bgawrych edited a comment on issue #20066:
URL:
https://github.com/apache/incubator-mxnet/issues/20066#issuecomment-804675928
NDArray is object describing array, but under the hood it contains normal
memory. You can access this memory by calling i.e:
```
int16_t* in_ptr = in_data.dptr<int16_t>();
```
(bsaed on example)
All offsets of different dimensions you can deduce by calling proper ndarray
functions.
You can also utilize numpy array to create mxnet's ndarray
```
from jpeg2dct.numpy import load, loads
import mxnet as mx
#read from a file
jpeg_file = 'test.jpg'
dct_y, dct_cb, dct_cr = load(jpeg_file)
print ("Y component DCT shape {} and type {}".format(dct_y.shape,
dct_y.dtype))
print ("Cb component DCT shape {} and type {}".format(dct_cb.shape,
dct_cb.dtype))
print ("Cr component DCT shape {} and type {}".format(dct_cr.shape,
dct_cr.dtype))
print(type(dct_cr))
print(dct_cr)
mxnet_array = mx.nd.array(dct_cr)
print(mxnet_array.shape)
print(type(mxnet_array))
print(mxnet_array)
```
However if you wish to load file directly and operate on bytes you can check
this operator:
https://github.com/apache/incubator-mxnet/blob/9de2a48fabf1b8a60eb539640dea4c0637b5522b/src/io/image_io.cc#L371
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