Fixed running custom onnx models.
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@@ -4,8 +4,12 @@ xhost +
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docker run --privileged --rm --network host -it \
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--gpus all --shm-size=16g --ulimit memlock=-1 --ulimit stack=67108864 \
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--volume "$(pwd)"/:/RapidPoseTriangulation/ \
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--volume "$(pwd)"/extras/easypose/pipeline.py:/EasyPose/easypose/pipeline.py \
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--volume "$(pwd)"/extras/easypose/detection.py:/EasyPose/easypose/model/detection.py \
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--volume "$(pwd)"/extras/easypose/pose.py:/EasyPose/easypose/model/pose.py \
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--volume "$(pwd)"/extras/easypose/utils.py:/EasyPose/easypose/model/utils.py \
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--volume "$(pwd)"/../datasets/:/datasets/ \
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--volume "$(pwd)"/../skelda/:/skelda/ \
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--volume "$(pwd)"/skelda/:/skelda/ \
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--volume /tmp/.X11-unix:/tmp/.X11-unix \
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--env DISPLAY --env QT_X11_NO_MITSHM=1 \
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rpt_easypose
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