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release_notes_v22.02.01
This version would be only available through the PyPI package (https://pypi.org/project/cucim/22.2.1/).
cuCIM's GPUDirectStorage (GDS) API was introduced at GTC 2022 Spring "Accelerating Storage IO to GPUs with Magnum IO [S41347]" session on March 24.
cuCIM's GDS API examples are available at https://github.com/NVIDIA/MagnumIO/tree/main/gds/readers/cucim-gds.
- Check nullptr of handler in CuFileDriver::close() (#229) @gigony
- Handle file descriptor ownership and update documents for GDS (#234) @gigony
- Apply fixes to skimage.transform scheduled for scikit-image 0.19.2 (#208) @grlee7
-
Randomization of transforms per image per batch (#231) @shekhardw
-
Expose data type of CuImage object for interoperability with NumPy (#246) @gigony
Random Color Jitter transform implemented. Random Image Flip, Random Image Rotate90 and Random Zoom transforms are updated to apply transforms per image per batch. Execution of these transforms on per image per batch basis may result in increase in runtime.
-
CuImage
object exposestypestr
property. -
DLDataType
andDLDataTypeCode
type is available undercucim.clara
.
Prior to this change, it was not easy to convert CuImage's dtype
(DLDataType) to NumPy's dtype
and had to use the below workaround.
>>> from cucim import CuImage
>>> a = CuImage("notebooks/input/image.tif")
>>> b = a.read_region((0,0), (10,10))
>>> import numpy as np
>>> np.dtype(b.__array_interface__["typestr"]) # b would expose `__cuda_array_interface__` if memory is in GPU.
dtype('uint8')
With this change, we can convert the data type of CuImage to NumPy's dtype
easily, and also can access cuCIM's DLDataType.
>>> from cucim import CuImage
>>> a = CuImage("notebooks/input/image.tif")
>>> b = a.read_region((0,0), (10,10))
>>> import numpy as np
>>> b.typestr
'|u1'
>>> np.dtype(b.typestr) == np.uint8
True
>>> from cucim.clara import DLDataType, DLDataTypeCode
>>> b.dtype == DLDataType(DLDataTypeCode.DLUInt, 8, 1)
True
- Remove verbose plugin messages temporarily
- Address #109 ([BUG] - Info messages appearing as warnings in Jupyter notebooks)
- Will support log level configuration later
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