[GitHub] [incubator-mxnet] bgawrych edited a comment on issue #20066: Custom Image Decoder Implementation

[GitBox <gi...@apache.org>]

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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