Expand Up @@ -401,7 +401,7 @@ dynamic: triple containing (state, detectiontreshold, margin)
If the state is true, then dynamic cropping will be performed. That means that if an object is detected (i.e., any body part > detectiontreshold), then object boundaries are computed according to the smallest/largest x position and smallest/largest y position of all body parts. This window is expanded by the margin and from then on only the posture within this crop is analyzed (until the object is lost; i.e., <detectiontreshold). The current position is utilized for updating the crop window for the next frame (this is why the margin is important and should be set large enough given the movement of the animal). ``` ### (J) Filter pose data data (RECOMMENDED!): ### (J) Filter pose data (RECOMMENDED!):
You can also filter the predictions with a median filter (default) or with a [SARIMAX model](https://www.statsmodels.org/dev/generated/statsmodels.tsa.statespace.sarimax.SARIMAX.html), if you wish. This creates a new .h5 file with the ending *_filtered* that you can use in create_labeled_data and/or plot trajectories. ```python Expand Down