open-mmlab · hhaAndroid · Dec 27, 2022 · Dec 12, 2022 · Dec 12, 2022 · Dec 12, 2022
diff --git a/configs/yolov5/voc/yolov5_s-v61_fast_1xb64-50e_voc.py b/configs/yolov5/voc/yolov5_s-v61_fast_1xb64-50e_voc.py
@@ -160,7 +160,7 @@
         ],
         # Use ignore_keys to avoid judging metainfo is
         # not equal in `ConcatDataset`.
-        ignore_keys='DATASET_TYPE'),
+        ignore_keys='dataset_type'),
     collate_fn=dict(type='yolov5_collate'))
 
 test_pipeline = [

diff --git a/configs/yolov5/yolov5_s-v61_syncbn_fast_1xb4-300e_balloon.py b/configs/yolov5/yolov5_s-v61_syncbn_fast_1xb4-300e_balloon.py
@@ -6,8 +6,8 @@
 train_num_workers = 2
 
 metainfo = {
-    'CLASSES': ('balloon', ),
-    'PALETTE': [
+    'classes': ('balloon', ),
+    'palette': [
         (220, 20, 60),
     ]
 }

diff --git a/demo/image_demo.py b/demo/image_demo.py
@@ -71,7 +71,7 @@ def main():
     files, source_type = get_file_list(args.img)
 
     # get model class name
-    dataset_classes = model.dataset_meta.get('CLASSES')
+    dataset_classes = model.dataset_meta.get('classes')
 
     # ready for labelme format if it is needed
     to_label_format = LabelmeFormat(classes=dataset_classes)

diff --git a/docs/en/index.rst b/docs/en/index.rst
@@ -50,6 +50,7 @@ Welcome to MMYOLO's documentation!
 
    notes/changelog.md
    notes/faq.md
+   notes/compatibility.md
 
 .. toctree::
    :maxdepth: 2

diff --git a/docs/en/notes/compatibility.md b/docs/en/notes/compatibility.md
@@ -0,0 +1,11 @@
+# Compatibility of MMYOLO
+
+## MMYOLO 0.3.0
+
+To unify with other OpenMMLab repositories, change all keys of `METAINFO` in Dataset from upper case to lower case.
+
+| Before v0.3.0 | after v0.3.0 |
+| :-----------: | :----------: |
+|    CLASSES    |   classes    |
+|    PALETTE    |   palette    |
+| DATASET_TYPE  | dataset_type |
diff --git a/docs/en/user_guides/yolov5_tutorial.md b/docs/en/user_guides/yolov5_tutorial.md
@@ -53,8 +53,8 @@ train_batch_size_per_gpu = 4
 train_num_workers = 2
 
 metainfo = {
-    'CLASSES': ('balloon', ),
-    'PALETTE': [
+    'classes': ('balloon', ),
+    'palette': [
         (220, 20, 60),
     ]
 }

diff --git a/docs/zh_cn/index.rst b/docs/zh_cn/index.rst
@@ -56,6 +56,7 @@
 
    notes/faq.md
    notes/changelog.md
+   notes/compatibility.md
 
 .. toctree::
    :maxdepth: 2

diff --git a/docs/zh_cn/notes/compatibility.md b/docs/zh_cn/notes/compatibility.md
@@ -0,0 +1,11 @@
+# MMYOLO 兼容性说明
+
+## MMYOLO v0.3.0
+
+为了和 OpenMMLab 其他仓库统一，将 Dataset 里 `METAINFO` 的所有键从大写改为小写。
+
+| 在 v0.3.0 之前 | v0.3.0 及之后 |
+| :------------: | :-----------: |
+|    CLASSES     |    classes    |
+|    PALETTE     |    palette    |
+|  DATASET_TYPE  | dataset_type  |
diff --git a/docs/zh_cn/user_guides/custom_dataset.md b/docs/zh_cn/user_guides/custom_dataset.md
@@ -801,8 +801,8 @@ base_lr = _base_.base_lr / 8
 class_name = ('cat', )  # 根据 class_with_id.txt 类别信息，设置 class_name
 num_classes = len(class_name)
 metainfo = dict(
-    CLASSES=class_name,
-    PALETTE=[(220, 20, 60)]  # 画图时候的颜色，随便设置即可
+    classes=class_name,
+    palette=[(220, 20, 60)]  # 画图时候的颜色，随便设置即可
 )
 
 train_cfg = dict(

diff --git a/docs/zh_cn/user_guides/yolov5_tutorial.md b/docs/zh_cn/user_guides/yolov5_tutorial.md
@@ -53,8 +53,8 @@ train_batch_size_per_gpu = 4
 train_num_workers = 2
 
 metainfo = {
-    'CLASSES': ('balloon', ),
-    'PALETTE': [
+    'classes': ('balloon', ),
+    'palette': [
         (220, 20, 60),
     ]
 }

diff --git a/mmyolo/utils/boxam_utils.py b/mmyolo/utils/boxam_utils.py
@@ -79,20 +79,23 @@ def init_detector(
         checkpoint_meta = checkpoint.get('meta', {})
         # save the dataset_meta in the model for convenience
         if 'dataset_meta' in checkpoint_meta:
-            # mmdet 3.x
-            model.dataset_meta = checkpoint_meta['dataset_meta']
+            # mmdet 3.x, all keys should be lowercase
+            model.dataset_meta = {
+                k.lower(): v
+                for k, v in checkpoint_meta['dataset_meta'].items()
+            }
         elif 'CLASSES' in checkpoint_meta:
             # < mmdet 3.x
             classes = checkpoint_meta['CLASSES']
-            model.dataset_meta = {'CLASSES': classes, 'PALETTE': palette}
+            model.dataset_meta = {'classes': classes, 'palette': palette}
         else:
             warnings.simplefilter('once')
             warnings.warn(
                 'dataset_meta or class names are not saved in the '
                 'checkpoint\'s meta data, use COCO classes by default.')
             model.dataset_meta = {
-                'CLASSES': get_classes('coco'),
-                'PALETTE': palette
+                'classes': get_classes('coco'),
+                'palette': palette
             }
 
     model.cfg = config  # save the config in the model for convenience
@@ -254,7 +257,7 @@ def __init__(self,
             if self.is_need_grad:
                 self.cam.activations_and_grads.release()
 
-        self.classes = model.detector.dataset_meta['CLASSES']
+        self.classes = model.detector.dataset_meta['classes']
         self.COLORS = np.random.uniform(0, 255, size=(len(self.classes), 3))
 
     def switch_activations_and_grads(self, model) -> None:

diff --git a/projects/misc/custom_dataset/yolov5_s-v61_syncbn_fast_1xb32-100e_cat.py b/projects/misc/custom_dataset/yolov5_s-v61_syncbn_fast_1xb32-100e_cat.py
@@ -30,8 +30,8 @@
 class_name = ('cat', )  # 根据 class_with_id.txt 类别信息，设置 class_name
 num_classes = len(class_name)
 metainfo = dict(
-    CLASSES=class_name,
-    PALETTE=[(220, 20, 60)]  # 画图时候的颜色，随便设置即可
+    classes=class_name,
+    palette=[(220, 20, 60)]  # 画图时候的颜色，随便设置即可
 )
 
 train_cfg = dict(

diff --git a/projects/misc/custom_dataset/yolov6_s_syncbn_fast_1xb32-100e_cat.py b/projects/misc/custom_dataset/yolov6_s_syncbn_fast_1xb32-100e_cat.py
@@ -23,8 +23,8 @@
 class_name = ('cat', )  # 根据 class_with_id.txt 类别信息，设置 class_name
 num_classes = len(class_name)
 metainfo = dict(
-    CLASSES=class_name,
-    PALETTE=[(220, 20, 60)]  # 画图时候的颜色，随便设置即可
+    classes=class_name,
+    palette=[(220, 20, 60)]  # 画图时候的颜色，随便设置即可
 )
 
 train_cfg = dict(

diff --git a/tools/analysis_tools/dataset_analysis.py b/tools/analysis_tools/dataset_analysis.py
@@ -383,7 +383,7 @@ def replace_pipeline_to_none(cfg):
     # Drawing settings
     fig_all_set = {
         'figsize': [35, 18],
-        'fontsize': int(10 - 0.08 * len(dataset.metainfo['CLASSES'])),
+        'fontsize': int(10 - 0.08 * len(dataset.metainfo['classes'])),
         'xticks_angle': 70,
         'out_name': cfg.dataset_type
     }
@@ -396,15 +396,15 @@ def replace_pipeline_to_none(cfg):
 
     # Call the category name and save address
     if args.class_name is None:
-        classes = dataset.metainfo['CLASSES']
+        classes = dataset.metainfo['classes']
         classes_idx = [i for i in range(len(classes))]
         fig_set = fig_all_set
-    elif args.class_name in dataset.metainfo['CLASSES']:
+    elif args.class_name in dataset.metainfo['classes']:
         classes = [args.class_name]
-        classes_idx = [dataset.metainfo['CLASSES'].index(args.class_name)]
+        classes_idx = [dataset.metainfo['classes'].index(args.class_name)]
         fig_set = fig_one_set
     else:
-        data_classes = dataset.metainfo['CLASSES']
+        data_classes = dataset.metainfo['classes']
         show_data_classes(data_classes)
         raise RuntimeError(f'Expected args.class_name to be one of the list,'
                            f'but got "{args.class_name}"')