Data type error

In the pre-processing sample code snippet:

# input
image_data = preprocess(image)
image_size = np.array([image.size[1], image.size[0]], dtype=np.int32).reshape(1, 2)

image size variable type is set to int32 as:

image_size = np.array([image.size[1], image.size[0]], **dtype=np.int32**).reshape(1, 2)

But tiny Yolo V3 model's input data types are float32. Above (current sample) code gives following error:

    boxes, scores, indices = session.run(None, {"input_1": imgData, "image_shape":imgSize})
  File "/opt/miniconda/lib/python3.7/site-packages/onnxruntime/capi/session.py", line 142, in run
    return self._sess.run(output_names, input_feed, run_options)
onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Unexpected input data type. Actual: (N11onnxruntime17PrimitiveDataTypeIiEE) , expected: (N11onnxruntime17PrimitiveDataTypeIfEE)

Correct sample code should be:

# input
image_data = preprocess(image)
image_size = np.array([image.size[1], image.size[0]], dtype=np.float32).reshape(1, 2)

Start from the pre-processing sample code shown in the issue and check the dtype used for image_size before the session.run call. Update the sample so its input type matches the model, then run the tiny YOLO V3 inference sample and confirm the input data type error no longer occurs.