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Hello,
I am new to this environment. I am trying to use one of the intel pretrained models provided. "vehicle-license-plate-detection-barrier-0106". I want to execute it on NCS2
below is my code:
import cv2
ARCH_FPATH = 'vehicle-license-plate-detection-barrier-0106.xml'
MODEL_FPATH = 'vehicle-license-plate-detection-barrier-0106.bin'
IMG_FPATH = 'car.jpeg'
net = cv2.dnn.readNet(ARCH_FPATH, MODEL_FPATH)
net.setPreferableBackend(cv2.dnn.DNN_BACKEND_INFERENCE_ENGINE)
net.setPreferableTarget(cv2.dnn.DNN_TARGET_MYRIAD)
img = cv2.imread(IMG_FPATH)
blob = cv2.dnn.blobFromImage(img)
net.setInput(blob)
out = net.forward()
Here I am getting error message:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
cv2.error: Check 'input_product.get_length() % output_product.get_length() == 0' failed at C:\j\workspace\private-ci\ie\build-windows-vs2019\b\repos\openvino\ngraph\core\src\op\reshape.cpp:334:
While validating node 'v1::Reshape SSD/concat_reshape_softmax/mbox_loc_final (SSD/concat_reshape_softmax/mbox_loc[0]:f16{1,12204}, SSD/concat_reshape_softmax/mbox_loc_final/shape[0]:i64{3}) -> (f16{?,?,?})' with friendly_name 'SSD/concat_reshape_softmax/mbox_loc_final':
Non-'-1' output dimensions do not evenly divide the input dimensions
Could someone please help me with it and let me know the issue. Thanks in advance.
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Hello Rohit,
Thank you for reaching out to us.
I faced the same issue when running the vehicle-license-plate-detection-barrier-0106 pre-trained model using the script you’ve shared.
My suggestion is that you can run the license-plate-detection-barrier-0106 pre-trained model with Object Detection Python Demo and use Myriad as a target device.
Sincerely,
Zulkifli
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Hello Rohit,
This thread will no longer be monitored since we have provided a solution. If you need any additional information from Intel, please submit a new question.
Sincerely,
Zulkifli
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