcnn_r50_caffe_c4_1x'
 load_from = None
 resume_from = None
 workflow = [('train', 1)]

configs/fast_mask_rcnn_r50_caffe_c4_1x.py

+# model settings
+norm_cfg = dict(type='BN', requires_grad=False)
+model = dict(
+    type='FastRCNN',
+    pretrained='open-mmlab://resnet50_caffe',
+    backbone=dict(
+        type='ResNet',
+        depth=50,
+        num_stages=3,
+        strides=(1, 2, 2),
+        dilations=(1, 1, 1),
+        out_indices=(2, ),
+        frozen_stages=1,
+        norm_cfg=norm_cfg,
+        norm_eval=True,
+        style='caffe'),
+    shared_head=dict(
+        type='ResLayer',
+        depth=50,
+        stage=3,
+        stride=2,
+        dilation=1,
+        style='caffe',
+        norm_cfg=norm_cfg,
+        norm_eval=True),
+    bbox_roi_extractor=dict(
+        type='SingleRoIExtractor',
+        roi_layer=dict(type='RoIAlign', out_size=14, sample_num=2),
+        out_channels=1024,
+        featmap_strides=[16]),
+    bbox_head=dict(
+        type='BBoxHead',
+        with_avg_pool=True,
+        roi_feat_size=7,
+        in_channels=2048,
+        num_classes=81,
+        target_means=[0., 0., 0., 0.],
+        target_stds=[0.1, 0.1, 0.2, 0.2],
+        reg_class_agnostic=False),
+    mask_roi_extractor=None,
+    mask_head=dict(
+        type='FCNMaskHead',
+        num_convs=0,
+        in_channels=2048,
+        conv_out_channels=256,
+        num_classes=81))
+# model training and testing settings
+train_cfg = dict(
+    rcnn=dict(
+        assigner=dict(
+            type='MaxIoUAssigner',
+            pos_iou_thr=0.5,
+            neg_iou_thr=0.5,
+            min_pos_iou=0.5,
+            ignore_iof_thr=-1),
+        sampler=dict(
+            type='RandomSampler',
+            num=512,
+            pos_fraction=0.25,
+            neg_pos_ub=-1,
+            add_gt_as_proposals=True),
+        mask_size=14,
+        pos_weight=-1,
+        debug=False))
+test_cfg = dict(
+    rcnn=dict(
+        score_thr=0.05,
+        nms=dict(type='nms', iou_thr=0.5),
+        max_per_img=100,
+        mask_thr_binary=0.5))
+# dataset settings
+dataset_type = 'CocoDataset'
+data_root = 'data/coco/'
+img_norm_cfg = dict(
+    mean=[102.9801, 115.9465, 122.7717], std=[1.0, 1.0, 1.0], to_rgb=False)
+data = dict(
+    imgs_per_gpu=1,
+    workers_per_gpu=2,
+    train=dict(
+        type=dataset_type,
+        ann_file=data_root + 'annotations/instances_train2017.json',
+        img_prefix=data_root + 'train2017/',
+        img_scale=(1333, 800),
+        img_norm_cfg=img_norm_cfg,
+        size_divisor=32,
+        proposal_file=data_root + 'proposals/rpn_r50_c4_1x_train2017.pkl',
+        flip_ratio=0.5,
+        with_mask=True,
+        with_crowd=True,
+        with_label=True),
+    val=dict(
+        type=dataset_type,
+        ann_file=data_root + 'annotations/instances_val2017.json',
+        img_prefix=data_root + 'val2017/',
+        img_scale=(1333, 800),
+        img_norm_cfg=img_norm_cfg,
+        size_divisor=32,
+        proposal_file=data_root + 'proposals/rpn_r50_c4_1x_val2017.pkl',
+        flip_ratio=0,
+        with_mask=True,
+        with_crowd=True,
+        with_label=True),
+    test=dict(
+        type=dataset_type,
+        ann_file=data_root + 'annotations/instances_val2017.json',
+        img_prefix=data_root + 'val2017/',
+        img_scale=(1333, 800),
+        img_norm_cfg=img_norm_cfg,
+        size_divisor=32,
+        proposal_file=data_root + 'proposals/rpn_r50_c4_1x_val2017.pkl',
+        flip_ratio=0,
+        with_mask=False,
+        with_label=False,
+        test_mode=True))
+# 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/fast_mask_rcnn_r50_caffe_c4_1x'
+load_from = None
+resume_from = None
+workflow = [('train', 1)]

configs/fast_rcnn_r50_c4_1x.py → configs/fast_rcnn_r50_caffe_c4_1x.py

@@ -83,8 +83,8 @@ data = dict(
         img_prefix=data_root + 'val2017/',
         img_scale=(1333, 800),
         img_norm_cfg=img_norm_cfg,
-        proposal_file=data_root + 'proposals/rpn_r50_c4_1x_val2017.pkl',
         size_divisor=32,
+        proposal_file=data_root + 'proposals/rpn_r50_c4_1x_val2017.pkl',
         flip_ratio=0,
         with_mask=False,
         with_crowd=True,
@@ -124,7 +124,7 @@ log_config = dict(
 total_epochs = 12
 dist_params = dict(backend='nccl')
 log_level = 'INFO'
-work_dir = './work_dirs/fast_rcnn_r50_c4_1x'
+work_dir = './work_dirs/fast_rcnn_r50_caffe_c4_1x'
 load_from = None
 resume_from = None
 workflow = [('train', 1)]

configs/faster_rcnn_r50_c4_1x.py → configs/faster_rcnn_r50_caffe_c4_1x.py

@@ -162,7 +162,7 @@ log_config = dict(
 total_epochs = 12
 dist_params = dict(backend='nccl')
 log_level = 'INFO'
-work_dir = './work_dirs/faster_rcnn_r50_c4_1x'
+work_dir = './work_dirs/faster_rcnn_r50_caffe_c4_1x'
 load_from = None
 resume_from = None
 workflow = [('train', 1)]

configs/mask_rcnn_r50_c4_1x.py → configs/mask_rcnn_r50_caffe_c4_1x.py

@@ -173,7 +173,7 @@ log_config = dict(
 total_epochs = 12
 dist_params = dict(backend='nccl')
 log_level = 'INFO'
-work_dir = './work_dirs/mask_rcnn_r50_c4_1x'
+work_dir = './work_dirs/mask_rcnn_r50_caffe_c4_1x'
 load_from = None
 resume_from = None
 workflow = [('train', 1)]

configs/rpn_r50_c4_1x.py → configs/rpn_r50_caffe_c4_1x.py

@@ -115,7 +115,7 @@ log_config = dict(
 total_epochs = 12
 dist_params = dict(backend='nccl')
 log_level = 'INFO'
-work_dir = './work_dirs/rpn_r50_c4_1x'
+work_dir = './work_dirs/rpn_r50_caffe_c4_1x'
 load_from = None
 resume_from = None
 workflow = [('train', 1)]