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Hello,
I try to run my single channel object detection model on the DL Workbench. For this I uploaded single channel jpg images. However. the backend part of the DL Workbench seems to recognize or load it as 3 channel input, because when I try to infer the model with the uploaded input data, I get the following Inference error:
[ ERROR ] Image shape (3, 192, 608) is not compatible with input shape [1, 1, 192, 608]! Make sure -i parameter is valid.
Traceback (most recent call last):
File "/usr/local/lib/python3.8/dist-packages/openvino/tools/benchmark/utils/inputs_filling.py", line 186, in get_image_tensors
images[b] = image
ValueError: could not broadcast input array from shape (3,192,608) into shape (1,192,608)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.8/dist-packages/openvino/tools/benchmark/main.py", line 375, in run
data_queue = get_input_data(paths_to_input, app_inputs_info)
File "/usr/local/lib/python3.8/dist-packages/openvino/tools/benchmark/utils/inputs_filling.py", line 113, in get_input_data
data[port] = get_image_tensors(image_mapping[info.name][:images_to_be_used_map[info.name]], info, batch_sizes_map[info.name])
File "/usr/local/lib/python3.8/dist-packages/openvino/tools/benchmark/utils/inputs_filling.py", line 188, in get_image_tensors
raise Exception(f"Image shape {image.shape} is not compatible with input shape {shape}! "
Exception: Image shape (3, 192, 608) is not compatible with input shape [1, 1, 192, 608]! Make sure -i parameter is valid.
I have made sure I saved the images as single channel images by converting them with openCV to grayscale. Attached I send you the corresponding server_log and a sample image of thos that I used.
Best Regards
Niclas
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Hi Niclas,
Thank you for reaching out to us.
We have replicated this issue using a single channel model (text-recognition-0012) with single channel .jpg images (grayscale) and we are also observing same errors as yours.
We are investigating this issue further and will update you at the earliest.
Regards,
Hairul
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Hi Niclas,
Apologies for the delayed response.
I've tested further using grayscale images with text-recognition-0012 and found an issue with OpenCV cv.imread() function. From my findings, a grayscale image will be read as a 3-chanelled image when using a default flag for cv.imread() function in /usr/local/lib/python3.8/dist-packages/openvino/tools/benchmark/utils/inputs_filling.py.
I've attempted a possible workaround by editing the cv.imread() function to use "-1" flag where OpenCV will retain the image shape so that it would not be read as a 3-chanelled image.
However, after changing the cv.imread(image) to cv.imread(image, -1) a different error occurs.
Original error when using cv.imread(image):
[ ERROR ] Image shape (32, 120, 3) is not compatible with input shape [1, 32, 120, 1]!
ValueError: could not broadcast input array from shape (32,120,3) into shape (32,120,1)
New error when using cv.imread(image, -1):
[ ERROR ] Image shape (32, 120) is not compatible with input shape [1, 32, 120, 1]!
ValueError: could not broadcast input array from shape (32,120) into shape (32,120,1)
Could you please provide the following information for further troubleshooting:
- How did you install OpenVINO™ Deep Learning Workbench (DL Workbench)?
- The DL Workbench version that you are using.
- Please share your single channel object detection model that you are running on DL Workbench.
Regards,
Hairul
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Hi Niclas,
Thank you for your question. If you need any additional information from Intel, please submit a new question as this thread is no longer being monitored.
Regards
Hairul

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