diff --git a/mmengine/infer/infer.py b/mmengine/infer/infer.py
index d72e986c0b..e27d1b233d 100644
--- a/mmengine/infer/infer.py
+++ b/mmengine/infer/infer.py
@@ -1,5 +1,6 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 import copy
+import importlib
 import os.path as osp
 import re
 import warnings
@@ -24,7 +25,6 @@
 from mmengine.runner.checkpoint import (_load_checkpoint,
                                         _load_checkpoint_to_model)
 from mmengine.structures import InstanceData
-from mmengine.utils import get_installed_path, is_installed
 from mmengine.visualization import Visualizer
 
 InstanceList = List[InstanceData]
@@ -368,10 +368,10 @@ def _load_model_from_metafile(self, model: str) -> Tuple[Config, str]:
         assert self.scope in MODULE2PACKAGE, (
             f'{self.scope} not in {MODULE2PACKAGE}!,'
             'please pass a valid scope.')
-        project = MODULE2PACKAGE[self.scope]
-        assert is_installed(project), f'Please install {project}'
-        package_path = get_installed_path(project)
-        for model_cfg in BaseInferencer._get_models_from_package(package_path):
+
+        repo_or_mim_dir = BaseInferencer._get_repo_or_mim_dir(self.scope)
+        for model_cfg in BaseInferencer._get_models_from_metafile(
+                repo_or_mim_dir):
             model_name = model_cfg['Name'].lower()
             model_aliases = model_cfg.get('Alias', [])
             if isinstance(model_aliases, str):
@@ -380,11 +380,50 @@ def _load_model_from_metafile(self, model: str) -> Tuple[Config, str]:
                 model_aliases = [alias.lower() for alias in model_aliases]
             if (model_name == model or model in model_aliases):
                 cfg = Config.fromfile(
-                    osp.join(package_path, '.mim', model_cfg['Config']))
+                    osp.join(repo_or_mim_dir, model_cfg['Config']))
                 weights = model_cfg['Weights']
                 weights = weights[0] if isinstance(weights, list) else weights
                 return cfg, weights
-        raise ValueError(f'Cannot find model: {model} in {project}')
+        raise ValueError(f'Cannot find model: {model} in {self.scope}')
+
+    @staticmethod
+    def _get_repo_or_mim_dir(scope):
+        """Get the directory where the ``Configs`` located when the package is
+        installed or ``PYTHONPATH`` is set.
+
+        Args:
+            scope (str): The scope of repository.
+
+        Returns:
+            str: The directory where the ``Configs`` is located.
+        """
+        try:
+            module = importlib.import_module(scope)
+        except ImportError:
+            if scope not in MODULE2PACKAGE:
+                raise KeyError(
+                    f'{scope} is not a valid scope. The available scopes '
+                    f'are {MODULE2PACKAGE.keys()}')
+            else:
+                project = MODULE2PACKAGE[scope]
+                raise ImportError(
+                    f'Cannot import {scope} correctly, please try to install '
+                    f'the {project} by "pip install {project}"')
+        # Since none of OpenMMLab series packages are namespace packages
+        # (https://docs.python.org/3/glossary.html#term-namespace-package),
+        # The first element of module.__path__ means package installation path.
+        package_path = module.__path__[0]
+
+        if osp.exists(osp.join(osp.dirname(package_path), 'configs')):
+            repo_dir = osp.dirname(package_path)
+            return repo_dir
+        else:
+            mim_dir = osp.join(package_path, '.mim')
+            if not osp.exists(osp.join(mim_dir, 'Configs')):
+                raise FileNotFoundError(
+                    f'Cannot find Configs directory in {package_path}!, '
+                    f'please check the completeness of the {scope}.')
+            return mim_dir
 
     def _init_model(
         self,
@@ -591,19 +630,21 @@ def _dispatch_kwargs(self, **kwargs) -> Tuple[Dict, Dict, Dict, Dict]:
         )
 
     @staticmethod
-    def _get_models_from_package(package_path: str):
+    def _get_models_from_metafile(dir: str):
         """Load model config defined in metafile from package path.
 
         Args:
-            package_path (str): Path to the package.
+            dir (str): Path to the directory of Config. It requires the
+                directory ``Config``, file ``model-index.yml`` exists in the
+                ``dir``.
 
         Yields:
             dict: Model config defined in metafile.
         """
-        meta_indexes = load(osp.join(package_path, '.mim', 'model-index.yml'))
+        meta_indexes = load(osp.join(dir, 'model-index.yml'))
         for meta_path in meta_indexes['Import']:
             # meta_path example: mmcls/.mim/configs/conformer/metafile.yml
-            meta_path = osp.join(package_path, '.mim', meta_path)
+            meta_path = osp.join(dir, meta_path)
             metainfo = load(meta_path)
             yield from metainfo['Models']
 
@@ -631,11 +672,9 @@ def list_models(scope: Optional[str] = None, patterns: str = r'.*'):
         assert scope in MODULE2PACKAGE, (
             f'{scope} not in {MODULE2PACKAGE}!, please make pass a valid '
             'scope.')
-        project = MODULE2PACKAGE[scope]
-        assert is_installed(project), (f'Please install {project}')
-        package_path = get_installed_path(project)
-
-        for model_cfg in BaseInferencer._get_models_from_package(package_path):
+        root_or_mim_dir = BaseInferencer._get_repo_or_mim_dir(scope)
+        for model_cfg in BaseInferencer._get_models_from_metafile(
+                root_or_mim_dir):
             model_name = [model_cfg['Name']]
             model_name.extend(model_cfg.get('Alias', []))
             for name in model_name: