Support for GeoTIFF images

Is this a new feature, an improvement, or a change to existing functionality?

Improvement

How would you describe the priority of this feature request

Must have (e.g. DALI adoption is impossible due to lack in functionality).

Please provide a clear description of problem this feature solves

I am working on a geospatial application that requires decoding GeoTIFF files. This format does not seem to be supported by DALI. You can see the warnings when decoding such a file with DALI as well as some statistics computed on the result.

original.tif

TIFFReadDirectory: Warning, Unknown field with tag 33550 (0x830e) encountered.
TIFFReadDirectory: Warning, Unknown field with tag 33922 (0x8482) encountered.
TIFFReadDirectory: Warning, Unknown field with tag 34735 (0x87af) encountered.
TIFFReadDirectory: Warning, Unknown field with tag 34736 (0x87b0) encountered.
TIFFReadDirectory: Warning, Unknown field with tag 34737 (0x87b1) encountered.
TIFFReadDirectory: Warning, Unknown field with tag 33550 (0x830e) encountered.
TIFFReadDirectory: Warning, Unknown field with tag 33922 (0x8482) encountered.
TIFFReadDirectory: Warning, Unknown field with tag 34735 (0x87af) encountered.                                                                                                                                            
TIFFReadDirectory: Warning, Unknown field with tag 34736 (0x87b0) encountered.
TIFFReadDirectory: Warning, Unknown field with tag 34737 (0x87b1) encountered.
[DALI RAW] Shape: torch.Size([874, 1362]) dtype: torch.uint8 min: 1.0000 max: 2.0000 mean: 1.6657
----------Image saved to pipeline_intermediate/dali_raw/image_dali.tif

Result (white border is a result of writing the image with matplotlib): image_dali.tif

For comparison's sake, here is the same image decoded by my original implementation using nvimgcodec:

decoder = nvimgcodec.Decoder(backends=[
    nvimgcodec.Backend(nvimgcodec.BackendKind.GPU_ONLY, load_hint=1.0)
])
decode_params = nvimgcodec.DecodeParams(color_spec=nvimgcodec.ColorSpec.UNCHANGED)
code_stream = nvimgcodec.CodeStream(f'{self.dir_path}/{tif_file}')
out = decoder.decode(code_stream, params=decode_params)
arr = np.array(out.cpu())
print(f"[STANDARD RAW] Shape: {arr.shape} dtype: {arr.dtype} min: {arr.min():.4f} max: {arr.max():.4f} mean: {arr.mean():.4f}")

[STANDARD RAW] Shape: (874, 1362, 1) dtype: uint8 min: 2.0000 max: 2.0000 mean: 2.0000
----------Image saved to pipeline_intermediate/standard_raw/image_standard.tif

image_standard.tif

As you can notice, statistics don't match (even if the result is the same visually).

Feature Description

I would like better support for GeoTIFF files in DALI. The decoder should not be triggering warnings about unknown fields when decoding such files.

Describe your ideal solution

I would like my existing decoder to decode GeoTIFF files too, without any issue.

files = fn.readers.file(files=self.generated_filepaths, random_shuffle=False)
jpegs = fn.decoders.image(
    files,
    device="mixed",
    output_type=types.ANY_DATA,
    bytes_per_sample_hint=50 * 1024 * 1024,
)

Describe any alternatives you have considered

I could probably write an external source, but I would prefer using the DALI decoder directly.

Additional context

1. Can you please confirm that GeoTIFF files aren't currently supported? original.tif is the file I am trying to decode using DALI.
2. Could the existing decoder fn.decoders.image() support GeoTIFF files too?

Thank you.

Check for duplicates

• I have searched the open bugs/issues and have found no duplicates for this bug report