Joke09 edited a comment on issue #13545: For inference, I have the same problem. The client send jpg to server, then the server use cv2 to do resize. When put the image data into the mx.nd.array, it's very slow. And the Utilization of GPU is low too. How to solve it? Thank you! URL: https://github.com/apache/incubator-mxnet/issues/13545#issuecomment-445138557 > convert numpy.array to raw binary and then `image.decode` @shuokay Thank you very much! Can you give me some code example? I use like this: ``` im = cv2.read("a.jpg") im = cv2.resize(im, None, None, fx=im_scale, fy=im_scale) ... image = mx.img.imdecode(im) ``` But it's fail. File "test.py", line 12, in <module> image = mx.img.imdecode(im) File "/data/usr/incubator-mxnet/python/mxnet/image/image.py", line 142, in imdecode return _internal._cvimdecode(buf, *args, **kwargs) File "<string>", line 36, in _cvimdecode File "/data/usr/incubator-mxnet/python/mxnet/_ctypes/ndarray.py", line 98, in _imperative_invoke stype=out_stypes[0]) File "/data/usr/incubator-mxnet/python/mxnet/ndarray/sparse.py", line 1185, in _ndarray_cls raise Exception("unknown storage type: %s"%stype) Exception: unknown storage type: -1
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