11 years of writing phone apps have convinced lions the best way to configure a phone app is a text file in a text editor.

So the tracking program being dual purpose required a configuration bit, if truck is 0 it reads configuration from the GUI.  If truck is 1, it reads configuration from the text file.  It seems easiest, since the 2 axis configuration depends on visual feedback on the GUI as the user manually moves the servos.  The 1 axis configuration doesn't need any GUI feedback.

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Another test run detected more trees than lion.  The COCO dataset all the pretrained models use seems to have animals who look like trees.  Tracking always stopped short of the subject, possibly because the body_25 hit box is too wide. 

Most tracked footage would be better off in manual mode.  Tracking is only needed when the truck turns & when the lion moves relative to the truck.  Most of the time, lions are in a fixed position relative to the truck. 

Other than the auto tracker issue, the other problems were the camera remote needing a power switch protector, the camera receiver's long standing frequency hopping bug getting really debilitating when using motion control.  Maybe it's worth putting in another switch or button to select motion control or manual control.

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The idea occurred of creating a separate color histogram for each body part & using the histograms of all the body parts to recognize a lion in a crowd.  Multiple body parts could enhance the detection.  There isn't going to be anything more reliable than color histograms & identification of any kind might just require wearing differentiating colors.  It might be better off using a contour model.

When only 1 animal is visible, it could constantly update its histogram table.

Testing it is the real problem.  Lions just aren't around crowds except very rare cases. They could deliberately walk around the shopping mall just for testing.

There was a new development in the announcement of a future raspberry pi 5.  This one goes at 2.4Ghz, thus taking efficientdet-lite to 11fps & increasing the reserve for chroma keying.  The jetson's power consumption & size have been disappointing.  TensorRT has proven to be a waste of time.