[Fix] Update correct In Collection in metafile of each configs.

.dev/md2yml.py

@@ -81,6 +81,13 @@ def parse_md(md_file):
     code_version = None
     repo_url = None
 
+    # To avoid re-counting number of backbone model in OpenMMLab,
+    # if certain model in configs folder is backbone whose name is already
+    # recorded in MMClassification, then the `COLLECTION` dict of this model
+    # in MMSegmentation should be deleted, and `In Collection` in `Models`
+    # should be set with head or neck of this config file.
+    is_backbone = None
+
     with open(md_file, 'r') as md:
         lines = md.readlines()
         i = 0
@@ -117,9 +124,13 @@ def parse_md(md_file):
                 datasets.append(line[4:])
                 current_dataset = line[4:]
                 i += 2
+            elif line[:15] == '<!-- [BACKBONE]':
+                is_backbone = True
+                i += 1
             elif line[0] == '|' and (
                     i + 1) < len(lines) and lines[i + 1][:3] == '| -':
                 cols = [col.strip() for col in line.split('|')]
+                method_id = cols.index('Method')
                 backbone_id = cols.index('Backbone')
                 crop_size_id = cols.index('Crop Size')
                 lr_schd_id = cols.index('Lr schd')
@@ -155,11 +166,13 @@ def parse_md(md_file):
                         mem_id] != '' else -1
                     crop_size = els[crop_size_id].split('x')
                     assert len(crop_size) == 2
+                    method = els[method_id].split(
+                        '-')[-1] if is_backbone else collection_name
                     model = {
                         'Name':
                         model_name,
                         'In Collection':
-                        collection_name,
+                        method,
                         'Metadata': {
                             'backbone': els[backbone_id],
                             'crop size': f'({crop_size[0]},{crop_size[1]})',
@@ -232,8 +245,10 @@ def parse_md(md_file):
                     collection.pop(check_key)
                 else:
                     collection[check_key].pop(key)
-
-    result = {'Collections': [collection], 'Models': models}
+    if is_backbone:
+        result = {'Models': models}
+    else:
+        result = {'Collections': [collection], 'Models': models}
     yml_file = f'{md_file[:-9]}{collection_name}.yml'
     return dump_yaml_and_check_difference(result, yml_file)
 

configs/hrnet/hrnet.yml

@@ -1,27 +1,6 @@
-Collections:
-- Name: hrnet
-  Metadata:
-    Training Data:
-    - Cityscapes
-    - ADE20K
-    - Pascal VOC 2012 + Aug
-    - Pascal Context
-    - Pascal Context 59
-    - LoveDA
-    - Potsdam
-    - Vaihingen
-  Paper:
-    URL: https://arxiv.org/abs/1908.07919
-    Title: Deep High-Resolution Representation Learning for Human Pose Estimation
-  README: configs/hrnet/README.md
-  Code:
-    URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/hrnet.py#L218
-    Version: v0.17.0
-  Converted From:
-    Code: https://github.com/HRNet/HRNet-Semantic-Segmentation
 Models:
 - Name: fcn_hr18s_512x1024_40k_cityscapes
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18-Small
     crop size: (512,1024)
@@ -43,7 +22,7 @@ Models:
   Config: configs/hrnet/fcn_hr18s_512x1024_40k_cityscapes.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x1024_40k_cityscapes/fcn_hr18s_512x1024_40k_cityscapes_20200601_014216-93db27d0.pth
 - Name: fcn_hr18_512x1024_40k_cityscapes
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18
     crop size: (512,1024)
@@ -65,7 +44,7 @@ Models:
   Config: configs/hrnet/fcn_hr18_512x1024_40k_cityscapes.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x1024_40k_cityscapes/fcn_hr18_512x1024_40k_cityscapes_20200601_014216-f196fb4e.pth
 - Name: fcn_hr48_512x1024_40k_cityscapes
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (512,1024)
@@ -87,7 +66,7 @@ Models:
   Config: configs/hrnet/fcn_hr48_512x1024_40k_cityscapes.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x1024_40k_cityscapes/fcn_hr48_512x1024_40k_cityscapes_20200601_014240-a989b146.pth
 - Name: fcn_hr18s_512x1024_80k_cityscapes
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18-Small
     crop size: (512,1024)
@@ -101,7 +80,7 @@ Models:
   Config: configs/hrnet/fcn_hr18s_512x1024_80k_cityscapes.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x1024_80k_cityscapes/fcn_hr18s_512x1024_80k_cityscapes_20200601_202700-1462b75d.pth
 - Name: fcn_hr18_512x1024_80k_cityscapes
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18
     crop size: (512,1024)
@@ -115,7 +94,7 @@ Models:
   Config: configs/hrnet/fcn_hr18_512x1024_80k_cityscapes.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x1024_80k_cityscapes/fcn_hr18_512x1024_80k_cityscapes_20200601_223255-4e7b345e.pth
 - Name: fcn_hr48_512x1024_80k_cityscapes
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (512,1024)
@@ -129,7 +108,7 @@ Models:
   Config: configs/hrnet/fcn_hr48_512x1024_80k_cityscapes.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x1024_80k_cityscapes/fcn_hr48_512x1024_80k_cityscapes_20200601_202606-58ea95d6.pth
 - Name: fcn_hr18s_512x1024_160k_cityscapes
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18-Small
     crop size: (512,1024)
@@ -143,7 +122,7 @@ Models:
   Config: configs/hrnet/fcn_hr18s_512x1024_160k_cityscapes.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x1024_160k_cityscapes/fcn_hr18s_512x1024_160k_cityscapes_20200602_190901-4a0797ea.pth
 - Name: fcn_hr18_512x1024_160k_cityscapes
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18
     crop size: (512,1024)
@@ -157,7 +136,7 @@ Models:
   Config: configs/hrnet/fcn_hr18_512x1024_160k_cityscapes.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x1024_160k_cityscapes/fcn_hr18_512x1024_160k_cityscapes_20200602_190822-221e4a4f.pth
 - Name: fcn_hr48_512x1024_160k_cityscapes
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (512,1024)
@@ -171,7 +150,7 @@ Models:
   Config: configs/hrnet/fcn_hr48_512x1024_160k_cityscapes.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x1024_160k_cityscapes/fcn_hr48_512x1024_160k_cityscapes_20200602_190946-59b7973e.pth
 - Name: fcn_hr18s_512x512_80k_ade20k
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18-Small
     crop size: (512,512)
@@ -193,7 +172,7 @@ Models:
   Config: configs/hrnet/fcn_hr18s_512x512_80k_ade20k.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_ade20k/fcn_hr18s_512x512_80k_ade20k_20200614_144345-77fc814a.pth
 - Name: fcn_hr18_512x512_80k_ade20k
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18
     crop size: (512,512)
@@ -215,7 +194,7 @@ Models:
   Config: configs/hrnet/fcn_hr18_512x512_80k_ade20k.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_ade20k/fcn_hr18_512x512_80k_ade20k_20210827_114910-6c9382c0.pth
 - Name: fcn_hr48_512x512_80k_ade20k
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (512,512)
@@ -237,7 +216,7 @@ Models:
   Config: configs/hrnet/fcn_hr48_512x512_80k_ade20k.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_ade20k/fcn_hr48_512x512_80k_ade20k_20200614_193946-7ba5258d.pth
 - Name: fcn_hr18s_512x512_160k_ade20k
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18-Small
     crop size: (512,512)
@@ -251,7 +230,7 @@ Models:
   Config: configs/hrnet/fcn_hr18s_512x512_160k_ade20k.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_160k_ade20k/fcn_hr18s_512x512_160k_ade20k_20210829_174739-f1e7c2e7.pth
 - Name: fcn_hr18_512x512_160k_ade20k
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18
     crop size: (512,512)
@@ -265,7 +244,7 @@ Models:
   Config: configs/hrnet/fcn_hr18_512x512_160k_ade20k.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_160k_ade20k/fcn_hr18_512x512_160k_ade20k_20200614_214426-ca961836.pth
 - Name: fcn_hr48_512x512_160k_ade20k
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (512,512)
@@ -279,7 +258,7 @@ Models:
   Config: configs/hrnet/fcn_hr48_512x512_160k_ade20k.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_160k_ade20k/fcn_hr48_512x512_160k_ade20k_20200614_214407-a52fc02c.pth
 - Name: fcn_hr18s_512x512_20k_voc12aug
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18-Small
     crop size: (512,512)
@@ -301,7 +280,7 @@ Models:
   Config: configs/hrnet/fcn_hr18s_512x512_20k_voc12aug.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_20k_voc12aug/fcn_hr18s_512x512_20k_voc12aug_20210829_174910-0aceadb4.pth
 - Name: fcn_hr18_512x512_20k_voc12aug
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18
     crop size: (512,512)
@@ -323,7 +302,7 @@ Models:
   Config: configs/hrnet/fcn_hr18_512x512_20k_voc12aug.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_20k_voc12aug/fcn_hr18_512x512_20k_voc12aug_20200617_224503-488d45f7.pth
 - Name: fcn_hr48_512x512_20k_voc12aug
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (512,512)
@@ -345,7 +324,7 @@ Models:
   Config: configs/hrnet/fcn_hr48_512x512_20k_voc12aug.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_20k_voc12aug/fcn_hr48_512x512_20k_voc12aug_20200617_224419-89de05cd.pth
 - Name: fcn_hr18s_512x512_40k_voc12aug
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18-Small
     crop size: (512,512)
@@ -359,7 +338,7 @@ Models:
   Config: configs/hrnet/fcn_hr18s_512x512_40k_voc12aug.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_40k_voc12aug/fcn_hr18s_512x512_40k_voc12aug_20200614_000648-4f8d6e7f.pth
 - Name: fcn_hr18_512x512_40k_voc12aug
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18
     crop size: (512,512)
@@ -373,7 +352,7 @@ Models:
   Config: configs/hrnet/fcn_hr18_512x512_40k_voc12aug.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_40k_voc12aug/fcn_hr18_512x512_40k_voc12aug_20200613_224401-1b4b76cd.pth
 - Name: fcn_hr48_512x512_40k_voc12aug
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (512,512)
@@ -387,7 +366,7 @@ Models:
   Config: configs/hrnet/fcn_hr48_512x512_40k_voc12aug.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_40k_voc12aug/fcn_hr48_512x512_40k_voc12aug_20200613_222111-1b0f18bc.pth
 - Name: fcn_hr48_480x480_40k_pascal_context
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (480,480)
@@ -409,7 +388,7 @@ Models:
   Config: configs/hrnet/fcn_hr48_480x480_40k_pascal_context.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_480x480_40k_pascal_context/fcn_hr48_480x480_40k_pascal_context_20200911_164852-667d00b0.pth
 - Name: fcn_hr48_480x480_80k_pascal_context
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (480,480)
@@ -423,7 +402,7 @@ Models:
   Config: configs/hrnet/fcn_hr48_480x480_80k_pascal_context.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_480x480_80k_pascal_context/fcn_hr48_480x480_80k_pascal_context_20200911_155322-847a6711.pth
 - Name: fcn_hr48_480x480_40k_pascal_context_59
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (480,480)
@@ -437,7 +416,7 @@ Models:
   Config: configs/hrnet/fcn_hr48_480x480_40k_pascal_context_59.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_480x480_40k_pascal_context_59/fcn_hr48_480x480_40k_pascal_context_59_20210410_122738-b808b8b2.pth
 - Name: fcn_hr48_480x480_80k_pascal_context_59
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (480,480)
@@ -451,7 +430,7 @@ Models:
   Config: configs/hrnet/fcn_hr48_480x480_80k_pascal_context_59.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_480x480_80k_pascal_context_59/fcn_hr48_480x480_80k_pascal_context_59_20210411_003240-3ae7081e.pth
 - Name: fcn_hr18s_512x512_80k_loveda
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18-Small
     crop size: (512,512)
@@ -473,7 +452,7 @@ Models:
   Config: configs/hrnet/fcn_hr18s_512x512_80k_loveda.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211210_203228-60a86a7a.pth
 - Name: fcn_hr18_512x512_80k_loveda
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18
     crop size: (512,512)
@@ -495,7 +474,7 @@ Models:
   Config: configs/hrnet/fcn_hr18_512x512_80k_loveda.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211210_203952-93d9c3b3.pth
 - Name: fcn_hr48_512x512_80k_loveda
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (512,512)
@@ -517,7 +496,7 @@ Models:
   Config: configs/hrnet/fcn_hr48_512x512_80k_loveda.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211211_044756-67072f55.pth
 - Name: fcn_hr18s_512x512_80k_potsdam
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18-Small
     crop size: (512,512)
@@ -539,7 +518,7 @@ Models:
   Config: configs/hrnet/fcn_hr18s_512x512_80k_potsdam.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_potsdam/fcn_hr18s_512x512_80k_potsdam_20211218_205517-ba32af63.pth
 - Name: fcn_hr18_512x512_80k_potsdam
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18
     crop size: (512,512)
@@ -561,7 +540,7 @@ Models:
   Config: configs/hrnet/fcn_hr18_512x512_80k_potsdam.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_potsdam/fcn_hr18_512x512_80k_potsdam_20211218_205517-5d0387ad.pth
 - Name: fcn_hr48_512x512_80k_potsdam
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (512,512)
@@ -583,7 +562,7 @@ Models:
   Config: configs/hrnet/fcn_hr48_512x512_80k_potsdam.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_potsdam/fcn_hr48_512x512_80k_potsdam_20211219_020601-97434c78.pth
 - Name: fcn_hr18s_4x4_512x512_80k_vaihingen
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18-Small
     crop size: (512,512)
@@ -605,7 +584,7 @@ Models:
   Config: configs/hrnet/fcn_hr18s_4x4_512x512_80k_vaihingen.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_4x4_512x512_80k_vaihingen/fcn_hr18s_4x4_512x512_80k_vaihingen_20211231_230909-b23aae02.pth
 - Name: fcn_hr18_4x4_512x512_80k_vaihingen
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W18
     crop size: (512,512)
@@ -627,7 +606,7 @@ Models:
   Config: configs/hrnet/fcn_hr18_4x4_512x512_80k_vaihingen.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_4x4_512x512_80k_vaihingen/fcn_hr18_4x4_512x512_80k_vaihingen_20211231_231216-2ec3ae8a.pth
 - Name: fcn_hr48_4x4_512x512_80k_vaihingen
-  In Collection: hrnet
+  In Collection: FCN
   Metadata:
     backbone: HRNetV2p-W48
     crop size: (512,512)