diff --git a/pixi.lock b/pixi.lock
index 908e68f8e6e7a716db918dd3cab83a569b99cad7..0c53663d8b30dc262ddeb3364eed801a2fccf189 100644
--- a/pixi.lock
+++ b/pixi.lock
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- - conda: https://conda.anaconda.org/conda-forge/noarch/httpcore-1.0.5-pyhd8ed1ab_0.conda
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- conda: https://conda.anaconda.org/conda-forge/noarch/hyperlink-21.0.0-pyhd3deb0d_0.tar.bz2
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- - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.12.6-hc5c86c4_1_cpython.conda
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- - conda: https://conda.anaconda.org/conda-forge/noarch/rich-13.8.1-pyhd8ed1ab_0.conda
+ - conda: https://conda.anaconda.org/conda-forge/noarch/rich-13.9.1-pyhd8ed1ab_0.conda
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- - conda: https://conda.anaconda.org/conda-forge/noarch/httpcore-1.0.5-pyhd8ed1ab_0.conda
+ - conda: https://conda.anaconda.org/conda-forge/noarch/httpcore-1.0.6-pyhd8ed1ab_0.conda
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- conda: https://conda.anaconda.org/conda-forge/noarch/hyperlink-21.0.0-pyhd3deb0d_0.tar.bz2
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- - conda: https://conda.anaconda.org/conda-forge/noarch/rich-13.8.1-pyhd8ed1ab_0.conda
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- - conda: https://conda.anaconda.org/conda-forge/noarch/aiohappyeyeballs-2.4.2-pyhd8ed1ab_0.conda
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- - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvtx-12.6.68-h5888daf_0.conda
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- - conda: https://conda.anaconda.org/conda-forge/noarch/httpcore-1.0.5-pyhd8ed1ab_0.conda
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name: aiohappyeyeballs
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license: PSF-2.0
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name: aiohttp
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- xdg
license: BSD-3-Clause
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purls:
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size: 30017
@@ -6813,6 +6818,7 @@ packages:
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- python_abi 3.11.* *_cp311
license: BSD-3-Clause
+ license_family: BSD
purls:
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size: 253595
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- python_abi 3.11.* *_cp311
license: BSD-3-Clause
+ license_family: BSD
purls:
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size: 277946
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- python_abi 3.12.* *_cp312
license: BSD-3-Clause
+ license_family: BSD
purls:
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size: 250774
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- python_abi 3.12.* *_cp312
license: BSD-3-Clause
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purls:
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size: 276004
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timestamp: 1725443252315
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name: cuda-cudart
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license: BSD-3-Clause
license_family: BSD
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+ url: https://conda.anaconda.org/conda-forge/linux-64/libnvjpeg-12.3.3.54-h5888daf_0.conda
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name: libopenblas
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license: BSD-3-Clause
license_family: BSD
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- libuv >=1.48.0,<2.0a0
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license: BSD-3-Clause
license_family: BSD
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license: BSD-3-Clause
license_family: BSD
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license: BSD-3-Clause
license_family: BSD
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license: Apache-2.0 WITH LLVM-exception
license_family: APACHE
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license: Apache-2.0 WITH LLVM-exception
license_family: APACHE
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license: MPL-2.0
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purls:
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name: xorg-libxdmcp
- version: 1.1.3
- build: hd74edd7_2
- build_number: 2
+ version: 1.1.5
+ build: hd74edd7_0
subdir: osx-arm64
- url: https://conda.anaconda.org/conda-forge/osx-arm64/xorg-libxdmcp-1.1.3-hd74edd7_2.conda
- sha256: fe664b9aa7a759132b0deb951c11b6f71e4ebf64d3289be94d6f9e93ba46f65a
- md5: 6aa30139d9b6f59e7c2f336d761df4f3
+ url: https://conda.anaconda.org/conda-forge/osx-arm64/xorg-libxdmcp-1.1.5-hd74edd7_0.conda
+ sha256: 9939a166d780700d81023546759102b33fdc2c5f11ef09f5f66c77210fd334c8
+ md5: 77c447f48cab5d3a15ac224edb86a968
depends:
- __osx >=11.0
license: MIT
license_family: MIT
purls:
- pkg:pypi/xorg-libxdmcp
- size: 18478
- timestamp: 1727619299547
+ size: 18487
+ timestamp: 1727795205022
- kind: conda
name: xorg-libxext
- version: 1.3.4
- build: hb9d3cd8_3
- build_number: 3
+ version: 1.3.6
+ build: hb9d3cd8_0
subdir: linux-64
- url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxext-1.3.4-hb9d3cd8_3.conda
- sha256: 792afe2b1f1f5eb94ad9fb56a2215f432fac41bf132ee1b5060900afe783c561
- md5: 823aa41a70f0c76f28e7d57206db6efa
+ url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxext-1.3.6-hb9d3cd8_0.conda
+ sha256: da5dc921c017c05f38a38bd75245017463104457b63a1ce633ed41f214159c14
+ md5: febbab7d15033c913d53c7a2c102309d
depends:
- __glibc >=2.17,<3.0.a0
- libgcc >=13
@@ -23138,17 +23212,16 @@ packages:
license_family: MIT
purls:
- pkg:pypi/xorg-libxext
- size: 50025
- timestamp: 1727531765423
+ size: 50060
+ timestamp: 1727752228921
- kind: conda
name: xorg-libxext
- version: 1.3.4
- build: hd74edd7_3
- build_number: 3
+ version: 1.3.6
+ build: hd74edd7_0
subdir: osx-arm64
- url: https://conda.anaconda.org/conda-forge/osx-arm64/xorg-libxext-1.3.4-hd74edd7_3.conda
- sha256: df54d659409f22b9ba975e34386f630107ee59063961f682eb5b539f19a3a6bb
- md5: f486059395fa3dc174c7fe258258712b
+ url: https://conda.anaconda.org/conda-forge/osx-arm64/xorg-libxext-1.3.6-hd74edd7_0.conda
+ sha256: 4526fcd879b74400e66cc2a041ca00c0ecd210486459cc65610b135be7c6a2d2
+ md5: acf6c394865f1b7a51c8e57fec6fcde3
depends:
- __osx >=11.0
- xorg-libx11 >=1.8.10,<2.0a0
@@ -23156,17 +23229,16 @@ packages:
license_family: MIT
purls:
- pkg:pypi/xorg-libxext
- size: 41659
- timestamp: 1727531876897
+ size: 41870
+ timestamp: 1727752280756
- kind: conda
name: xorg-libxfixes
- version: 6.0.0
- build: hb9d3cd8_1
- build_number: 1
+ version: 6.0.1
+ build: hb9d3cd8_0
subdir: linux-64
- url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxfixes-6.0.0-hb9d3cd8_1.conda
- sha256: f94cb1198c6a50093db8bfad3b9b0a2c9f46e79e538a5d0ed5d09115fc873c7b
- md5: bf964023af99d6cbbe51c1c00ca6b4c1
+ url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxfixes-6.0.1-hb9d3cd8_0.conda
+ sha256: 2fef37e660985794617716eb915865ce157004a4d567ed35ec16514960ae9271
+ md5: 4bdb303603e9821baf5fe5fdff1dc8f8
depends:
- __glibc >=2.17,<3.0.a0
- libgcc >=13
@@ -23175,71 +23247,67 @@ packages:
license_family: MIT
purls:
- pkg:pypi/xorg-libxfixes
- size: 19705
- timestamp: 1727618702362
+ size: 19575
+ timestamp: 1727794961233
- kind: conda
name: xorg-libxi
- version: 1.7.10
- build: hb9d3cd8_2
- build_number: 2
+ version: 1.8.2
+ build: hb9d3cd8_0
subdir: linux-64
- url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxi-1.7.10-hb9d3cd8_2.conda
- sha256: 8499fc6278b1c0c98e209e3495bfc722bd2bccc55be9acaac581b65bf9e3fb21
- md5: 22589726de8aa48df4543865011dc667
+ url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxi-1.8.2-hb9d3cd8_0.conda
+ sha256: 1a724b47d98d7880f26da40e45f01728e7638e6ec69f35a3e11f92acd05f9e7a
+ md5: 17dcc85db3c7886650b8908b183d6876
depends:
- __glibc >=2.17,<3.0.a0
- libgcc >=13
- xorg-libx11 >=1.8.10,<2.0a0
- - xorg-libxext >=1.3.4,<2.0a0
- - xorg-libxfixes >=6.0.0,<7.0a0
+ - xorg-libxext >=1.3.6,<2.0a0
+ - xorg-libxfixes >=6.0.1,<7.0a0
license: MIT
license_family: MIT
purls:
- pkg:pypi/xorg-libxi
- size: 46832
- timestamp: 1727638107602
+ size: 47179
+ timestamp: 1727799254088
- kind: conda
name: xorg-libxmu
- version: 1.1.3
- build: h4ab18f5_1
- build_number: 1
+ version: 1.2.1
+ build: hb9d3cd8_0
subdir: linux-64
- url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxmu-1.1.3-h4ab18f5_1.conda
- sha256: a34986d71949ba714b27080c8ebb4932857f6e2ebd6383fbb1639415b30f4fd0
- md5: 4d6c9925cdcda27e9d022e40eb3eac05
+ url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxmu-1.2.1-hb9d3cd8_0.conda
+ sha256: d1e91fcb0ed11628abb95940d7f8a59d7cfaf49a03c10d94403faeea4896e17b
+ md5: 7edf3f07320d0416e197940d50e8c890
depends:
- - libgcc-ng >=12
- - xorg-libx11 >=1.8.9,<2.0a0
- - xorg-libxext 1.3.*
- - xorg-libxext >=1.3.4,<2.0a0
+ - __glibc >=2.17,<3.0.a0
+ - libgcc >=13
+ - xorg-libx11 >=1.8.10,<2.0a0
+ - xorg-libxext >=1.3.6,<2.0a0
- xorg-libxt >=1.3.0,<2.0a0
license: MIT
license_family: MIT
purls:
- pkg:pypi/xorg-libxmu
- size: 89113
- timestamp: 1714742286287
+ size: 72619
+ timestamp: 1727801252658
- kind: conda
name: xorg-libxmu
- version: 1.1.3
- build: h99b78c6_1
- build_number: 1
+ version: 1.2.1
+ build: hd74edd7_0
subdir: osx-arm64
- url: https://conda.anaconda.org/conda-forge/osx-arm64/xorg-libxmu-1.1.3-h99b78c6_1.conda
- sha256: 3e8bf9e88e78814b3c5258578ad30e9495fefa0392e00492f5c47aa65729c450
- md5: 5aa16bc32a4b4e3b172ca1134cb5c824
+ url: https://conda.anaconda.org/conda-forge/osx-arm64/xorg-libxmu-1.2.1-hd74edd7_0.conda
+ sha256: 8290144ef3579e08a70428832063285a3c415b1f29e5a38f2365ba8fa75b7807
+ md5: d47d19645a570db0c069c5d883d4a2b7
depends:
- __osx >=11.0
- - xorg-libx11 >=1.8.9,<2.0a0
- - xorg-libxext 1.3.*
- - xorg-libxext >=1.3.4,<2.0a0
+ - xorg-libx11 >=1.8.10,<2.0a0
+ - xorg-libxext >=1.3.6,<2.0a0
- xorg-libxt >=1.3.0,<2.0a0
license: MIT
license_family: MIT
purls:
- pkg:pypi/xorg-libxmu
- size: 63743
- timestamp: 1714742659450
+ size: 63627
+ timestamp: 1727801347298
- kind: conda
name: xorg-libxrender
version: 0.9.11
diff --git a/pyproject.toml b/pyproject.toml
index 6aab5a241086aa1a1ec243e138b740cb73e5fb52..df371fec9dede49dfc4e3588c646c14f442c808e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -96,11 +96,11 @@ lightning = ">=2.2.0"
h5py = "*"
matplotlib-base = "*"
mlflow-skinny = "*"
-numpy = "<2"
+numpy = "*"
pillow = "*"
psutil = "*"
python-gitlab = "*"
-pytorch = "~=2.3.1" # https://github.com/conda-forge/pytorch-cpu-feedstock/issues/254
+pytorch = "*"
scikit-image = "*"
scikit-learn = "*"
scipy = "*"
@@ -508,6 +508,7 @@ select = [
"ISC", # https://docs.astral.sh/ruff/rules/#flake8-implicit-str-concat-isc
"LOG", # https://docs.astral.sh/ruff/rules/#flake8-logging-log
"N", # https://docs.astral.sh/ruff/rules/#pep8-naming-n
+ "NPY", # https://docs.astral.sh/ruff/rules/#numpy-specific-rules-npy
"PTH", # https://docs.astral.sh/ruff/rules/#flake8-use-pathlib-pth
"Q", # https://docs.astral.sh/ruff/rules/#flake8-quotes-q
"RET", # https://docs.astral.sh/ruff/rules/#flake8-return-ret
@@ -518,7 +519,6 @@ select = [
"W", # https://docs.astral.sh/ruff/rules/#warning-w
#"G", # https://docs.astral.sh/ruff/rules/#flake8-logging-format-g
#"ICN", # https://docs.astral.sh/ruff/rules/#flake8-import-conventions-icn
- #"NPY", # https://docs.astral.sh/ruff/rules/#numpy-specific-rules-npy
]
ignore = [
"COM812", # https://docs.astral.sh/ruff/rules/missing-trailing-comma/
diff --git a/src/mednet/data/augmentations.py b/src/mednet/data/augmentations.py
index fcf8887d06b23bdf7f4f187651e9041b43d5b38e..760ea9d98d8ff095439a197e6384ce1ae2f449cb 100644
--- a/src/mednet/data/augmentations.py
+++ b/src/mednet/data/augmentations.py
@@ -14,7 +14,6 @@ input image.
import functools
import logging
-import random
import typing
import numpy.random
@@ -27,6 +26,7 @@ logger = logging.getLogger(__name__)
def _elastic_deformation_on_image(
img: torch.Tensor,
+ rng: numpy.random.Generator,
alpha: float = 1000.0,
sigma: float = 30.0,
spline_order: int = 1,
@@ -46,6 +46,8 @@ def _elastic_deformation_on_image(
The input image to apply elastic deformation to. This image should
always have this shape: ``[C, H, W]``. It should always represent a
tensor on the CPU.
+ rng
+ The numpy random number generator to use.
alpha
A multiplier for the gaussian filter outputs.
sigma
@@ -66,7 +68,7 @@ def _elastic_deformation_on_image(
The image with elastic deformation applied, as a tensor on the CPU.
"""
- if random.random() < p:
+ if rng.random() < p:
assert img.ndim == 3, (
f"This filter accepts only images with 3 dimensions, "
f"however I got an image with {img.ndim} dimensions."
@@ -78,7 +80,7 @@ def _elastic_deformation_on_image(
dx = alpha * typing.cast(
numpy.typing.NDArray[numpy.float64],
gaussian_filter(
- (numpy.random.rand(img_shape[0], img_shape[1]) * 2 - 1),
+ (rng.random(size=(img_shape[0], img_shape[1])) * 2 - 1),
sigma,
mode="constant",
cval=0.0,
@@ -87,7 +89,7 @@ def _elastic_deformation_on_image(
dy = alpha * typing.cast(
numpy.typing.NDArray[numpy.float64],
gaussian_filter(
- (numpy.random.rand(img_shape[0], img_shape[1]) * 2 - 1),
+ (rng.random(size=(img_shape[0], img_shape[1])) * 2 - 1),
sigma,
mode="constant",
cval=0.0,
@@ -125,6 +127,7 @@ def _elastic_deformation_on_image(
def _elastic_deformation_on_batch(
batch: torch.Tensor,
+ rng: numpy.random.Generator,
alpha: float = 1000.0,
sigma: float = 30.0,
spline_order: int = 1,
@@ -142,6 +145,8 @@ def _elastic_deformation_on_batch(
----------
batch
The batch to apply elastic deformation to.
+ rng
+ The numpy random number generator to use.
alpha
A multiplier for the gaussian filter outputs.
sigma
@@ -165,6 +170,7 @@ def _elastic_deformation_on_batch(
# transforms our custom functions into simpler callables
partial = functools.partial(
_elastic_deformation_on_image,
+ rng=rng,
alpha=alpha,
sigma=sigma,
spline_order=spline_order,
@@ -209,6 +215,9 @@ class ElasticDeformation:
p
Probability that this transformation will be applied. Meaningful when
using it as a data augmentation technique.
+ seed
+ Set the random generator seed, if given. Otherwise, initializes the generator
+ with a random seed (c.f. :py:func:`numpy.random.default_rng`).
"""
def __init__(
@@ -218,12 +227,15 @@ class ElasticDeformation:
spline_order: int = 1,
mode: str = "nearest",
p: float = 1.0,
+ seed: int | None = None,
):
self.alpha: float = alpha
self.sigma: float = sigma
self.spline_order: int = spline_order
self.mode: str = mode
self.p: float = p
+ self.seed = seed
+ self.npy_rng = numpy.random.default_rng(seed=seed)
def __str__(self) -> str:
parameters = [
@@ -232,28 +244,31 @@ class ElasticDeformation:
f"spline_order={self.spline_order}",
f"mode={self.mode}",
f"p={self.p}",
+ f"seed={self.seed}",
]
return f"{type(self).__name__}({', '.join(parameters)})"
def __call__(self, img: torch.Tensor) -> torch.Tensor:
if len(img.shape) == 4:
return _elastic_deformation_on_batch(
- img,
- self.alpha,
- self.sigma,
- self.spline_order,
- self.mode,
- self.p,
+ batch=img,
+ rng=self.npy_rng,
+ alpha=self.alpha,
+ sigma=self.sigma,
+ spline_order=self.spline_order,
+ mode=self.mode,
+ p=self.p,
).to(img.device)
if len(img.shape) == 3:
return _elastic_deformation_on_image(
- img.cpu(),
- self.alpha,
- self.sigma,
- self.spline_order,
- self.mode,
- self.p,
+ img=img.cpu(),
+ rng=self.npy_rng,
+ alpha=self.alpha,
+ sigma=self.sigma,
+ spline_order=self.spline_order,
+ mode=self.mode,
+ p=self.p,
).to(img.device)
raise RuntimeError(
diff --git a/tests/data/raw_with_elastic_deformation.png b/tests/data/raw_with_elastic_deformation.png
index 60a71fe65164bbcc20cbc5ce4ff06e17f46057ab..9bed9b39901b85028ba63feb82c2c624420ac5fc 100644
Binary files a/tests/data/raw_with_elastic_deformation.png and b/tests/data/raw_with_elastic_deformation.png differ
diff --git a/tests/test_transforms.py b/tests/test_transforms.py
index f8f54fdbc9cad54f3306b1c3528ddb4b5ad6d88e..f30cea9219c9c3d8982ba13247f0b499ffe03b99 100644
--- a/tests/test_transforms.py
+++ b/tests/test_transforms.py
@@ -38,8 +38,7 @@ def test_elastic_deformation(datadir):
)
# Elastic deforms the raw
- numpy.random.seed(seed=100)
- ed = mednet.data.augmentations.ElasticDeformation()
+ ed = mednet.data.augmentations.ElasticDeformation(seed=100)
raw_deformed = ed(raw_without_deformation)
raw_deformed = F.to_pil_image(raw_deformed)
# uncomment to save a new reference if required