Regularize load_super_animal_config()

AlexEMG · Sep 10, 2025 · Jun 25, 2025 · Jun 26, 2025 · Jun 26, 2025 · Jun 26, 2025
commit 424ac92941fbdf30ff61c432a2b6575fc3836ca6
diff --git a/deeplabcut/pose_estimation_pytorch/modelzoo/utils.py b/deeplabcut/pose_estimation_pytorch/modelzoo/utils.py
@@ -15,7 +15,6 @@
 
 import torch
 from dlclibrary import download_huggingface_model
-import huggingface_hub
 
 import deeplabcut.pose_estimation_pytorch.config.utils as config_utils
 from deeplabcut.core.config import read_config_as_dict
@@ -108,52 +107,19 @@ def load_super_animal_config(
     project_cfg_path = get_super_animal_project_config_path(super_animal=super_animal)
     project_config = read_config_as_dict(project_cfg_path)
 
-    # Special handling for superanimal_humanbody with rtmpose_x - download config from HuggingFace
-    if super_animal == "superanimal_humanbody" and model_name == "rtmpose_x":
-        # Download config from HuggingFace
-        model_files = get_snapshot_folder_path()
-        model_files.mkdir(exist_ok=True)
-
-        path_model_config = Path(
-            huggingface_hub.hf_hub_download(
-                "DeepLabCut/HumanBody",
-                "rtmpose-x_simcc-body7_pytorch_config.yaml",
-                local_dir=model_files,
-            )
-        )
-        model_config = read_config_as_dict(path_model_config)
-    else:
-        # Use local config file for other models
-        model_cfg_path = get_super_animal_model_config_path(model_name=model_name, super_animal=super_animal)
-        model_config = read_config_as_dict(model_cfg_path)
-
-    model_config = add_metadata(project_config, model_config, model_cfg_path if 'model_cfg_path' in locals() else path_model_config)
+    model_cfg_path = get_super_animal_model_config_path(model_name=model_name)
+    model_config = read_config_as_dict(model_cfg_path)
+    model_config = add_metadata(project_config, model_config, model_cfg_path)
+    model_config = update_config(model_config, max_individuals, device)
 
-    if detector_name is None:
+    if detector_name is None and super_animal != "superanimal_humanbody":
         model_config["method"] = "BU"
     else:
-        # Check if this is a torchvision detector (not in dlclibrary)
-        if super_animal == "superanimal_humanbody" and detector_name == "fasterrcnn_mobilenet_v3_large_fpn":
-            # Use torchvision detector - set method to TD and load detector config
-            model_config["method"] = "TD"
-            detector_cfg_path = get_super_animal_model_config_path(model_name=detector_name, super_animal=super_animal)
+        model_config["method"] = "TD"
+        if super_animal != "superanimal_humanbody":
+            detector_cfg_path = get_super_animal_model_config_path(model_name=detector_name)
             detector_cfg = read_config_as_dict(detector_cfg_path)
             model_config["detector"] = detector_cfg
-        else:
-            # Load detector config from dlclibrary
-            detector_cfg_path = get_super_animal_model_config_path(model_name=detector_name, super_animal=super_animal)
-            detector_cfg = read_config_as_dict(detector_cfg_path)
-            model_config["method"] = "TD"
-            model_config["detector"] = detector_cfg
-
-    # Update config after detector is added (if any)
-    model_config = update_config(model_config, max_individuals, device)
-
-    # Add superanimal_name to metadata for all superanimal models (needed for detector routing)
-    if "metadata" not in model_config:
-        model_config["metadata"] = {}
-    model_config["metadata"]["superanimal_name"] = super_animal
-
     return model_config