I uploaded and converted an onnx model to IR format using the Openvino DL Workbench. For input data I chose the gray scale images I used when training the network also, and uploaded 100 of them packed in a zip structure. When trying inference, following Error occurs:
[ ERROR ] 'NoneType' object has no attribute 'shape' 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 155, in get_image_tensors if image.shape[:-1] != new_im_size: AttributeError: 'NoneType' object has no attribute 'shape'
I attached the corresponding server_log.
For further information if useful: Before I used the default images which got rejected for another error because of having three channels (not grayscale) while my network is using 1 channel as input.
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For sharing purposes, the Not Annotated Datasets uses .jpg image format. The archive for not annotated dataset is organized as follows:
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