Tomas Nykodym created SPARK-22730:
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Summary: Add support for non-integer image formats
Key: SPARK-22730
URL: https://issues.apache.org/jira/browse/SPARK-22730
Project: Spark
Issue Type: Improvement
Components: ML
Affects Versions: 2.3.0
Reporter: Tomas Nykodym
The conversion functions toImage and toNDArray provided by ImageSchema
currently do not support non-integer image formats.
Therefore, users who want to work with both integer and floating point formats
have to write their own versions.
Related to this problem is the lack of description of supported openCV modes
(e.g. number of channels, data type).
This tickets is based on our implementation in spark-deep learning and aims to
bring this functionality to the ImageSchema.
To be more specific, we want to
1. update toImage and toNDArray functions to handle float32(64) based
images.
See
https://github.com/tomasatdatabricks/spark-deep-learning/blob/92217afcfdb3f0a42540f396d9018d75ffa6ba7c/python/sparkdl/image/imageIO.py#L61-L87
2. add information about individual OpenCv modes, e.g.
See
https://github.com/tomasatdatabricks/spark-deep-learning/blob/92217afcfdb3f0a42540f396d9018d75ffa6ba7c/python/sparkdl/image/imageIO.py#L31-L46
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