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1090-enhance-tutorials (#1100)
Signed-off-by: binliu <binliu@nvidia.com> Fixes #1090 . ### Description Fix some basic problems occured during test. ### Checks - [x] Reconstruction tutorial: - [x] some typo and grammar problems in the readme file. - [x] `fastmri_ssim.py` absents in `varnet_demo` folder. - [x] the checkpoint device directly map to 'cpu' in [unet_demo/inference.ipynb](https://github.com/binliunls/tutorials/blob/1014-mlflow-handler-tutorial/reconstruction/MRI_reconstruction/unet_demo/inference.ipynb). - [x] Detection tutorial: - [x] some typo, link and grammar problems in the readme file. - [x] CAI tutorial: - [x] add explanation for opencv codec error in the `video_seg` tutorial. - [x] use `EnsureChannelFirst` instead of `AsChannelFirst` in `endoscopic inbody classification tutorial`. - [x] accuracy in endoscopic inbody classfication tutorial should be a number instead of tensor. - [x] Pathology tutorial: - [x] some useless cell output in nuclick tutorial. - [x] Add license to above tutorials - [x] Check license in other tutorials Signed-off-by: binliu <binliu@nvidia.com> Signed-off-by: Bin Liu (SW-GPU) <binliu@nvidia.com> Signed-off-by: Mingxin Zheng <18563433+mingxin-zheng@users.noreply.github.com> Signed-off-by: mingxin-zheng <18563433+mingxin-zheng@users.noreply.github.com> Signed-off-by: Mingxin Zheng <mingxinz@nvidia.com> Co-authored-by: mingxin-zheng <mingxin-zheng@users.noreply.github.com> Co-authored-by: Mingxin Zheng <18563433+mingxin-zheng@users.noreply.github.com> Co-authored-by: Mingxin Zheng <mingxinz@nvidia.com>
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‎2d_classification/mednist_tutorial.ipynb‎

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‎2d_registration/registration_mednist.ipynb‎

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‎3d_registration/paired_lung_ct.ipynb‎

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‎3d_segmentation/brats_segmentation_3d.ipynb‎

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"cell_type": "markdown",
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"Copyright (c) MONAI Consortium \n",
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"Licensed under the Apache License, Version 2.0 (the \"License\"); \n",
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"you may not use this file except in compliance with the License. \n",
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"You may obtain a copy of the License at \n",
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"&nbsp;&nbsp;&nbsp;&nbsp;http://www.apache.org/licenses/LICENSE-2.0 \n",
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"Unless required by applicable law or agreed to in writing, software \n",
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"distributed under the License is distributed on an \"AS IS\" BASIS, \n",
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"WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \n",
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"See the License for the specific language governing permissions and \n",
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"limitations under the License.\n",
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"\n",
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"# Brain tumor 3D segmentation with MONAI\n",
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"\n",
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"This tutorial shows how to construct a training workflow of multi-labels segmentation task.\n",
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}
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"source": [
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"# Copyright 2020 MONAI Consortium\n",
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"# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
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"# you may not use this file except in compliance with the License.\n",
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"# You may obtain a copy of the License at\n",
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"# http://www.apache.org/licenses/LICENSE-2.0\n",
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"# Unless required by applicable law or agreed to in writing, software\n",
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"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
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"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
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"# See the License for the specific language governing permissions and\n",
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"# limitations under the License.\n",
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"\n",
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"import os\n",
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‎3d_segmentation/challenge_baseline/run_net.py‎

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# Copyright 2020 MONAI Consortium
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# Copyright (c) MONAI Consortium
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at

‎3d_segmentation/ignite/unet_evaluation_array.py‎

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# Copyright 2020 MONAI Consortium
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# Copyright (c) MONAI Consortium
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at

‎3d_segmentation/ignite/unet_evaluation_dict.py‎

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# Copyright 2020 MONAI Consortium
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# Copyright (c) MONAI Consortium
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at

‎3d_segmentation/ignite/unet_training_array.py‎

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# Copyright 2020 MONAI Consortium
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# Copyright (c) MONAI Consortium
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at

‎3d_segmentation/ignite/unet_training_dict.py‎

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# Copyright 2020 MONAI Consortium
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# Copyright (c) MONAI Consortium
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at

‎3d_segmentation/spleen_segmentation_3d.ipynb‎

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Copyright (c) MONAI Consortium \n",
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"Licensed under the Apache License, Version 2.0 (the \"License\"); \n",
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"you may not use this file except in compliance with the License. \n",
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"You may obtain a copy of the License at \n",
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"&nbsp;&nbsp;&nbsp;&nbsp;http://www.apache.org/licenses/LICENSE-2.0 \n",
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"Unless required by applicable law or agreed to in writing, software \n",
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"distributed under the License is distributed on an \"AS IS\" BASIS, \n",
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"WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \n",
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"See the License for the specific language governing permissions and \n",
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"limitations under the License.\n",
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"\n",
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"# Spleen 3D segmentation with MONAI\n",
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"\n",
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"This tutorial shows how to integrate MONAI into an existing PyTorch medical DL program.\n",
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"The Spleen dataset can be downloaded from http://medicaldecathlon.com/.\n",
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"![spleen](http://medicaldecathlon.com/img/spleen0.png)\n",
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"![spleen](../figures/spleen0.png)\n",
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Setup imports"
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]
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},
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"name": "stderr",
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"output_type": "stream",
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"/opt/conda/lib/python3.8/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
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" from .autonotebook import tqdm as notebook_tqdm\n"
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]
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},
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"name": "stdout",
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"text": [
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"MONAI version: 1.1.0+2.g97918e46\n",
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"Numpy version: 1.22.2\n",
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"Pytorch version: 1.13.0a0+d0d6b1f\n",
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"MONAI flags: HAS_EXT = True, USE_COMPILED = False, USE_META_DICT = False\n",
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"MONAI rev id: 97918e46e0d2700c050e678d72e3edb35afbd737\n",
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"MONAI __file__: /opt/monai/monai/__init__.py\n",
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"\n",
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"Optional dependencies:\n",
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"Pytorch Ignite version: 0.4.10\n",
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"Nibabel version: 4.0.2\n",
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"scikit-image version: 0.19.3\n",
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"Pillow version: 9.0.1\n",
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"Tensorboard version: 2.10.1\n",
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"gdown version: 4.6.0\n",
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"TorchVision version: 0.14.0a0\n",
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"tqdm version: 4.64.1\n",
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"lmdb version: 1.3.0\n",
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"psutil version: 5.9.2\n",
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"pandas version: 1.4.4\n",
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"einops version: 0.6.0\n",
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"transformers version: 4.21.3\n",
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"mlflow version: 2.0.1\n",
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"\n",
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"For details about installing the optional dependencies, please visit:\n",
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" https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies\n",
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"\n"
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"MONAI version: 0.9.1\n",
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"Numpy version: 1.22.4\n",
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"Pytorch version: 1.13.0a0+340c412\n",
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"MONAI flags: HAS_EXT = True, USE_COMPILED = False, USE_META_DICT = False\n",
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"MONAI rev id: 356d2d2f41b473f588899d705bbc682308cee52c\n",
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"MONAI __file__: /opt/monai/monai/__init__.py\n",
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"Pytorch Ignite version: 0.4.9\n",
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"Tensorboard version: 2.9.1\n",
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"psutil version: 5.9.1\n",
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"pandas version: 1.3.5\n",
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"For details about installing the optional dependencies, please visit:\n",
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"source": [
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"# Copyright 2020 MONAI Consortium\n",
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"# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
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"# you may not use this file except in compliance with the License.\n",
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"# You may obtain a copy of the License at\n",
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"# http://www.apache.org/licenses/LICENSE-2.0\n",
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"# Unless required by applicable law or agreed to in writing, software\n",
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"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
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"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
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"# See the License for the specific language governing permissions and\n",
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