diff --git a/happypose/pose_estimators/cosypose/cosypose/utils/cosypose_wrapper.py b/happypose/pose_estimators/cosypose/cosypose/utils/cosypose_wrapper.py
index 6f87a3e6..2e6f447e 100644
--- a/happypose/pose_estimators/cosypose/cosypose/utils/cosypose_wrapper.py
+++ b/happypose/pose_estimators/cosypose/cosypose/utils/cosypose_wrapper.py
@@ -32,6 +32,47 @@
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 
+# To download model weights for one of the datasets, run these commands:
+# python -m happypose.toolbox.utils.download --cosypose_models=<detector_run_id>
+# python -m happypose.toolbox.utils.download --cosypose_models=<coarse_run_id>
+# python -m happypose.toolbox.utils.download --cosypose_models=<refiner_run_id>
+
+AVAILABLE_MODELS = {
+    "hope": {
+        "pbr": {
+            "detector_run_id": "detector-bop-hope-pbr--15246",
+            "coarse_run_id": "coarse-bop-hope-pbr--225203",
+            "refiner_run_id": "refiner-bop-hope-pbr--955392",
+        },
+        "synth+real": {},  # no such model
+    },
+    "tless": {
+        "pbr": {
+            "detector_run_id": "detector-bop-tless-pbr--873074",
+            "coarse_run_id": "coarse-bop-tless-pbr--506801",
+            "refiner_run_id": "refiner-bop-tless-pbr--233420",
+        },
+        "synth+real": {
+            "detector_run_id": "detector-bop-tless-synt+real--452847",
+            "coarse_run_id": "coarse-bop-tless-synt+real--160982",
+            "refiner_run_id": "refiner-bop-tless-synt+real--881314",
+        },
+    },
+    "ycbv": {
+        "ycbv": {
+            "detector_run_id": "detector-bop-ycbv-pbr--970850",
+            "coarse_run_id": "coarse-bop-ycbv-pbr--724183",
+            "refiner_run_id": "refiner-bop-ycbv-pbr--604090",
+        },
+        "synth+real": {
+            "detector_run_id": "detector-bop-ycbv-synt+real--292971",
+            "coarse_run_id": "coarse-bop-ycbv-synt+real--822463",
+            "refiner_run_id": "refiner-bop-ycbv-synt+real--631598",
+        },
+    },
+}
+
+
 class CosyPoseWrapper:
     def __init__(
         self,
@@ -56,38 +97,25 @@ def __init__(
             dataset_name, n_workers, renderer_type
         )
 
-    def get_model(self, dataset_name, n_workers, renderer_type):
-        # load models
-        if dataset_name == "hope":
-            # HOPE setup
-            # python -m happypose.toolbox.utils.download --cosypose_models=detector-bop-hope-pbr--15246
-            # python -m happypose.toolbox.utils.download --cosypose_models=coarse-bop-hope-pbr--225203
-            # python -m happypose.toolbox.utils.download --cosypose_models=refiner-bop-hope-pbr--955392
-            detector_run_id = "detector-bop-hope-pbr--15246"
-            coarse_run_id = "coarse-bop-hope-pbr--225203"
-            refiner_run_id = "refiner-bop-hope-pbr--955392"
-        elif dataset_name == "tless":
-            # TLESS setup
-            # python -m happypose.toolbox.utils.download --cosypose_models=detector-bop-tless-pbr--873074
-            # python -m happypose.toolbox.utils.download --cosypose_models=coarse-bop-tless-pbr--506801
-            # python -m happypose.toolbox.utils.download --cosypose_models=refiner-bop-tless-pbr--233420
-            detector_run_id = "detector-bop-tless-pbr--873074"
-            coarse_run_id = "coarse-bop-tless-pbr--506801"
-            refiner_run_id = "refiner-bop-tless-pbr--233420"
-        elif dataset_name == "ycbv":
-            # YCBV setup
-            # python -m happypose.toolbox.utils.download --cosypose_models=detector-bop-ycbv-pbr--970850
-            # python -m happypose.toolbox.utils.download --cosypose_models=coarse-bop-ycbv-pbr--724183
-            # python -m happypose.toolbox.utils.download --cosypose_models=refiner-bop-ycbv-pbr--604090
-            detector_run_id = "detector-bop-ycbv-pbr--970850"
-            coarse_run_id = "coarse-bop-ycbv-pbr--724183"
-            refiner_run_id = "refiner-bop-ycbv-pbr--604090"
-        else:
-            msg = f"Not prepared for {dataset_name} dataset"
-            raise ValueError(msg)
-        detector = load_detector(detector_run_id, device)
+    def get_model(self, dataset_name, n_workers, renderer_type, model_type="pbr"):
+        """
+
+        :param dataset_name: str, name of the dataset on which model was trained
+        :param n_workers: int, number of workers used in the renderer
+        :param renderer_type: str, which renderer to use, "panda3d" and "bullet" supported
+        :param model_type: str, what training data was used, "pbr" and "synth+real" supported
+        :return: tuple (detector)
+        """
+        try:
+            mids = AVAILABLE_MODELS[dataset_name][model_type]
+        except KeyError:
+            raise KeyError(
+                f"{dataset_name}, {model_type} combination not supported when loading cosypose models"
+            )
+
+        detector = load_detector(mids["detector_run_id"], device)
         coarse_model, refiner_model = self.load_pose_models(
-            coarse_run_id, refiner_run_id, n_workers, renderer_type
+            mids["coarse_run_id"], mids["refiner_run_id"], n_workers, renderer_type
         )
 
         pose_estimator = PoseEstimator(