Merge pull request #2 from airctic/update-to-mmdet-2.16.0

update configs to mmdet 2.16.0
airctic · Sep 13, 2021 · 9f527e1 · 9f527e1
2 parents 5c2e320 + 1e250b3
commit 9f527e1
Show file tree

Hide file tree

Showing 472 changed files with 13,199 additions and 918 deletions.
diff --git a/configs/_base_/datasets/cityscapes_detection.py b/configs/_base_/datasets/cityscapes_detection.py
@@ -1,3 +1,4 @@
+# dataset settings
 dataset_type = 'CityscapesDataset'
 data_root = 'data/cityscapes/'
 img_norm_cfg = dict(

diff --git a/configs/_base_/datasets/cityscapes_instance.py b/configs/_base_/datasets/cityscapes_instance.py
@@ -1,3 +1,4 @@
+# dataset settings
 dataset_type = 'CityscapesDataset'
 data_root = 'data/cityscapes/'
 img_norm_cfg = dict(

diff --git a/configs/_base_/datasets/coco_detection.py b/configs/_base_/datasets/coco_detection.py
@@ -1,3 +1,4 @@
+# dataset settings
 dataset_type = 'CocoDataset'
 data_root = 'data/coco/'
 img_norm_cfg = dict(

diff --git a/configs/_base_/datasets/coco_instance.py b/configs/_base_/datasets/coco_instance.py
@@ -1,3 +1,4 @@
+# dataset settings
 dataset_type = 'CocoDataset'
 data_root = 'data/coco/'
 img_norm_cfg = dict(

diff --git a/configs/_base_/datasets/coco_instance_semantic.py b/configs/_base_/datasets/coco_instance_semantic.py
@@ -1,3 +1,4 @@
+# dataset settings
 dataset_type = 'CocoDataset'
 data_root = 'data/coco/'
 img_norm_cfg = dict(

diff --git a/configs/_base_/datasets/coco_panoptic.py b/configs/_base_/datasets/coco_panoptic.py
@@ -0,0 +1,59 @@
+# dataset settings
+dataset_type = 'CocoPanopticDataset'
+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='LoadPanopticAnnotations',
+        with_bbox=True,
+        with_mask=True,
+        with_seg=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='SegRescale', scale_factor=1 / 4),
+    dict(type='DefaultFormatBundle'),
+    dict(
+        type='Collect',
+        keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks', 'gt_semantic_seg']),
+]
+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(
+    samples_per_gpu=2,
+    workers_per_gpu=2,
+    train=dict(
+        type=dataset_type,
+        ann_file=data_root + 'annotations/panoptic_train2017.json',
+        img_prefix=data_root + 'train2017/',
+        seg_prefix=data_root + 'annotations/panoptic_train2017/',
+        pipeline=train_pipeline),
+    val=dict(
+        type=dataset_type,
+        ann_file=data_root + 'annotations/panoptic_val2017.json',
+        img_prefix=data_root + 'val2017/',
+        seg_prefix=data_root + 'annotations/panoptic_val2017/',
+        pipeline=test_pipeline),
+    test=dict(
+        type=dataset_type,
+        ann_file=data_root + 'annotations/panoptic_val2017.json',
+        img_prefix=data_root + 'val2017/',
+        seg_prefix=data_root + 'annotations/panoptic_val2017/',
+        pipeline=test_pipeline))
+evaluation = dict(interval=1, metric=['PQ'])
diff --git a/configs/_base_/datasets/lvis_v0.5_instance.py b/configs/_base_/datasets/lvis_v0.5_instance.py
@@ -1,3 +1,4 @@
+# dataset settings
 _base_ = 'coco_instance.py'
 dataset_type = 'LVISV05Dataset'
 data_root = 'data/lvis_v0.5/'

diff --git a/configs/_base_/datasets/lvis_v1_instance.py b/configs/_base_/datasets/lvis_v1_instance.py
@@ -1,3 +1,4 @@
+# dataset settings
 _base_ = 'coco_instance.py'
 dataset_type = 'LVISV1Dataset'
 data_root = 'data/lvis_v1/'

diff --git a/configs/_base_/models/cascade_mask_rcnn_r50_fpn.py b/configs/_base_/models/cascade_mask_rcnn_r50_fpn.py
@@ -1,7 +1,6 @@
 # model settings
 model = dict(
     type='CascadeRCNN',
-    pretrained='torchvision://resnet50',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -10,7 +9,8 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         norm_eval=True,
-        style='pytorch'),
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
     neck=dict(
         type='FPN',
         in_channels=[256, 512, 1024, 2048],

diff --git a/configs/_base_/models/cascade_rcnn_r50_fpn.py b/configs/_base_/models/cascade_rcnn_r50_fpn.py
@@ -1,7 +1,6 @@
 # model settings
 model = dict(
     type='CascadeRCNN',
-    pretrained='torchvision://resnet50',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -10,7 +9,8 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         norm_eval=True,
-        style='pytorch'),
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
     neck=dict(
         type='FPN',
         in_channels=[256, 512, 1024, 2048],

diff --git a/configs/_base_/models/fast_rcnn_r50_fpn.py b/configs/_base_/models/fast_rcnn_r50_fpn.py
@@ -1,7 +1,6 @@
 # model settings
 model = dict(
     type='FastRCNN',
-    pretrained='torchvision://resnet50',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -10,7 +9,8 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         norm_eval=True,
-        style='pytorch'),
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
     neck=dict(
         type='FPN',
         in_channels=[256, 512, 1024, 2048],

diff --git a/configs/_base_/models/faster_rcnn_r50_caffe_c4.py b/configs/_base_/models/faster_rcnn_r50_caffe_c4.py
@@ -2,7 +2,6 @@
 norm_cfg = dict(type='BN', requires_grad=False)
 model = dict(
     type='FasterRCNN',
-    pretrained='open-mmlab://detectron2/resnet50_caffe',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -13,7 +12,10 @@
         frozen_stages=1,
         norm_cfg=norm_cfg,
         norm_eval=True,
-        style='caffe'),
+        style='caffe',
+        init_cfg=dict(
+            type='Pretrained',
+            checkpoint='open-mmlab://detectron2/resnet50_caffe')),
     rpn_head=dict(
         type='RPNHead',
         in_channels=1024,

diff --git a/configs/_base_/models/faster_rcnn_r50_caffe_dc5.py b/configs/_base_/models/faster_rcnn_r50_caffe_dc5.py
@@ -2,7 +2,6 @@
 norm_cfg = dict(type='BN', requires_grad=False)
 model = dict(
     type='FasterRCNN',
-    pretrained='open-mmlab://detectron2/resnet50_caffe',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -13,7 +12,10 @@
         frozen_stages=1,
         norm_cfg=norm_cfg,
         norm_eval=True,
-        style='caffe'),
+        style='caffe',
+        init_cfg=dict(
+            type='Pretrained',
+            checkpoint='open-mmlab://detectron2/resnet50_caffe')),
     rpn_head=dict(
         type='RPNHead',
         in_channels=2048,

diff --git a/configs/_base_/models/faster_rcnn_r50_fpn.py b/configs/_base_/models/faster_rcnn_r50_fpn.py
@@ -1,6 +1,6 @@
+# model settings
 model = dict(
     type='FasterRCNN',
-    pretrained='torchvision://resnet50',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -9,7 +9,8 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         norm_eval=True,
-        style='pytorch'),
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
     neck=dict(
         type='FPN',
         in_channels=[256, 512, 1024, 2048],

diff --git a/configs/_base_/models/mask_rcnn_r50_caffe_c4.py b/configs/_base_/models/mask_rcnn_r50_caffe_c4.py
@@ -2,7 +2,6 @@
 norm_cfg = dict(type='BN', requires_grad=False)
 model = dict(
     type='MaskRCNN',
-    pretrained='open-mmlab://detectron2/resnet50_caffe',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -13,7 +12,10 @@
         frozen_stages=1,
         norm_cfg=norm_cfg,
         norm_eval=True,
-        style='caffe'),
+        style='caffe',
+        init_cfg=dict(
+            type='Pretrained',
+            checkpoint='open-mmlab://detectron2/resnet50_caffe')),
     rpn_head=dict(
         type='RPNHead',
         in_channels=1024,

diff --git a/configs/_base_/models/mask_rcnn_r50_fpn.py b/configs/_base_/models/mask_rcnn_r50_fpn.py
@@ -1,7 +1,6 @@
 # model settings
 model = dict(
     type='MaskRCNN',
-    pretrained='torchvision://resnet50',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -10,7 +9,8 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         norm_eval=True,
-        style='pytorch'),
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
     neck=dict(
         type='FPN',
         in_channels=[256, 512, 1024, 2048],

diff --git a/configs/_base_/models/retinanet_r50_fpn.py b/configs/_base_/models/retinanet_r50_fpn.py
@@ -1,7 +1,6 @@
 # model settings
 model = dict(
     type='RetinaNet',
-    pretrained='torchvision://resnet50',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -10,7 +9,8 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         norm_eval=True,
-        style='pytorch'),
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
     neck=dict(
         type='FPN',
         in_channels=[256, 512, 1024, 2048],
@@ -41,7 +41,7 @@
             alpha=0.25,
             loss_weight=1.0),
         loss_bbox=dict(type='L1Loss', loss_weight=1.0)),
-    # training and testing settings
+    # model training and testing settings
     train_cfg=dict(
         assigner=dict(
             type='MaxIoUAssigner',

diff --git a/configs/_base_/models/rpn_r50_caffe_c4.py b/configs/_base_/models/rpn_r50_caffe_c4.py
@@ -1,7 +1,6 @@
 # model settings
 model = dict(
     type='RPN',
-    pretrained='open-mmlab://detectron2/resnet50_caffe',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -12,7 +11,10 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=False),
         norm_eval=True,
-        style='caffe'),
+        style='caffe',
+        init_cfg=dict(
+            type='Pretrained',
+            checkpoint='open-mmlab://detectron2/resnet50_caffe')),
     neck=None,
     rpn_head=dict(
         type='RPNHead',

diff --git a/configs/_base_/models/rpn_r50_fpn.py b/configs/_base_/models/rpn_r50_fpn.py
@@ -1,8 +1,6 @@
 # model settings
-
 model = dict(
     type='RPN',
-    pretrained='torchvision://resnet50',
     backbone=dict(
         type='ResNet',
         depth=50,
@@ -11,7 +9,8 @@
         frozen_stages=1,
         norm_cfg=dict(type='BN', requires_grad=True),
         norm_eval=True,
-        style='pytorch'),
+        style='pytorch',
+        init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')),
     neck=dict(
         type='FPN',
         in_channels=[256, 512, 1024, 2048],

diff --git a/configs/_base_/models/ssd300.py b/configs/_base_/models/ssd300.py
@@ -2,17 +2,22 @@
 input_size = 300
 model = dict(
     type='SingleStageDetector',
-    pretrained='open-mmlab://vgg16_caffe',
     backbone=dict(
         type='SSDVGG',
-        input_size=input_size,
         depth=16,
         with_last_pool=False,
         ceil_mode=True,
         out_indices=(3, 4),
         out_feature_indices=(22, 34),
+        init_cfg=dict(
+            type='Pretrained', checkpoint='open-mmlab://vgg16_caffe')),
+    neck=dict(
+        type='SSDNeck',
+        in_channels=(512, 1024),
+        out_channels=(512, 1024, 512, 256, 256, 256),
+        level_strides=(2, 2, 1, 1),
+        level_paddings=(1, 1, 0, 0),
         l2_norm_scale=20),
-    neck=None,
     bbox_head=dict(
         type='SSDHead',
         in_channels=(512, 1024, 512, 256, 256, 256),
@@ -28,6 +33,7 @@
             type='DeltaXYWHBBoxCoder',
             target_means=[.0, .0, .0, .0],
             target_stds=[0.1, 0.1, 0.2, 0.2])),
+    # model training and testing settings
     train_cfg=dict(
         assigner=dict(
             type='MaxIoUAssigner',
@@ -42,6 +48,7 @@
         neg_pos_ratio=3,
         debug=False),
     test_cfg=dict(
+        nms_pre=1000,
         nms=dict(type='nms', iou_threshold=0.45),
         min_bbox_size=0,
         score_thr=0.02,

diff --git a/configs/albu_example/README.md b/configs/albu_example/README.md
@@ -1,6 +1,6 @@
 # Albu Example
 
-[OTHERS]
+<!-- [OTHERS] -->
 
 ```
 @article{2018arXiv180906839B,
@@ -16,4 +16,4 @@
 
 | Backbone  | Style   | Lr schd | Mem (GB) | Inf time (fps) | box AP | mask AP | Config | Download |
 |:---------:|:-------:|:-------:|:--------:|:--------------:|:------:|:-------:|:------:|:--------:|
-| R-50      | pytorch | 1x      | 4.4      | 16.6           |  38.0  | 34.5    |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/albu_example/mask_rcnn_r50_fpn_albu_1x_coco.py) | [model](http://download.openmmlab.com/mmdetection/v2.0/albu_example/mask_rcnn_r50_fpn_albu_1x_coco/mask_rcnn_r50_fpn_albu_1x_coco_20200208-ab203bcd.pth) &#124; [log](http://download.openmmlab.com/mmdetection/v2.0/albu_example/mask_rcnn_r50_fpn_albu_1x_coco/mask_rcnn_r50_fpn_albu_1x_coco_20200208_225520.log.json) |
+| R-50      | pytorch | 1x      | 4.4      | 16.6           |  38.0  | 34.5    |[config](https://github.com/open-mmlab/mmdetection/tree/master/configs/albu_example/mask_rcnn_r50_fpn_albu_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/albu_example/mask_rcnn_r50_fpn_albu_1x_coco/mask_rcnn_r50_fpn_albu_1x_coco_20200208-ab203bcd.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/albu_example/mask_rcnn_r50_fpn_albu_1x_coco/mask_rcnn_r50_fpn_albu_1x_coco_20200208_225520.log.json) |
diff --git a/configs/atss/README.md b/configs/atss/README.md
@@ -2,7 +2,7 @@
 
 ## Introduction
 
-[ALGORITHM]
+<!-- [ALGORITHM] -->
 
 ```latex
 @article{zhang2019bridging,
@@ -17,5 +17,5 @@
 
 | Backbone  | Style   | Lr schd | Mem (GB) | Inf time (fps) | box AP | Config | Download |
 |:---------:|:-------:|:-------:|:--------:|:--------------:|:------:|:------:|:--------:|
-| R-50      | pytorch | 1x      | 3.7      | 19.7           |  39.4  | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/atss/atss_r50_fpn_1x_coco.py) | [model](http://download.openmmlab.com/mmdetection/v2.0/atss/atss_r50_fpn_1x_coco/atss_r50_fpn_1x_coco_20200209-985f7bd0.pth) &#124; [log](http://download.openmmlab.com/mmdetection/v2.0/atss/atss_r50_fpn_1x_coco/atss_r50_fpn_1x_coco_20200209_102539.log.json) |
-| R-101     | pytorch | 1x      | 5.6      | 12.3           |  41.5  | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/atss/atss_r101_fpn_1x_coco.py) | [model](http://download.openmmlab.com/mmdetection/v2.0/atss/atss_r101_fpn_1x_coco/atss_r101_fpn_1x_20200825-dfcadd6f.pth) &#124; [log](http://download.openmmlab.com/mmdetection/v2.0/atss/atss_r101_fpn_1x_coco/atss_r101_fpn_1x_20200825-dfcadd6f.log.json) |
+| R-50      | pytorch | 1x      | 3.7      | 19.7           |  39.4  | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/atss/atss_r50_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/atss/atss_r50_fpn_1x_coco/atss_r50_fpn_1x_coco_20200209-985f7bd0.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/atss/atss_r50_fpn_1x_coco/atss_r50_fpn_1x_coco_20200209_102539.log.json) |
+| R-101     | pytorch | 1x      | 5.6      | 12.3           |  41.5  | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/atss/atss_r101_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/atss/atss_r101_fpn_1x_coco/atss_r101_fpn_1x_20200825-dfcadd6f.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/atss/atss_r101_fpn_1x_coco/atss_r101_fpn_1x_20200825-dfcadd6f.log.json) |
diff --git a/configs/atss/atss_r101_fpn_1x_coco.py b/configs/atss/atss_r101_fpn_1x_coco.py
@@ -1,5 +1,6 @@
 _base_ = './atss_r50_fpn_1x_coco.py'
 model = dict(
-    pretrained='torchvision://resnet101',
-    backbone=dict(depth=101),
-)
+    backbone=dict(
+        depth=101,
+        init_cfg=dict(type='Pretrained',
+                      checkpoint='torchvision://resnet101')))