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Opencv version issue?
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lines changed

4 files changed

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.conda/naps-track/bld.bat

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@@ -4,8 +4,8 @@ set PIP_NO_INDEX=False
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set PIP_NO_DEPENDENCIES=False
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set PIP_IGNORE_INSTALLED=False
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pip install opencv-python-headless
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pip install opencv-contrib-python-headless
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pip install opencv-python-headless==4.6.0.66
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pip install opencv-contrib-python-headless=4.6.0.66
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pip install numpy==1.19.5
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pip install attrs==21.2.0
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pip install wheel==0.35

.conda/naps-track/build.sh

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@@ -4,8 +4,8 @@ export PIP_NO_INDEX=False
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export PIP_NO_DEPENDENCIES=False
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export PIP_IGNORE_INSTALLED=False
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pip install opencv-python-headless
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pip install opencv-contrib-python-headless
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pip install opencv-python-headless==4.6.0.66
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pip install opencv-contrib-python-headless=4.6.0.66
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pip install numpy==1.19.5
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pip install attrs==21.2.0
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pip install wheel==0.35

naps/__init__.py

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@@ -6,7 +6,7 @@
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# Basic Information
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__name__ = "naps-track"
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__version__ = "1.0.5"
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__version__ = "1.0.6"
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__summary__ = "NAPS (NAPS is ArUco Plus SLEAP)"
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__url__ = "https://github.com/kocherlab/naps"
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__code__ = "https://github.com/kocherlab/naps"

naps/naps_track.py

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@@ -60,6 +60,13 @@ def build_parser():
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required=True,
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)
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parser.add_argument(
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"--aruco-marker-set",
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help="The ArUco markers used in the video. This must match the specific set of ArUco markers used in the video for accurate detection and tracking. An example would be DICT_5X5_50, which is a set of 50 5x5 markers. More information can be found in the OpenCV documentation.",
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type=str,
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required=True,
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)
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parser.add_argument(
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"--half-rolling-window-size",
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help="Specifies the number of flanking frames (prior and subsequent) required in the rolling window for Hungarian matching a frame. The larger this window, the more frames will be used for matching. This can result in more robust tracks but in the event of an identity swap, it may take longer to correct the identity. The default is set to 5, resulting in an 11 frame window. You should change this depending on your intended use and your recording setup. ",
@@ -80,13 +87,6 @@ def build_parser():
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type=int,
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)
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parser.add_argument(
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"--aruco-marker-set",
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help="The ArUco markers used in the video. This must match the specific set of ArUco markers used in the video for accurate detection and tracking. An example would be DICT_5X5_50, which is a set of 50 5x5 markers. More information can be found in the OpenCV documentation.",
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type=str,
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required=True,
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)
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parser.add_argument(
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"--aruco-adaptive-thresh-win-size-min",
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dest="adaptiveThreshWinSizeMin",

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