adopt new model name 'fmpose3d_humans' in fmpose3d and tests

Author: deruyter92

fmpose3d/fmpose3d.py

@@ -483,7 +483,7 @@ class _IngestedInput:
 class FMPose3DInference:
     """High-level, two-step inference API for FMPose3D.
 
-    Supports both **human** (``model_type="fmpose3d"``, 17 H36M joints)
+    Supports both **human** (``model_type="fmpose3d_humans"``, 17 H36M joints)
     and **animal** (``model_type="fmpose3d_animals"``, 26 Animal3D joints)
     pipelines.  The skeleton layout, 2D estimator, and post-processing
     are chosen automatically from the model configuration.
@@ -722,7 +722,7 @@ def pose_3d(
     ) -> Pose3DResult:
         """Lift 2D keypoints to 3D using the flow-matching model.
 
-        **Human pipeline** (``model_type="fmpose3d"``):
+        **Human pipeline** (``model_type="fmpose3d_humans"``):
         Mirrors ``demo/vis_in_the_wild.py`` -- normalise screen
         coordinates, flip-augmented TTA, Euler ODE sampling, zero the
         root joint, ``camera_to_world``.

tests/test_fmpose3d.py

@@ -104,7 +104,7 @@ def forward(self, c_2d: torch.Tensor, y: torch.Tensor, t: torch.Tensor) -> torch
 
 
 def _make_ready_api(
-    model_type: str = "fmpose3d",
+    model_type: str = "fmpose3d_humans",
     test_augmentation: bool = False,
 ) -> FMPose3DInference:
     """Return an ``FMPose3DInference`` with a mock model pre-installed.
@@ -148,7 +148,7 @@ def animal_api() -> FMPose3DInference:
 @pytest.fixture
 def ready_human_api() -> FMPose3DInference:
     """Human API with mock model (TTA disabled)."""
-    return _make_ready_api("fmpose3d", test_augmentation=False)
+    return _make_ready_api("fmpose3d_humans", test_augmentation=False)
 
 
 @pytest.fixture
@@ -393,7 +393,7 @@ def test_animal(self):
 
 class TestFMPose3DInferenceInit:
     def test_default_human(self, human_api):
-        assert human_api.model_cfg.model_type == "fmpose3d"
+        assert human_api.model_cfg.model_type == "fmpose3d_humans"
         assert human_api._joints_left == [4, 5, 6, 11, 12, 13]
         assert human_api._joints_right == [1, 2, 3, 14, 15, 16]
         assert human_api._root_joint == 0
@@ -645,7 +645,7 @@ def test_progress_callback(self, ready_human_api):
 
     def test_tta_path_produces_output(self):
         """Test-time augmentation (flip) path produces correct shapes."""
-        api = _make_ready_api("fmpose3d", test_augmentation=True)
+        api = _make_ready_api("fmpose3d_humans", test_augmentation=True)
         kpts = np.random.randn(1, 17, 2).astype("float32")
         result = api.pose_3d(kpts, image_size=(480, 640), seed=42)
         assert result.poses_3d.shape == (1, 17, 3)
@@ -660,7 +660,7 @@ def test_animal_api_shapes(self):
 
     def test_predict_end_to_end_with_mock_estimator(self):
         """predict() chains prepare_2d → pose_3d correctly."""
-        api = _make_ready_api("fmpose3d", test_augmentation=False)
+        api = _make_ready_api("fmpose3d_humans", test_augmentation=False)
 
         mock_kpts = np.random.randn(1, 1, 17, 2).astype("float32")
         mock_scores = np.ones((1, 1, 17), dtype="float32")