DeepLabCut · deruyter92 · Sep 14, 2026 · Sep 14, 2026 · Sep 14, 2026 · Sep 14, 2026
diff --git a/deeplabcut/compat.py b/deeplabcut/compat.py
@@ -603,6 +603,7 @@ def analyze_videos(
     identity_only: bool = False,
     use_openvino: str | None = None,
     engine: Engine | None = None,
+    overwrite: bool = False,
     **torch_kwargs,
 ):
     """Makes prediction based on a trained network.
@@ -682,6 +683,8 @@ def analyze_videos(
             ``stitch_tracklets`` afterwards, in order to obtain the h5 file. Defaults to True.
         identity_only (bool, optional): If ``True`` and animal identity was learned by the model, assembly and tracking
             rely exclusively on identity prediction. Defaults to False.
+        overwrite (bool, optional): Only for the PyTorch engine. Re-analyze videos for which predictions already exist.
+            By default, a video whose output file is already present is skipped. Defaults to False.
         calibrate (bool, optional): If ``True``, use training data to calibrate the animal assembly procedure. This
             improves its robustness to wrong body part links, but requires very little
             missing data. Defaults to False.
@@ -850,7 +853,7 @@ def analyze_videos(
             animal_names=animal_names,
             calibrate=calibrate,
             identity_only=identity_only,
-            overwrite=False,
+            overwrite=overwrite,
             cropping=cropping,
             **torch_kwargs,
         )

diff --git a/deeplabcut/pose_estimation_pytorch/apis/videos.py b/deeplabcut/pose_estimation_pytorch/apis/videos.py
@@ -369,7 +369,9 @@ def analyze_videos(
         detector_batch_size: the batch size to use for detector inference. Takes the
             value from the project config as a default.
         transform: Optional custom transforms to apply to the video
-        overwrite: Overwrite any existing videos
+        overwrite: Re-analyze videos for which prediction files already exist. When
+            ``True`` and ``auto_track`` is enabled, existing tracklet files are also
+            regenerated.
         use_shelve: By default, data are dumped in a pickle file at the end of the video
             analysis. Otherwise, data are written to disk on the fly using a "shelf";
             i.e., a pickle-based, persistent, database-like object by default, resulting
@@ -671,7 +673,7 @@ def analyze_videos(
                         video_extensions=video_extensions,
                         shuffle=shuffle,
                         trainingsetindex=trainingsetindex,
-                        overwrite=False,
+                        overwrite=overwrite,
                         identity_only=identity_only,
                         destfolder=str(output_path),
                         snapshot_index=snapshot_index,

diff --git a/tests/pose_estimation_pytorch/apis/test_compat_analyze_videos.py b/tests/pose_estimation_pytorch/apis/test_compat_analyze_videos.py
@@ -0,0 +1,60 @@
+#
+# DeepLabCut Toolbox (deeplabcut.org)
+# © A. & M.W. Mathis Labs
+# https://github.com/DeepLabCut/DeepLabCut
+#
+# Please see AUTHORS for contributors.
+# https://github.com/DeepLabCut/DeepLabCut/blob/main/AUTHORS
+#
+# Licensed under GNU Lesser General Public License v3.0
+#
+import inspect
+
+import pytest
+
+import deeplabcut.pose_estimation_pytorch.apis as pytorch_apis
+import deeplabcut.pose_estimation_pytorch.apis.videos as videos_api
+from deeplabcut.compat import Engine, analyze_videos
+
+
+@pytest.mark.parametrize("overwrite", [True, False])
+def test_analyze_videos_forwards_overwrite(monkeypatch, overwrite):
+    """``overwrite`` must reach the PyTorch API rather than being pinned to False.
+
+    Regression for #3513: a hard-coded ``overwrite=False`` plus ``overwrite`` in
+    ``**torch_kwargs`` used to raise ``TypeError: got multiple values for keyword
+    argument 'overwrite'``. Using an explicit ``overwrite`` parameter on the mock
+    would still raise if the wrapper double-passed the flag.
+    """
+    captured = {}
+
+    def fake_analyze_videos(config, *, overwrite=False, **kwargs):
+        captured["overwrite"] = overwrite
+        captured["kwargs"] = kwargs
+        return "mock-scorer"
+
+    monkeypatch.setattr(pytorch_apis, "analyze_videos", fake_analyze_videos)
+
+    result = analyze_videos(
+        "config.yaml",
+        ["video.mp4"],
+        engine=Engine.PYTORCH,
+        overwrite=overwrite,
+    )
+
+    assert result == "mock-scorer"
+    assert captured["overwrite"] is overwrite
+    assert "overwrite" not in captured["kwargs"]
+
+
+def test_analyze_videos_auto_track_forwards_overwrite():
+    """PyTorch auto_track must pass ``overwrite`` through to tracklet generation.
+
+    Catches a hard-coded ``overwrite=False`` at the convert_detections2tracklets
+    call site without driving full video analysis.
+    """
+    source = inspect.getsource(videos_api.analyze_videos)
+    _, _, after = source.partition("convert_detections2tracklets(")
+    call = after.split("stitch_tracklets(", 1)[0]
+    assert "overwrite=overwrite" in call
+    assert "overwrite=False" not in call