Pip install RoboFlowOak error

ted@ted-desktop:~$ pip install roboflowoak
Defaulting to user installation because normal site-packages is not writeable
Collecting roboflowoak
Downloading roboflowoak-0.0.2.tar.gz (6.5 kB)
Preparing metadata (setup.py) … error
error: subprocess-exited-with-error

× python setup.py egg_info did not run successfully.
│ exit code: 1
╰─> [6 lines of output]
Traceback (most recent call last):
File “”, line 2, in
File “”, line 34, in
File “/tmp/pip-install-qp9feet9/roboflowoak_e3b0470b5ae64b31a6763dbc67c216c3/setup.py”, line 5, in
with open(“README-dist.md”, “r”) as fh:
FileNotFoundError: [Errno 2] No such file or directory: ‘README-dist.md’
[end of output]

note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details.

install roboflowoak didnt work.txt
This was on Ubuntu 22 Jammy on Raspberry Pi

pi@raspberrypi:~ $ pip install roboflowoak
Defaulting to user installation because normal site-packages is not writeable
Looking in indexes: Simple index, piwheels - Simple index
Collecting roboflowoak
Downloading roboflowoak-0.0.2.tar.gz (6.5 kB)
Preparing metadata (setup.py) … error
error: subprocess-exited-with-error

× python setup.py egg_info did not run successfully.
│ exit code: 1
╰─> [6 lines of output]
Traceback (most recent call last):
File “”, line 36, in
File “”, line 34, in
File “/tmp/pip-install-wc9s_nk4/roboflowoak_179c7af25b6d4b1b95cea040f985d551/setup.py”, line 5, in
with open(“README-dist.md”, “r”) as fh:
FileNotFoundError: [Errno 2] No such file or directory: ‘README-dist.md’
[end of output]

note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details.
WARNING: You are using pip version 22.0.4; however, version 22.1 is available.
You should consider upgrading via the ‘/usr/bin/python3 -m pip install --upgrade pip’ command.
pi@raspberrypi:~ $ ^C
pi@raspberrypi:~ $

This was on Raspian Buster on Raspberry Pi

rod@rod-HP-Pavilion-Laptop-15-eh0xxx:~$ pip install roboflowoak
Collecting roboflowoak
Downloading roboflowoak-0.0.2.tar.gz (6.5 kB)
ERROR: Command errored out with exit status 1:
command: /usr/bin/python3 -c ‘import sys, setuptools, tokenize; sys.argv[0] = ‘"’"’/tmp/pip-install-uymil8ep/roboflowoak/setup.py’"’"’; file=’"’"’/tmp/pip-install-uymil8ep/roboflowoak/setup.py’"’"’;f=getattr(tokenize, ‘"’"‘open’"’"’, open)(file);code=f.read().replace(’"’"’\r\n’"’"’, ‘"’"’\n’"’"’);f.close();exec(compile(code, file, ‘"’"‘exec’"’"’))’ egg_info --egg-base /tmp/pip-install-uymil8ep/roboflowoak/pip-egg-info
cwd: /tmp/pip-install-uymil8ep/roboflowoak/
Complete output (5 lines):
Traceback (most recent call last):
File “”, line 1, in
File “/tmp/pip-install-uymil8ep/roboflowoak/setup.py”, line 5, in
with open(“README-dist.md”, “r”) as fh:
FileNotFoundError: [Errno 2] No such file or directory: ‘README-dist.md’
----------------------------------------
ERROR: Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.
rod@rod-HP-Pavilion-Laptop-15-eh0xxx:~$

This was on HP laptop with Ubuntu Focal

This category is for question related to accounts on https://app.roboflow.com/

Please share the following so we may better assist you:

  1. Project type (Object detection, Classification, Polygon, etc.)
  2. The operating system & browser you are using and their versions
  3. The screenshot of the error being triggered in your browser’s developer tools/console. Please copy/paste the url below to watch how to pull up your devtools

Hello @Russ76! Thank you for the detailed error report, we have pushed a version to address these issues. Could you try pip install -u roboflowoak?

Will get to that about 8 PM Central, thanks!

I had to use capital U, not small u.
There yet seems to be an error. In the Python script to run the model, it says “Choose-a-device-name” is that where it should say “Oak”?

rod@rod-HP-Pavilion-Laptop-15-eh0xxx:~/depthai$ python3 Herbieai.py
Traceback (most recent call last):
File “Herbieai.py”, line 9, in
rf = RoboflowOak(model=“https://detect.roboflow.com/yardbot-weeds”, confidence=0.05, overlap=0.5,
File “/home/rod/.local/lib/python3.8/site-packages/roboflowoak/init.py”, line 31, in init
self.cache_path = self.find_weights()
File “/home/rod/.local/lib/python3.8/site-packages/roboflowoak/init.py”, line 59, in find_weights
return download_blob(self.project, self.version, self.api_key, self.dev)
File “/home/rod/.local/lib/python3.8/site-packages/roboflowoak/api.py”, line 21, in download_blob
model_objects[‘class_names’] = api_data[‘oak’][‘classes’]
KeyError: ‘oak’
rod@rod-HP-Pavilion-Laptop-15-eh0xxx:~/depthai$

Hi @Russ76 you can choose any device name you’d like.

And the install should work with pip install --upgrade roboflowoak or pip install -U roboflowoak if you already had the previous version of the package installed. pip install roboflowoak is the code to use if you didn’t yet have it installed in your Python environment.

Here is an example of my script (API key removed):
image

To add more color, this is to support future device management functionality to do things like monitor your devices’ uptime, visualize their predictions, associate uploaded images from the edge, etc.

This is still all it will do, pointing to some error in the api.py file. Each of my three machines will run the depthai demo, but will not run the Roboflow Oak model. Am I doing something wrong?

rod@rod-HP-Pavilion-Laptop-15-eh0xxx:~/depthai$ python3 Herbieai.py
Traceback (most recent call last):
File “Herbieai.py”, line 9, in
rf = RoboflowOak(model=“https://detect.roboflow.com/yardbot-weeds”, confidence=0.05, overlap=0.5,
File “/home/rod/.local/lib/python3.8/site-packages/roboflowoak/init.py”, line 31, in init
self.cache_path = self.find_weights()
File “/home/rod/.local/lib/python3.8/site-packages/roboflowoak/init.py”, line 59, in find_weights
return download_blob(self.project, self.version, self.api_key, self.dev)
File “/home/rod/.local/lib/python3.8/site-packages/roboflowoak/api.py”, line 21, in download_blob
model_objects[‘class_names’] = api_data[‘oak’][‘classes’]
KeyError: ‘oak’

@Russ76 are you pointing to a model version that has been trained with Roboflow Train? It will need a trained model to work.

Additionally, your model/project ID should be in the code as model=yardbot-weeds (this is what you would input if your project ID is yardbot-weeds.

Yes, that was it. I had the complete web address there, not just the model name. It works!

However, on Raspberry Pi with Ubuntu Jammy, this happens!

ted@ted-desktop:~/depthai/depthai-main$ python3 Herbieai.py
Traceback (most recent call last):
File “/home/ted/depthai/depthai-main/Herbieai.py”, line 16, in
result, frame, raw_frame, depth = rf.detect(visualize=True)
File “/home/ted/.local/lib/python3.10/site-packages/roboflowoak/init.py”, line 63, in detect
ret = self.dai_pipe.get()
File “/home/ted/.local/lib/python3.10/site-packages/roboflowoak/pipe.py”, line 130, in get
detections = self.post_processing(in_det)
File “/home/ted/.local/lib/python3.10/site-packages/roboflowoak/pipe.py”, line 206, in post_processing
in_nn_layer = in_det.getLayerFp16(‘output’)
AttributeError: ‘depthai.ADatatype’ object has no attribute ‘getLayerFp16’
Stack trace (most recent call last):
#20 Object “[0xffffffffffffffff]”, at 0xffffffffffffffff, in
#19 Object “python3”, at 0xaaaad0bea62f, in _start
#18 Object “/lib/aarch64-linux-gnu/libc.so.6”, at 0xffffbef874cb, in __libc_start_main
#17 Object “/lib/aarch64-linux-gnu/libc.so.6”, at 0xffffbef873fb, in
#16 Object “python3”, at 0xaaaad0bea747, in Py_BytesMain
#15 Object “python3”, at 0xaaaad0c1bfa3, in Py_RunMain
#14 Object “python3”, at 0xaaaad0c2f067, in Py_FinalizeEx
#13 Object “python3”, at 0xaaaad0c32a07, in
#12 Object “python3”, at 0xaaaad0adfe77, in
#11 Object “python3”, at 0xaaaad0c330db, in
#10 Object “python3”, at 0xaaaad0aef283, in
#9 Object “python3”, at 0xaaaad0aef4f7, in
#8 Object “python3”, at 0xaaaad0b3048f, in
#7 Object “python3”, at 0xaaaad0aef3b3, in
#6 Object “python3”, at 0xaaaad0b3048f, in
#5 Object “python3”, at 0xaaaad0aef3b3, in
#4 Object “/home/ted/.local/lib/python3.10/site-packages/depthai.cpython-310-aarch64-linux-gnu.so”, at 0xffffbd7baabf, in
#3 Object “/home/ted/.local/lib/python3.10/site-packages/depthai.cpython-310-aarch64-linux-gnu.so”, at 0xffffbd87a607, in
#2 Object “/home/ted/.local/lib/python3.10/site-packages/depthai.cpython-310-aarch64-linux-gnu.so”, at 0xffffbda0df83, in dai::DataOutputQueue::~DataOutputQueue()
#1 Object “/home/ted/.local/lib/python3.10/site-packages/depthai.cpython-310-aarch64-linux-gnu.so”, at 0xffffbda0af57, in
#0 Object “/home/ted/.local/lib/python3.10/site-packages/depthai.cpython-310-aarch64-linux-gnu.so”, at 0xffffbdb1b38c, in
Segmentation fault (Address not mapped to object [0x60006003c])
Segmentation fault (core dumped)

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
PREDICTIONS
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
PREDICTIONS
INFERENCE TIME IN MS 7.231845400765892
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INFERENCE TIME IN MS 7.159959030385798
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INFERENCE TIME IN MS 7.07955567783436
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INFERENCE TIME IN MS 7.231084859957451
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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
PREDICTIONS
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 7.608328284459021
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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 $

Is that using the RGB camera? I need to use the full width of RGB camera to get image for robot. It is mounted about 18 inches high and picks up an image 20 inches wide. And I’d like to limit the height of image to 300 pixels.