It starts to work on Raspian Buster on Raspi. Then quits suddenly.
pi@raspberrypi:~/depthai $ python3 Herbieai.py
/home/pi/.local/lib/python3.7/site-packages/roboflowoak/pipe.py:105: RuntimeWarning: divide by zero encountered in true_divide
return 441.25 * 7.5 / disparity
INFERENCE TIME IN MS 2.858843744909289
PREDICTIONS [{‘x’: 149.0, ‘y’: 209.5, ‘width’: 298, ‘height’: 413, ‘depth’: 50.91346153846154, ‘confidence’: 0.0772705078125, ‘class’: ‘weed11rotation’}, {‘x’: 150.5, ‘y’: 232.5, ‘width’: 301, ‘height’: 367, ‘depth’: 50.91346153846154, ‘confidence’: 0.209716796875, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 6.446229981864568
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INFERENCE TIME IN MS 7.595693550285678
PREDICTIONS [{‘x’: 391.0, ‘y’: 185.0, ‘width’: 50, ‘height’: 236, ‘depth’: 220.625, ‘confidence’: 0.05255126953125, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 6.686025084326441
PREDICTIONS [{‘x’: 385.0, ‘y’: 217.0, ‘width’: 62, ‘height’: 290, ‘depth’: 220.625, ‘confidence’: 0.06048583984375, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.465658502028255
PREDICTIONS [{‘x’: 386.0, ‘y’: 237.5, ‘width’: 50, ‘height’: 345, ‘depth’: 220.625, ‘confidence’: 0.050323486328125, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.178217042323424
PREDICTIONS [{‘x’: 387.0, ‘y’: 209.5, ‘width’: 50, ‘height’: 299, ‘depth’: 220.625, ‘confidence’: 0.05279541015625, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 6.794177581810937
PREDICTIONS [{‘x’: 389.0, ‘y’: 210.5, ‘width’: 54, ‘height’: 295, ‘depth’: 220.625, ‘confidence’: 0.06475830078125, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 6.997340736118943
PREDICTIONS [{‘x’: 389.0, ‘y’: 209.5, ‘width’: 54, ‘height’: 293, ‘depth’: 206.8359375, ‘confidence’: 0.075927734375, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.046491037963285
PREDICTIONS [{‘x’: 388.5, ‘y’: 210.0, ‘width’: 55, ‘height’: 294, ‘depth’: 220.625, ‘confidence’: 0.059600830078125, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 6.802872115598274
PREDICTIONS [{‘x’: 388.5, ‘y’: 210.5, ‘width’: 55, ‘height’: 293, ‘depth’: 206.8359375, ‘confidence’: 0.0576171875, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.07701133522085
PREDICTIONS [{‘x’: 389.0, ‘y’: 210.0, ‘width’: 54, ‘height’: 292, ‘depth’: 157.58928571428572, ‘confidence’: 0.055328369140625, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 6.81629356366857
PREDICTIONS [{‘x’: 388.0, ‘y’: 210.0, ‘width’: 56, ‘height’: 292, ‘depth’: 220.625, ‘confidence’: 0.0654296875, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.119802275998805
PREDICTIONS [{‘x’: 388.5, ‘y’: 209.5, ‘width’: 55, ‘height’: 291, ‘depth’: 206.8359375, ‘confidence’: 0.0726318359375, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 6.832738729404712
PREDICTIONS [{‘x’: 388.0, ‘y’: 210.0, ‘width’: 56, ‘height’: 290, ‘depth’: 220.625, ‘confidence’: 0.06939697265625, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.133376305097256
PREDICTIONS [{‘x’: 388.0, ‘y’: 210.5, ‘width’: 56, ‘height’: 291, ‘depth’: 220.625, ‘confidence’: 0.07086181640625, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 6.789921081387349
PREDICTIONS [{‘x’: 388.0, ‘y’: 210.0, ‘width’: 56, ‘height’: 290, ‘depth’: 206.8359375, ‘confidence’: 0.0733642578125, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 6.821381872117305
PREDICTIONS [{‘x’: 388.0, ‘y’: 210.0, ‘width’: 56, ‘height’: 288, ‘depth’: 220.625, ‘confidence’: 0.076171875, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 6.874026291162911
PREDICTIONS [{‘x’: 388.0, ‘y’: 210.0, ‘width’: 56, ‘height’: 290, ‘depth’: 220.625, ‘confidence’: 0.0723876953125, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 6.726157467915154
PREDICTIONS [{‘x’: 385.5, ‘y’: 237.0, ‘width’: 61, ‘height’: 318, ‘depth’: 194.6691176470588, ‘confidence’: 0.0621337890625, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.416275015294738
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INFERENCE TIME IN MS 6.8705019001441485
PREDICTIONS [{‘x’: 39.5, ‘y’: 178.5, ‘width’: 79, ‘height’: 207, ‘depth’: 106.75403225806451, ‘confidence’: 0.06048583984375, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.082030102356115
PREDICTIONS [{‘x’: 47.0, ‘y’: 199.5, ‘width’: 92, ‘height’: 243, ‘depth’: 114.11637931034483, ‘confidence’: 0.07928466796875, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 6.931668355112355
PREDICTIONS [{‘x’: 37.0, ‘y’: 231.0, ‘width’: 74, ‘height’: 282, ‘depth’: 110.3125, ‘confidence’: 0.109619140625, ‘class’: ‘weed3rotation’}, {‘x’: 73.0, ‘y’: 205.0, ‘width’: 146, ‘height’: 272, ‘depth’: 110.3125, ‘confidence’: 0.1361083984375, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 6.916237799760241
PREDICTIONS [{‘x’: 82.0, ‘y’: 232.5, ‘width’: 164, ‘height’: 257, ‘depth’: 84.85576923076923, ‘confidence’: 0.054901123046875, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.294137288182754
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INFERENCE TIME IN MS 7.170816856523961
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INFERENCE TIME IN MS 6.905261216943499
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INFERENCE TIME IN MS 6.926196928188437
PREDICTIONS [{‘x’: 55.0, ‘y’: 365.0, ‘width’: 110, ‘height’: 102, ‘depth’: 66.1875, ‘confidence’: 0.066650390625, ‘class’: ‘weed3rotation’}, {‘x’: 321.5, ‘y’: 90.0, ‘width’: 167, ‘height’: 180, ‘depth’: 61.28472222222222, ‘confidence’: 0.070068359375, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.041735290908022
PREDICTIONS [{‘x’: 356.5, ‘y’: 284.5, ‘width’: 119, ‘height’: 263, ‘depth’: 52.529761904761905, ‘confidence’: 0.05242919921875, ‘class’: ‘weed3rotation’}, {‘x’: 111.0, ‘y’: 337.5, ‘width’: 218, ‘height’: 157, ‘depth’: 67.53826530612245, ‘confidence’: 0.099365234375, ‘class’: ‘weed3rotation’}, {‘x’: 46.5, ‘y’: 252.0, ‘width’: 93, ‘height’: 230, ‘depth’: 67.53826530612245, ‘confidence’: 0.08966064453125, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.085308088896096
PREDICTIONS [{‘x’: 201.0, ‘y’: 358.0, ‘width’: 188, ‘height’: 116, ‘depth’: 53.377016129032256, ‘confidence’: 0.05926513671875, ‘class’: ‘weed3rotation’}, {‘x’: 87.0, ‘y’: 343.5, ‘width’: 174, ‘height’: 145, ‘depth’: 56.09110169491525, ‘confidence’: 0.057037353515625, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 6.814898100773242
PREDICTIONS [{‘x’: 286.0, ‘y’: 355.5, ‘width’: 172, ‘height’: 121, ‘depth’: 54.252049180327866, ‘confidence’: 0.0682373046875, ‘class’: ‘weed3rotation’}, {‘x’: 114.5, ‘y’: 366.5, ‘width’: 229, ‘height’: 97, ‘depth’: 57.05818965517241, ‘confidence’: 0.0562744140625, ‘class’: ‘weed3rotation’}, {‘x’: 368.5, ‘y’: 279.5, ‘width’: 93, ‘height’: 263, ‘depth’: 49.39365671641791, ‘confidence’: 0.054595947265625, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.060012489627045
PREDICTIONS [{‘x’: 361.0, ‘y’: 301.0, ‘width’: 106, ‘height’: 230, ‘depth’: 44.72128378378378, ‘confidence’: 0.052947998046875, ‘class’: ‘weed3rotation’}, {‘x’: 124.0, ‘y’: 344.0, ‘width’: 222, ‘height’: 144, ‘depth’: 55.15625, ‘confidence’: 0.07647705078125, ‘class’: ‘weed3rotation’}, {‘x’: 49.5, ‘y’: 56.0, ‘width’: 99, ‘height’: 106, ‘depth’: 49.39365671641791, ‘confidence’: 0.06634521484375, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.133267119280535
PREDICTIONS [{‘x’: 184.5, ‘y’: 345.5, ‘width’: 203, ‘height’: 141, ‘depth’: 39.39732142857143, ‘confidence’: 0.05096435546875, ‘class’: ‘weed3rotation’}, {‘x’: 233.5, ‘y’: 29.5, ‘width’: 209, ‘height’: 59, ‘depth’: 39.39732142857143, ‘confidence’: 0.054901123046875, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.376597795271159
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INFERENCE TIME IN MS 7.040328726286353
PREDICTIONS [{‘x’: 361.5, ‘y’: 300.0, ‘width’: 103, ‘height’: 232, ‘depth’: 34.83552631578947, ‘confidence’: 0.061309814453125, ‘class’: ‘weed3rotation’}, {‘x’: 307.5, ‘y’: 304.0, ‘width’: 185, ‘height’: 224, ‘depth’: 35.2061170212766, ‘confidence’: 0.0806884765625, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.299341819029818
PREDICTIONS [{‘x’: 360.0, ‘y’: 320.0, ‘width’: 106, ‘height’: 192, ‘depth’: 34.83552631578947, ‘confidence’: 0.056732177734375, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.54582940537273
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INFERENCE TIME IN MS 6.897516646411956
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INFERENCE TIME IN MS 7.35451856293935
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INFERENCE TIME IN MS 7.2371611816733985
PREDICTIONS [{‘x’: 307.0, ‘y’: 175.0, ‘width’: 218, ‘height’: 98, ‘depth’: 34.83552631578947, ‘confidence’: 0.0625, ‘class’: ‘weed11rotation’}, {‘x’: 344.0, ‘y’: 174.5, ‘width’: 144, ‘height’: 95, ‘depth’: 34.83552631578947, ‘confidence’: 0.10101318359375, ‘class’: ‘weed3rotation’}]
INFERENCE TIME IN MS 7.248480072444984
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INFERENCE TIME IN MS 7.405838428818877
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INFERENCE TIME IN MS 7.5265068521419565
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INFERENCE TIME IN MS 7.911348019382718
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INFERENCE TIME IN MS 7.567298792820067
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INFERENCE TIME IN MS 7.918173477362915
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Traceback (most recent call last):
File “Herbieai.py”, line 16, in
result, frame, raw_frame, depth = rf.detect(visualize=True)
File “/home/pi/.local/lib/python3.7/site-packages/roboflowoak/init.py”, line 63, in detect
ret = self.dai_pipe.get()
File “/home/pi/.local/lib/python3.7/site-packages/roboflowoak/pipe.py”, line 128, in get
in_det = self.q_det.get()
RuntimeError: Communication exception - possible device error/misconfiguration. Original message ‘Couldn’t read data from stream: ‘nn’ (X_LINK_ERROR)’
pi@raspberrypi:~/depthai $