improve automodel design

1. raise warning for no available models
2. identify models based on dataset names

src/layoutparser/models/auto_layoutmodel.py

@@ -13,26 +13,57 @@
 # limitations under the License.
 
 from typing import Optional, Dict, Union, List
-from .detectron2.layoutmodel import Detectron2LayoutModel
-from .paddledetection.layoutmodel import PaddleDetectionLayoutModel
-from .effdet.layoutmodel import EfficientDetLayoutModel
+from collections import defaultdict
+
 from .model_config import (
     is_lp_layout_model_config_any_format,
 )
+from ..file_utils import (
+    is_effdet_available,
+    is_detectron2_available,
+    is_paddle_available,
+)
+
+ALL_AVAILABLE_BACKENDS = dict()
+ALL_AVAILABLE_DATASETS = defaultdict(list)
+
+if is_effdet_available():
+    from .effdet.layoutmodel import EfficientDetLayoutModel
+    from .effdet.catalog import MODEL_CATALOG as _effdet_model_catalog
+
+    # fmt: off
+    ALL_AVAILABLE_BACKENDS[EfficientDetLayoutModel.DETECTOR_NAME] = EfficientDetLayoutModel
+    for dataset_name in _effdet_model_catalog:
+        ALL_AVAILABLE_DATASETS[dataset_name].append(EfficientDetLayoutModel.DETECTOR_NAME)
+    # fmt: on
+
+if is_detectron2_available():
+    from .detectron2.layoutmodel import Detectron2LayoutModel
+    from .detectron2.catalog import MODEL_CATALOG as _detectron2_model_catalog
+
+    # fmt: off
+    ALL_AVAILABLE_BACKENDS[Detectron2LayoutModel.DETECTOR_NAME] = Detectron2LayoutModel
+    for dataset_name in _detectron2_model_catalog:
+        ALL_AVAILABLE_DATASETS[dataset_name].append(Detectron2LayoutModel.DETECTOR_NAME)
+    # fmt: on
+
+if is_paddle_available():
+    from .paddledetection.layoutmodel import PaddleDetectionLayoutModel
+    from .paddledetection.catalog import MODEL_CATALOG as _paddle_model_catalog
 
-ALL_AVAILABLE_BACKENDS = {
-    Detectron2LayoutModel.DETECTOR_NAME: Detectron2LayoutModel,
-    PaddleDetectionLayoutModel.DETECTOR_NAME: PaddleDetectionLayoutModel,
-    EfficientDetLayoutModel.DETECTOR_NAME: EfficientDetLayoutModel,
-}
+    # fmt: off
+    ALL_AVAILABLE_BACKENDS[PaddleDetectionLayoutModel.DETECTOR_NAME] = PaddleDetectionLayoutModel
+    for dataset_name in _paddle_model_catalog:
+        ALL_AVAILABLE_DATASETS[dataset_name].append(PaddleDetectionLayoutModel.DETECTOR_NAME)
+    # fmt: on
 
 
 def AutoLayoutModel(
     config_path: str,
     model_path: Optional[str] = None,
-    label_map: Optional[Dict]=None,
-    device: Optional[str]=None,
-    extra_config: Optional[Union[Dict, List]]=None,
+    label_map: Optional[Dict] = None,
+    device: Optional[str] = None,
+    extra_config: Optional[Union[Dict, List]] = None,
 ) -> "BaseLayoutModel":
     """[summary]
 
@@ -50,7 +81,7 @@ def AutoLayoutModel(
             Defaults to `None`.
         device(:obj:`str`, optional):
             Whether to use cuda or cpu devices. If not set, LayoutParser will
-            automatically determine the device to initialize the models on. 
+            automatically determine the device to initialize the models on.
         extra_config (:obj:`dict`, optional):
             Extra configuration passed used for initializing the layout model.
 
@@ -59,6 +90,8 @@ def AutoLayoutModel(
     """
     if not is_lp_layout_model_config_any_format(config_path):
         raise ValueError(f"Invalid model config_path {config_path}")
+
+    # Try to search for the model keywords 
     for backend_name in ALL_AVAILABLE_BACKENDS:
         if backend_name in config_path:
             return ALL_AVAILABLE_BACKENDS[backend_name](
@@ -68,3 +101,16 @@ def AutoLayoutModel(
                 extra_config=extra_config,
                 device=device,
             )
+
+    # Try to search for the dataset keywords 
+    for dataset_name in ALL_AVAILABLE_DATASETS:
+        if dataset_name in config_path:
+            return ALL_AVAILABLE_BACKENDS[ALL_AVAILABLE_DATASETS[dataset_name][0]](
+                config_path,
+                model_path=model_path,
+                label_map=label_map,
+                extra_config=extra_config,
+                device=device,
+            )
+
+    raise ValueError(f"No available model found for {config_path}")