Merge pull request #4 from juglab/dev

Dev
juglab · Jan 11, 2021 · 0b89fb2 · 0b89fb2
2 parents dd80473 + ce3d5d0
commit 0b89fb2
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Showing 7 changed files with 187 additions and 22 deletions.
diff --git a/README.md b/README.md
@@ -6,7 +6,7 @@ Build Python package:
 `python setup.py bdist_wheel`
 
 Build singularity recipe:
-`neurodocker generate singularity -b nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04 -p apt --copy /home/tibuch/Gitrepos/FourierImageTransformer/dist/fourier_image_transformers-0.1.2-py3-none-any.whl /fourier_image_transformers-0.1.2-py3-none-any.whl --miniconda create_env=fit conda_install='python=3.7 astra-toolbox pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch -c astra-toolbox/label/dev' pip_install='/fourier_image_transformers-0.1.2-py3-none-any.whl' activate=true --entrypoint "/neurodocker/startup.sh python" > v0.1.2.Singularity`
+`neurodocker generate singularity -b nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04 -p apt --copy /home/tibuch/Gitrepos/FourierImageTransformer/dist/fourier_image_transformers-0.1.3-py3-none-any.whl /fourier_image_transformers-0.1.3-py3-none-any.whl --miniconda create_env=fit conda_install='python=3.7 astra-toolbox pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch -c astra-toolbox/label/dev' pip_install='/fourier_image_transformers-0.1.3-py3-none-any.whl' activate=true --entrypoint "/neurodocker/startup.sh python" > v0.1.3.Singularity`
 
 Build singularity container:
-`sudo singularity build fit_v0.1.2.simg v0.1.2.Singularity`
+`sudo singularity build fit_v0.1.3.simg v0.1.3.Singularity`
diff --git a/examples/DataModule - MNIST Tomo .ipynb b/examples/DataModule - MNIST Tomo .ipynb
diff --git a/fit/datamodules/tomo_rec/FCDataset.py b/fit/datamodules/tomo_rec/FCDataset.py
@@ -18,8 +18,21 @@ def __len__(self):
 
 
 class FourierCoefficientDataset(FCDataset):
-    def __init__(self, ds, part='train', img_shape=42):
+    def __init__(self, ds, mag_min, mag_max, part='train', img_shape=42):
         super().__init__(ds, part=part, img_shape=img_shape)
+        if mag_min == None and mag_max == None:
+            tmp_sinos = []
+            for i in np.random.permutation(len(self.ds))[:200]:
+                sino, _ = self.ds[i]
+                tmp_sinos.append(sino)
+
+            tmp_sinos = torch.stack(tmp_sinos)
+            tmp_sinos = torch.fft.rfftn(tmp_sinos, dim=[1,2]).abs()
+            self.mag_min = tmp_sinos.min()
+            self.mag_max = tmp_sinos.max()
+        else:
+            self.mag_min = mag_min
+            self.mag_max = mag_max
 
     def __getitem__(self, item):
         sino, img = self.ds[item]
@@ -36,14 +49,12 @@ def __getitem__(self, item):
         img_mag = torch.log(img_mag)
         img_phi = img_fft.angle()
 
-        mag_min, mag_max = sino_mag.min(), sino_mag.max()
-
-        sino_mag = 2 * (sino_mag - mag_min) / (mag_max - mag_min) - 1
-        img_mag = 2 * (img_mag - mag_min) / (mag_max - mag_min) - 1
+        sino_mag = 2 * (sino_mag - self.mag_min) / (self.mag_max - self.mag_min) - 1
+        img_mag = 2 * (img_mag - self.mag_min) / (self.mag_max - self.mag_min) - 1
 
         sino_phi = 2 * sino_phi / (2 * np.pi) - 1
         img_phi = 2 * img_phi / (2 * np.pi) - 1
 
         sino_fft = torch.stack([sino_mag.flatten(), sino_phi.flatten()], dim=-1)
         img_fft = torch.stack([img_mag.flatten(), img_phi.flatten()], dim=-1)
-        return sino_fft, img_fft, img, (mag_min.unsqueeze(-1), mag_max.unsqueeze(-1))
+        return sino_fft, img_fft, img, (self.mag_min.unsqueeze(-1), self.mag_max.unsqueeze(-1))
diff --git a/fit/datamodules/tomo_rec/TRecDataModule.py b/fit/datamodules/tomo_rec/TRecDataModule.py
@@ -86,6 +86,8 @@ def __init__(self, root_dir, batch_size, num_angles=15, inner_circle=True):
         self.gt_ds = None
         self.mean = None
         self.std = None
+        self.mag_min = None
+        self.mag_max = None
 
     def setup(self, stage: Optional[str] = None):
         mnist_test = MNIST(self.root_dir, train=False, download=True).data.type(torch.float32)
@@ -117,20 +119,27 @@ def setup(self, stage: Optional[str] = None):
             GroundTruthDataset(mnist_train, mnist_val, mnist_test),
             num_angles=self.num_angles, im_shape=70, impl='astra_cpu', inner_circle=self.inner_circle)
 
+        tmp_fcds = FourierCoefficientDataset(self.gt_ds, mag_min=None, mag_max=None, part='train',
+                                             img_shape=MNISTTomoFourierTargetDataModule.IMG_SHAPE)
+        self.mag_min = tmp_fcds.mag_min
+        self.mag_max = tmp_fcds.mag_max
+
     def train_dataloader(self, *args, **kwargs) -> DataLoader:
         return DataLoader(
-            FourierCoefficientDataset(self.gt_ds, part='train', img_shape=MNISTTomoFourierTargetDataModule.IMG_SHAPE),
+            FourierCoefficientDataset(self.gt_ds, mag_min=self.mag_min, mag_max=self.mag_max, part='train',
+                                      img_shape=MNISTTomoFourierTargetDataModule.IMG_SHAPE),
             batch_size=self.batch_size, num_workers=2)
 
     def val_dataloader(self, *args, **kwargs) -> Union[DataLoader, List[DataLoader]]:
         return DataLoader(
-            FourierCoefficientDataset(self.gt_ds, part='validation',
+            FourierCoefficientDataset(self.gt_ds, mag_min=self.mag_min, mag_max=self.mag_max, part='validation',
                                       img_shape=MNISTTomoFourierTargetDataModule.IMG_SHAPE),
             batch_size=self.batch_size, num_workers=2)
 
     def test_dataloader(self, *args, **kwargs) -> Union[DataLoader, List[DataLoader]]:
         return DataLoader(
-            FourierCoefficientDataset(self.gt_ds, part='test', img_shape=MNISTTomoFourierTargetDataModule.IMG_SHAPE),
+            FourierCoefficientDataset(self.gt_ds, mag_min=self.mag_min, mag_max=self.mag_max, part='test',
+                                      img_shape=MNISTTomoFourierTargetDataModule.IMG_SHAPE),
             batch_size=1)
 
 
@@ -173,18 +182,25 @@ def setup(self, stage: Optional[str] = None):
             GroundTruthDataset(gt_train, gt_val, gt_test),
             num_angles=self.num_angles, im_shape=450, impl='astra_cpu', inner_circle=self.inner_circle)
 
+        tmp_fcds = FourierCoefficientDataset(self.gt_ds, mag_min=None, mag_max=None, part='train',
+                                             img_shape=MNISTTomoFourierTargetDataModule.IMG_SHAPE)
+        self.mag_min = tmp_fcds.mag_min
+        self.mag_max = tmp_fcds.mag_max
+
     def train_dataloader(self, *args, **kwargs) -> DataLoader:
         return DataLoader(
-            FourierCoefficientDataset(self.gt_ds, part='train', img_shape=LoDoPaBFourierTargetDataModule.IMG_SHAPE),
+            FourierCoefficientDataset(self.gt_ds, mag_min=self.mag_min, mag_max=self.mag_max, part='train',
+                                      img_shape=LoDoPaBFourierTargetDataModule.IMG_SHAPE),
             batch_size=self.batch_size, num_workers=2)
 
     def val_dataloader(self, *args, **kwargs) -> Union[DataLoader, List[DataLoader]]:
         return DataLoader(
-            FourierCoefficientDataset(self.gt_ds, part='validation',
+            FourierCoefficientDataset(self.gt_ds, mag_min=self.mag_min, mag_max=self.mag_max, part='validation',
                                       img_shape=LoDoPaBFourierTargetDataModule.IMG_SHAPE),
             batch_size=self.batch_size, num_workers=2)
 
     def test_dataloader(self, *args, **kwargs) -> Union[DataLoader, List[DataLoader]]:
         return DataLoader(
-            FourierCoefficientDataset(self.gt_ds, part='test', img_shape=LoDoPaBFourierTargetDataModule.IMG_SHAPE),
+            FourierCoefficientDataset(self.gt_ds, mag_min=self.mag_min, mag_max=self.mag_max, part='test',
+                                      img_shape=LoDoPaBFourierTargetDataModule.IMG_SHAPE),
             batch_size=1)
diff --git a/fit/version.py b/fit/version.py
@@ -1 +1 @@
-__version__ = '0.1.2'
+__version__ = '0.1.3'
diff --git a/scripts/TRec_MNIST.py b/scripts/TRec_MNIST.py
@@ -76,7 +76,7 @@ def main():
                                                        dst_flatten_coords=model.dst_flatten_coords,
                                                        dst_order=model.dst_order)
 
-    test_res = trainer.test(model, test_dl)[0]
+    test_res = trainer.test(model, datamodule=dm)[0]
     out_res = {
         "Mean PSNR": test_res["Mean PSNR"].item(),
         "SEM PSNR": test_res["SEM PSNR"].item()
@@ -95,7 +95,7 @@ def main():
                                                        dst_flatten_coords=model.dst_flatten_coords,
                                                        dst_order=model.dst_order)
 
-    test_res = trainer.test(model, test_dl)[0]
+    test_res = trainer.test(model, datamodule=dm)[0]
     out_res = {
         "Mean PSNR": test_res["Mean PSNR"].item(),
         "SEM PSNR": test_res["SEM PSNR"].item()

diff --git a/singularity/v0.1.3.Singularity b/singularity/v0.1.3.Singularity
@@ -0,0 +1,138 @@
+# Generated by: Neurodocker version 0.7.0
+# Latest release: Neurodocker version 0.7.0
+# Timestamp: 2021/01/11 14:22:17 UTC
+# 
+# Thank you for using Neurodocker. If you discover any issues
+# or ways to improve this software, please submit an issue or
+# pull request on our GitHub repository:
+# 
+#     https://github.com/ReproNim/neurodocker
+
+Bootstrap: docker
+From: nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04
+
+%post
+su - root
+
+export ND_ENTRYPOINT="/neurodocker/startup.sh"
+apt-get update -qq
+apt-get install -y -q --no-install-recommends \
+    apt-utils \
+    bzip2 \
+    ca-certificates \
+    curl \
+    locales \
+    unzip
+apt-get clean
+rm -rf /var/lib/apt/lists/*
+sed -i -e 's/# en_US.UTF-8 UTF-8/en_US.UTF-8 UTF-8/' /etc/locale.gen
+dpkg-reconfigure --frontend=noninteractive locales
+update-locale LANG="en_US.UTF-8"
+chmod 777 /opt && chmod a+s /opt
+mkdir -p /neurodocker
+if [ ! -f "$ND_ENTRYPOINT" ]; then
+  echo '#!/usr/bin/env bash' >> "$ND_ENTRYPOINT"
+  echo 'set -e' >> "$ND_ENTRYPOINT"
+  echo 'export USER="${USER:=`whoami`}"' >> "$ND_ENTRYPOINT"
+  echo 'if [ -n "$1" ]; then "$@"; else /usr/bin/env bash; fi' >> "$ND_ENTRYPOINT";
+fi
+chmod -R 777 /neurodocker && chmod a+s /neurodocker
+
+export PATH="/opt/miniconda-latest/bin:$PATH"
+echo "Downloading Miniconda installer ..."
+conda_installer="/tmp/miniconda.sh"
+curl -fsSL --retry 5 -o "$conda_installer" https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
+bash "$conda_installer" -b -p /opt/miniconda-latest
+rm -f "$conda_installer"
+conda update -yq -nbase conda
+conda config --system --prepend channels conda-forge
+conda config --system --set auto_update_conda false
+conda config --system --set show_channel_urls true
+sync && conda clean -y --all && sync
+conda create -y -q --name fit
+conda install -y -q --name fit \
+    "python=3.7" \
+    "astra-toolbox" \
+    "pytorch" \
+    "torchvision" \
+    "torchaudio" \
+    "cudatoolkit=10.2" \
+    "-c" \
+    "pytorch" \
+    "-c" \
+    "astra-toolbox/label/dev"
+sync && conda clean -y --all && sync
+bash -c "source activate fit
+  pip install --no-cache-dir  \
+      "/fourier_image_transformers-0.1.3-py3-none-any.whl""
+rm -rf ~/.cache/pip/*
+sync
+sed -i '$isource activate fit' $ND_ENTRYPOINT
+
+
+echo '{
+\n  "pkg_manager": "apt",
+\n  "instructions": [
+\n    [
+\n      "base",
+\n      "nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04"
+\n    ],
+\n    [
+\n      "user",
+\n      "root"
+\n    ],
+\n    [
+\n      "_header",
+\n      {
+\n        "version": "generic",
+\n        "method": "custom"
+\n      }
+\n    ],
+\n    [
+\n      "copy",
+\n      [
+\n        "/home/tibuch/Gitrepos/FourierImageTransformer/dist/fourier_image_transformers-0.1.3-py3-none-any.whl",
+\n        "/fourier_image_transformers-0.1.3-py3-none-any.whl"
+\n      ]
+\n    ],
+\n    [
+\n      "miniconda",
+\n      {
+\n        "create_env": "fit",
+\n        "conda_install": [
+\n          "python=3.7",
+\n          "astra-toolbox",
+\n          "pytorch",
+\n          "torchvision",
+\n          "torchaudio",
+\n          "cudatoolkit=10.2",
+\n          "-c",
+\n          "pytorch",
+\n          "-c",
+\n          "astra-toolbox/label/dev"
+\n        ],
+\n        "pip_install": [
+\n          "/fourier_image_transformers-0.1.3-py3-none-any.whl"
+\n        ],
+\n        "activate": true
+\n      }
+\n    ],
+\n    [
+\n      "entrypoint",
+\n      "/neurodocker/startup.sh python"
+\n    ]
+\n  ]
+\n}' > /neurodocker/neurodocker_specs.json
+
+%environment
+export LANG="en_US.UTF-8"
+export LC_ALL="en_US.UTF-8"
+export ND_ENTRYPOINT="/neurodocker/startup.sh"
+export CONDA_DIR="/opt/miniconda-latest"
+export PATH="/opt/miniconda-latest/bin:$PATH"
+
+%files
+/home/tibuch/Gitrepos/FourierImageTransformer/dist/fourier_image_transformers-0.1.3-py3-none-any.whl /fourier_image_transformers-0.1.3-py3-none-any.whl
+
+%runscript
+/neurodocker/startup.sh python