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Merged
RomaneCar1 merged 1 commit into from
Aug 26, 2025
Merged

Update Example, dossier auto_example #2

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158 changes: 158 additions & 0 deletions auto_examples/DICOMExample/create3DSeqFromDicom.ipynb
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Original file line number Diff line number Diff line change
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n# Create 3D Sequence from DICOM\nauthor: OpenTPS team\n\nThis example shows how to read data from a 4DCT folder, create a dynamic 3D sequence with the 4DCT data, and save this sequence in serialized format on the drive.\n\nrunning time: ~ 10 minutes\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Setting up the environment in google collab\n First you need to change the type of execution in the bottom left from processor to GPU. Then you can run the example.\n\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import sys\nif \"google.colab\" in sys.modules:\n from IPython import get_ipython\n get_ipython().system('git clone https://gitlab.com/openmcsquare/opentps.git')\n get_ipython().system('pip install ./opentps')\n get_ipython().system('pip install scipy==1.10.1')\n get_ipython().system('pip install cupy-cuda12x')\n import opentps"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"imports\n\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import os\nfrom pathlib import Path\nimport sys"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"import the needed opentps.core packages\n\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from opentps.core.io.dataLoader import readData\nfrom opentps.core.data.dynamicData._dynamic3DSequence import Dynamic3DSequence\nfrom opentps.core.io.serializedObjectIO import saveSerializedObjects"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Get the current working directory, its parent, then add the testData folder at the end of it\n\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"testDataPath = os.path.join(Path(os.getcwd()).parent.absolute(), 'testData/')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# read a serialized dynamic sequence\n\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"dataPath = 'Path_to_your_4DCT_data/' # replace with the path to your 4DCT data folder\n\nprint('Datas present in ' + dataPath + 'are loaded.')\ndataList = readData(dataPath)\nprint(len(dataList), 'images found in the folder')\nprint('Image type =', type(dataList[0]))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"create a Dynamic3DSequence and change its name\n\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"dynseq = Dynamic3DSequence(dyn3DImageList=dataList)\nprint('Type of the created object =', type(dynseq))\nprint('Sequence name =', dynseq.name)\ndynseq.name = 'Light4DCT'\nprint('Sequence name = ', dynseq.name)\nprint('Sequence lenght =', len(dynseq.dyn3DImageList))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"save it as a serialized object\n\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"savingPath = testDataPath + 'lightDynSeq'\nsaveSerializedObjects(dynseq, savingPath)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.11.13"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
158 changes: 158 additions & 0 deletions auto_examples/DICOMExample/create3DSeqFromImages.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,158 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n# Create 3D Sequence from Images\nauthor: OpenTPS team\n\nThis example shows how to read data from a 4DCT folder, create a dynamic 3D sequence with the 4DCT data, and save this sequence in serialized format on the drive.\n\nrunning time: ~ 10 minutes\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Setting up the environment in google collab\n First you need to change the type of execution in the bottom left from processor to GPU. Then you can run the example.\n\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import sys\nif \"google.colab\" in sys.modules:\n from IPython import get_ipython\n get_ipython().system('git clone https://gitlab.com/openmcsquare/opentps.git')\n get_ipython().system('pip install ./opentps')\n get_ipython().system('pip install scipy==1.10.1')\n get_ipython().system('pip install cupy-cuda12x')\n import opentps"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"imports\n\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import os\nfrom pathlib import Path\nimport sys"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"import the needed opentps.core packages\n\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from opentps.core.io.dataLoader import readData\nfrom opentps.core.data.dynamicData._dynamic3DSequence import Dynamic3DSequence\nfrom opentps.core.io.serializedObjectIO import saveSerializedObjects"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Get the current working directory, its parent, then add the testData folder at the end of it\n\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"testDataPath = os.path.join(Path(os.getcwd()).parent.absolute(), 'testData/')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"read a serialized dynamic sequence\n\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"dataPath = 'Path_to_your_4DCT_data/' # replace with the path to your 4DCT data folder\n\nprint('Datas present in ' + dataPath + 'are loaded.')\ndataList = readData(dataPath)\nprint(len(dataList), 'images found in the folder')\nprint('Image type =', type(dataList[0]))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"create a Dynamic3DSequence and change its name\n\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"dynseq = Dynamic3DSequence(dyn3DImageList=dataList)\nprint('Type of the created object =', type(dynseq))\nprint('Sequence name =', dynseq.name)\ndynseq.name = 'Light4DCT'\nprint('Sequence name = ', dynseq.name)\nprint('Sequence lenght =', len(dynseq.dyn3DImageList))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"save it as a serialized object\n\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"savingPath = testDataPath + 'lightDynSeq'\nsaveSerializedObjects(dynseq, savingPath)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.11.13"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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