diff --git a/3d_segmentation/brats_segmentation_3d.ipynb b/3d_segmentation/brats_segmentation_3d.ipynb index 522d5f54af..407e063d90 100644 --- a/3d_segmentation/brats_segmentation_3d.ipynb +++ b/3d_segmentation/brats_segmentation_3d.ipynb @@ -266,9 +266,9 @@ " # load 4 Nifti images and stack them together\n", " LoadImaged(keys=[\"image\", \"label\"]),\n", " EnsureChannelFirstd(keys=\"image\"),\n", + " Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\"),\n", " FromMetaTensord(keys=[\"image\", \"label\"]),\n", " ConvertToMultiChannelBasedOnBratsClassesd(keys=\"label\"),\n", - " Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\"),\n", " Spacingd(\n", " keys=[\"image\", \"label\"],\n", " pixdim=(1.0, 1.0, 1.0),\n", @@ -288,9 +288,9 @@ " [\n", " LoadImaged(keys=[\"image\", \"label\"]),\n", " EnsureChannelFirstd(keys=\"image\"),\n", + " Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\"),\n", " FromMetaTensord(keys=[\"image\", \"label\"]),\n", " ConvertToMultiChannelBasedOnBratsClassesd(keys=\"label\"),\n", - " Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\"),\n", " Spacingd(\n", " keys=[\"image\", \"label\"],\n", " pixdim=(1.0, 1.0, 1.0),\n", @@ -787,9 +787,9 @@ " [\n", " LoadImaged(keys=[\"image\", \"label\"]),\n", " EnsureChannelFirstd(keys=[\"image\"]),\n", + " Orientationd(keys=[\"image\"], axcodes=\"RAS\"),\n", " FromMetaTensord(keys=[\"image\", \"label\"]),\n", " ConvertToMultiChannelBasedOnBratsClassesd(keys=\"label\"),\n", - " Orientationd(keys=[\"image\"], axcodes=\"RAS\"),\n", " Spacingd(keys=[\"image\"], pixdim=(1.0, 1.0, 1.0), mode=\"bilinear\"),\n", " NormalizeIntensityd(keys=\"image\", nonzero=True, channel_wise=True),\n", " EnsureTyped(keys=[\"image\", \"label\"]),\n", diff --git a/3d_segmentation/spleen_segmentation_3d.ipynb b/3d_segmentation/spleen_segmentation_3d.ipynb index 77ebef0431..174616636f 100644 --- a/3d_segmentation/spleen_segmentation_3d.ipynb +++ b/3d_segmentation/spleen_segmentation_3d.ipynb @@ -281,8 +281,8 @@ " [\n", " LoadImaged(keys=[\"image\", \"label\"]),\n", " EnsureChannelFirstd(keys=[\"image\", \"label\"]),\n", - " FromMetaTensord(keys=[\"image\", \"label\"]),\n", " Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\"),\n", + " FromMetaTensord(keys=[\"image\", \"label\"]),\n", " Spacingd(keys=[\"image\", \"label\"], pixdim=(\n", " 1.5, 1.5, 2.0), mode=(\"bilinear\", \"nearest\")),\n", " ScaleIntensityRanged(\n", @@ -314,8 +314,8 @@ " [\n", " LoadImaged(keys=[\"image\", \"label\"]),\n", " EnsureChannelFirstd(keys=[\"image\", \"label\"]),\n", - " FromMetaTensord(keys=[\"image\", \"label\"]),\n", " Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\"),\n", + " FromMetaTensord(keys=[\"image\", \"label\"]),\n", " Spacingd(keys=[\"image\", \"label\"], pixdim=(\n", " 1.5, 1.5, 2.0), mode=(\"bilinear\", \"nearest\")),\n", " ScaleIntensityRanged(\n", @@ -696,8 +696,8 @@ " [\n", " LoadImaged(keys=[\"image\", \"label\"]),\n", " EnsureChannelFirstd(keys=[\"image\", \"label\"]),\n", - " FromMetaTensord(keys=[\"image\", \"label\"]),\n", " Orientationd(keys=[\"image\"], axcodes=\"RAS\"),\n", + " FromMetaTensord(keys=[\"image\", \"label\"]),\n", " Spacingd(keys=[\"image\"], pixdim=(\n", " 1.5, 1.5, 2.0), mode=\"bilinear\"),\n", " ScaleIntensityRanged(\n", @@ -791,8 +791,8 @@ " [\n", " LoadImaged(keys=\"image\"),\n", " EnsureChannelFirstd(keys=\"image\"),\n", - " FromMetaTensord(keys=\"image\"),\n", " Orientationd(keys=[\"image\"], axcodes=\"RAS\"),\n", + " FromMetaTensord(keys=\"image\"),\n", " Spacingd(keys=[\"image\"], pixdim=(\n", " 1.5, 1.5, 2.0), mode=\"bilinear\"),\n", " ScaleIntensityRanged(\n", diff --git a/3d_segmentation/spleen_segmentation_3d_lightning.ipynb b/3d_segmentation/spleen_segmentation_3d_lightning.ipynb index a0b9be76ca..83366499b1 100644 --- a/3d_segmentation/spleen_segmentation_3d_lightning.ipynb +++ b/3d_segmentation/spleen_segmentation_3d_lightning.ipynb @@ -271,8 +271,8 @@ " [\n", " LoadImaged(keys=[\"image\", \"label\"]),\n", " AddChanneld(keys=[\"image\", \"label\"]),\n", - " FromMetaTensord(keys=[\"image\", \"label\"]),\n", " Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\"),\n", + " FromMetaTensord(keys=[\"image\", \"label\"]),\n", " Spacingd(\n", " keys=[\"image\", \"label\"],\n", " pixdim=(1.5, 1.5, 2.0),\n", @@ -312,8 +312,8 @@ " [\n", " LoadImaged(keys=[\"image\", \"label\"]),\n", " AddChanneld(keys=[\"image\", \"label\"]),\n", - " FromMetaTensord(keys=[\"image\", \"label\"]),\n", " Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\"),\n", + " FromMetaTensord(keys=[\"image\", \"label\"]),\n", " Spacingd(\n", " keys=[\"image\", \"label\"],\n", " pixdim=(1.5, 1.5, 2.0),\n", diff --git a/modules/decollate_batch.ipynb b/modules/decollate_batch.ipynb index a7300f4a68..3232be99ee 100644 --- a/modules/decollate_batch.ipynb +++ b/modules/decollate_batch.ipynb @@ -246,8 +246,8 @@ " [\n", " LoadImaged(keys=[\"img\", \"seg\"]),\n", " EnsureChannelFirstd(keys=[\"img\", \"seg\"]),\n", - " FromMetaTensord(keys=[\"img\", \"seg\"]),\n", " Orientationd(keys=\"img\", axcodes=\"RAS\"),\n", + " FromMetaTensord(keys=[\"img\", \"seg\"]),\n", " Resized(keys=\"img\", spatial_size=(96, 96, 96), mode=\"trilinear\", align_corners=True),\n", " ScaleIntensityd(keys=\"img\"),\n", " EnsureTyped(keys=[\"img\", \"seg\"]),\n", diff --git a/modules/integrate_3rd_party_transforms.ipynb b/modules/integrate_3rd_party_transforms.ipynb index a6a5ad6de8..cc14e1dc90 100644 --- a/modules/integrate_3rd_party_transforms.ipynb +++ b/modules/integrate_3rd_party_transforms.ipynb @@ -267,10 +267,10 @@ "source": [ "monai_transforms = [\n", " LoadImaged(keys=[\"image\", \"label\"]),\n", - " FromMetaTensord(keys=[\"image\", \"label\"]),\n", - " ToNumpyd(keys=[\"image\", \"label\", \"image_meta_dict\", \"label_meta_dict\"]),\n", " AddChanneld(keys=[\"image\", \"label\"]),\n", " Orientationd(keys=[\"image\", \"label\"], axcodes=\"RAS\"),\n", + " FromMetaTensord(keys=[\"image\", \"label\"]),\n", + " ToNumpyd(keys=[\"image\", \"label\", \"image_meta_dict\", \"label_meta_dict\"]),\n", " Spacingd(keys=[\"image\", \"label\"], pixdim=(\n", " 1.5, 1.5, 2.0), mode=(\"bilinear\", \"nearest\")),\n", " ScaleIntensityRanged(keys=[\"image\"], a_min=-57,\n", diff --git a/modules/interpretability/cats_and_dogs.ipynb b/modules/interpretability/cats_and_dogs.ipynb index 2fcb526986..c00ea11174 100644 --- a/modules/interpretability/cats_and_dogs.ipynb +++ b/modules/interpretability/cats_and_dogs.ipynb @@ -165,8 +165,8 @@ "divisible_factor = 20\n", "transforms = Compose([\n", " LoadImaged(\"image\"),\n", - " FromMetaTensord(\"image\"),\n", " AsChannelFirstd(\"image\"),\n", + " FromMetaTensord(\"image\"),\n", " ScaleIntensityd(\"image\"),\n", " Rotate90d(\"image\", k=3),\n", " DivisiblePadd(\"image\", k=divisible_factor),\n", @@ -202,7 +202,7 @@ " axes = np.asarray(axes) if nims == 1 else axes\n", " for d, ax in zip(data, axes.ravel()):\n", " # channel last for matplotlib\n", - " im = np.moveaxis(d[\"image\"], 0, -1)\n", + " im = np.moveaxis(d[\"image\"].cpu().numpy(), 0, -1)\n", " ax.imshow(im, cmap='gray')\n", " ax.set_title(Animals(d['label']).name, fontsize=25)\n", " ax.axis(\"off\")\n", diff --git a/modules/nifti_read_example.ipynb b/modules/nifti_read_example.ipynb index 6b2ff1fda3..3d73ef19b8 100644 --- a/modules/nifti_read_example.ipynb +++ b/modules/nifti_read_example.ipynb @@ -89,7 +89,6 @@ "\n", "import glob\n", "import os\n", - "import shutil\n", "import tempfile\n", "\n", "import nibabel as nib\n", @@ -113,30 +112,6 @@ "print_config()" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Setup data directory\n", - "\n", - "You can specify a directory with the `MONAI_DATA_DIRECTORY` environment variable. \n", - "This allows you to save results and reuse downloads. \n", - "If not specified a temporary directory will be used." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "directory = os.environ.get(\"MONAI_DATA_DIRECTORY\")\n", - "root_dir = tempfile.mkdtemp() if directory is None else directory\n", - "print(root_dir)" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -150,6 +125,7 @@ "metadata": {}, "outputs": [], "source": [ + "root_dir = tempfile.mkdtemp()\n", "for i in range(5):\n", " im, seg = create_test_image_3d(128, 128, 128)\n", "\n", @@ -189,9 +165,9 @@ "imtrans = Compose(\n", " [\n", " LoadImage(),\n", + " AddChannel(),\n", " ToNumpy(),\n", " ScaleIntensity(),\n", - " AddChannel(),\n", " RandSpatialCrop((64, 64, 64), random_size=False),\n", " EnsureType(),\n", " ]\n", @@ -200,8 +176,8 @@ "segtrans = Compose(\n", " [\n", " LoadImage(),\n", - " ToNumpy(),\n", " AddChannel(),\n", + " ToNumpy(),\n", " RandSpatialCrop((64, 64, 64), random_size=False),\n", " EnsureType(),\n", " ]\n", @@ -263,25 +239,6 @@ "im, seg = first(loader)\n", "print(\"image shapes:\", im.shape, seg.shape)" ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Cleanup data directory\n", - "\n", - "Remove directory if a temporary was used." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "if directory is None:\n", - " shutil.rmtree(root_dir)" - ] } ], "metadata": {