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ITK + Dask notebooks (August 2022)
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{
"cells": [
{
"cell_type": "code",
"execution_count": 29,
"id": "2876057e",
"metadata": {},
"outputs": [],
"source": [
"import itk\n",
"import numpy as np\n",
"import skimage.restoration"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "89e50023",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(200, 200, 200)\n",
"(101, 64, 64)\n"
]
}
],
"source": [
"img_size = (200, 200, 200)\n",
"psf_size = (101, 64, 64) #(12, 100, 100)\n",
"\n",
"img = np.random.random(img_size)\n",
"psf = np.ones(psf_size) / np.prod(psf_size).astype('uint16')\n",
"\n",
"print(img.shape)\n",
"print(psf.shape)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "383fd3f4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"float64\n",
"float64\n"
]
}
],
"source": [
"print(psf.dtype)\n",
"print(img.dtype)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "90733602",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"done\n"
]
}
],
"source": [
"# itk richardson-lucy deconvolution\n",
"\n",
"image = itk.image_view_from_array(img) # Convert to ITK object\n",
"kernel = itk.image_view_from_array(psf) # Convert to ITK object\n",
"iterations = 1\n",
"\n",
"deconvolved = itk.richardson_lucy_deconvolution_image_filter(\n",
" image,\n",
" kernel_image=kernel,\n",
" number_of_iterations=iterations\n",
")\n",
"\n",
"result = itk.array_from_image(deconvolved) # Convert back to Numpy array\n",
"print('done')"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "c5f601d6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(200, 200, 200)\n"
]
}
],
"source": [
"print(result.shape)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "0bdcd30a",
"metadata": {},
"outputs": [
{
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"text/plain": [
"dask.array<array, shape=(200, 200, 200), dtype=float64, chunksize=(50, 100, 100), chunktype=numpy.ndarray>"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import dask.array as da\n",
"\n",
"imgs = da.from_array(img, chunks=(50,100,100))\n",
"imgs"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "1836c22a",
"metadata": {},
"outputs": [
{
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"text/plain": [
"dask.array<richardson_lucy_deconvolution_image_filter, shape=(200, 200, 200), dtype=float32, chunksize=(50, 100, 100), chunktype=numpy.ndarray>"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"deconvolved = da.map_blocks(\n",
" itk.richardson_lucy_deconvolution_image_filter,\n",
" imgs, \n",
" kernel_image=kernel,\n",
" number_of_iterations=1,\n",
" dtype=np.float32\n",
")\n",
"deconvolved"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "5a46cdfb",
"metadata": {},
"outputs": [],
"source": [
"deonvolved_result = deconvolved.compute()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "5bbae81c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(200, 200, 200)\n"
]
}
],
"source": [
"print(deonvolved_result.shape)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "d500e9ad",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Validation errors in config file(s).\n",
"The following fields have been reset to the default value:\n",
"\n",
"schema_version\n",
" value is not a valid tuple (type=type_error.tuple)\n",
"\n",
"\n",
"\n",
"napari was tested with QT library `>=5.12.3`.\n",
"The version installed is 5.9.7. Please report any issues with\n",
"this specific QT version at https://github.com/Napari/napari/issues.\n"
]
},
{
"data": {
"text/plain": [
"<Image layer 'result' at 0x7f1a4fb0cbb0>"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Traceback (most recent call last):\n",
" File \"/home/genevieb/em95/miniconda/conda/envs/itk-dask/lib/python3.10/site-packages/vispy/app/backends/_qt.py\", line 489, in mouseMoveEvent\n",
" modifiers=self._modifiers(ev),\n",
" File \"/home/genevieb/em95/miniconda/conda/envs/itk-dask/lib/python3.10/site-packages/vispy/app/backends/_qt.py\", line 582, in _modifiers\n",
" if q & qtmod:\n",
"TypeError: unsupported operand type(s) for &: 'KeyboardModifier' and 'KeyboardModifiers'\n",
"Traceback (most recent call last):\n",
" File \"/home/genevieb/em95/miniconda/conda/envs/itk-dask/lib/python3.10/site-packages/vispy/app/backends/_qt.py\", line 489, in mouseMoveEvent\n",
" modifiers=self._modifiers(ev),\n",
" File \"/home/genevieb/em95/miniconda/conda/envs/itk-dask/lib/python3.10/site-packages/vispy/app/backends/_qt.py\", line 582, in _modifiers\n",
" if q & qtmod:\n",
"TypeError: unsupported operand type(s) for &: 'KeyboardModifier' and 'KeyboardModifiers'\n",
"Traceback (most recent call last):\n",
" File \"/home/genevieb/em95/miniconda/conda/envs/itk-dask/lib/python3.10/site-packages/vispy/app/backends/_qt.py\", line 489, in mouseMoveEvent\n",
" modifiers=self._modifiers(ev),\n",
" File \"/home/genevieb/em95/miniconda/conda/envs/itk-dask/lib/python3.10/site-packages/vispy/app/backends/_qt.py\", line 582, in _modifiers\n",
" if q & qtmod:\n",
"TypeError: unsupported operand type(s) for &: 'KeyboardModifier' and 'KeyboardModifiers'\n",
"Traceback (most recent call last):\n",
" File \"/home/genevieb/em95/miniconda/conda/envs/itk-dask/lib/python3.10/site-packages/vispy/app/backends/_qt.py\", line 489, in mouseMoveEvent\n",
" modifiers=self._modifiers(ev),\n",
" File \"/home/genevieb/em95/miniconda/conda/envs/itk-dask/lib/python3.10/site-packages/vispy/app/backends/_qt.py\", line 582, in _modifiers\n",
" if q & qtmod:\n",
"TypeError: unsupported operand type(s) for &: 'KeyboardModifier' and 'KeyboardModifiers'\n",
"Traceback (most recent call last):\n",
" File \"/home/genevieb/em95/miniconda/conda/envs/itk-dask/lib/python3.10/site-packages/vispy/app/backends/_qt.py\", line 489, in mouseMoveEvent\n",
" modifiers=self._modifiers(ev),\n",
" File \"/home/genevieb/em95/miniconda/conda/envs/itk-dask/lib/python3.10/site-packages/vispy/app/backends/_qt.py\", line 582, in _modifiers\n",
" if q & qtmod:\n",
"TypeError: unsupported operand type(s) for &: 'KeyboardModifier' and 'KeyboardModifiers'\n",
"Traceback (most recent call last):\n",
" File \"/home/genevieb/em95/miniconda/conda/envs/itk-dask/lib/python3.10/site-packages/vispy/app/backends/_qt.py\", line 489, in mouseMoveEvent\n",
" modifiers=self._modifiers(ev),\n",
" File \"/home/genevieb/em95/miniconda/conda/envs/itk-dask/lib/python3.10/site-packages/vispy/app/backends/_qt.py\", line 582, in _modifiers\n",
" if q & qtmod:\n",
"TypeError: unsupported operand type(s) for &: 'KeyboardModifier' and 'KeyboardModifiers'\n"
]
}
],
"source": [
"import napari\n",
"\n",
"viewer = napari.Viewer()\n",
"viewer.add_image(result)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7320ab30",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "be4e635f",
"metadata": {},
"outputs": [],
"source": [
"# itk richardson-lucy deconvolution\n",
"deconvolved = itk.RichardsonLucyDeconvolutionImageFilter(img, kernel_image=psf, number_of_iterations=1)\n",
"print(deconvolved.shape)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "367b6db1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(200, 200, 200)\n"
]
}
],
"source": [
"# scikit-image richardson-lucy deconvolution\n",
"deconvolved_RL = skimage.restoration.richardson_lucy(img, psf, num_iter=30)\n",
"print(deconvolved_RL.shape)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "6f00a0ce",
"metadata": {},
"outputs": [],
"source": [
"del deconvolved_RL"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "621c6f24",
"metadata": {},
"outputs": [],
"source": []
}
],
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"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.4"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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