Load Numpy arrays of incompatible dtypes

[souravraha]

What does this PR do?

Handles the loading of .npy images of integer data-types better. Previously, the ndarrays would be unsafely cast into 'uint8'. If the original dtype were, say 'int64', the loaded PIL Image would be different from what was intended.

Now it should throw up a warning whenever there is unsafe casting. In addition, it would attempt to load a float ndarray (instead of possibly an integer array). The latter is needed as PIL can readily import from float64 ndarrays (but not, say int64 ndarrays).

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[souravraha]

The old contribution is discarded, as it was failing a required test.

Now, the pixel values are scaled linearly to lie in between 0 and 255. This ensures minimal losses while loading an ndarray of dtype int64 to a PIL image. The downside for this is that every ndarray would get scaled differently, i.e. this is a sample specific scaling (rather than, say a global scaling for samples of the entire dataset).

[codecov]

Codecov Report

Merging #1507 (a093de1) into master (8ad3a96) will decrease coverage by 3%.
The diff coverage is 60%.

Additional details and impacted files

@@           Coverage Diff           @@
##           master   #1507    +/-   ##
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- Coverage      85%     83%    -3%     
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  Files         291     291            
  Lines       12852   12856     +4     
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- Hits        10982   10609   -373     
- Misses       1870    2247   +377