fix monitor-api notebook

VectorInstitute · Nov 21, 2023 · 08b4659 · 08b4659
1 parent 3c4da81
commit 08b4659
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Showing 2 changed files with 17 additions and 8 deletions.
diff --git a/cyclops/data/transforms.py b/cyclops/data/transforms.py
@@ -45,7 +45,7 @@ def __init__(
         allow_missing_keys: bool = False,
     ):
         self.transform = Dictd(
-            transform=Lambda(func=func),
+            transform=Lambda(func),
             keys=keys,
             allow_missing_keys=allow_missing_keys,
         )
@@ -70,7 +70,7 @@ def __init__(
         allow_missing_keys: bool = False,
     ):
         self.transform = Dictd(
-            transform=Resize(spatial_size=spatial_size),
+            transform=Resize(size=spatial_size),
             keys=keys,
             allow_missing_keys=allow_missing_keys,
         )

diff --git a/docs/source/tutorials/nihcxr/monitor_api.ipynb b/docs/source/tutorials/nihcxr/monitor_api.ipynb
@@ -26,17 +26,25 @@
     "\"\"\"NIHCXR Clinical Drift Experiments Tutorial.\"\"\"\n",
     "\n",
     "\n",
+    "import random\n",
+    "\n",
     "import numpy as np\n",
-    "from monai.transforms import Compose, Lambdad, Resized\n",
+    "import torch\n",
+    "from torchvision.transforms import Compose\n",
     "from torchxrayvision.models import DenseNet\n",
     "\n",
     "from cyclops.data.loader import load_nihcxr\n",
     "from cyclops.data.slicer import SliceSpec\n",
+    "from cyclops.data.transforms import Lambdad, Resized\n",
     "from cyclops.monitor import ClinicalShiftApplicator, Detector, Reductor, TSTester\n",
     "from cyclops.monitor.plotter import plot_drift_experiment, plot_drift_timeseries\n",
     "\n",
     "\n",
-    "nih_ds = load_nihcxr(\"/mnt/data/clinical_datasets/NIHCXR\")[\"test\"]"
+    "nih_ds = load_nihcxr(\"/mnt/data/clinical_datasets/NIHCXR\")[\"test\"]\n",
+    "\n",
+    "random.seed(42)\n",
+    "np.random.seed(42)\n",
+    "torch.manual_seed(42)"
    ]
   },
   {
@@ -65,18 +73,19 @@
     "transforms = Compose(\n",
     "    [\n",
     "        Resized(\n",
-    "            keys=(\"image\",),\n",
     "            spatial_size=(224, 224),\n",
+    "            keys=(\"image\",),\n",
     "            allow_missing_keys=True,\n",
     "        ),\n",
     "        Lambdad(\n",
-    "            keys=(\"image\",),\n",
     "            func=lambda x: ((2 * (x / 255.0)) - 1.0) * 1024,\n",
+    "            keys=(\"image\",),\n",
     "            allow_missing_keys=True,\n",
     "        ),\n",
     "        Lambdad(\n",
-    "            (\"image\",),\n",
-    "            func=lambda x: np.mean(x, axis=0)[np.newaxis, :] if x.shape[0] != 1 else x,\n",
+    "            func=lambda x: x[0][np.newaxis, :] if x.shape[0] != 1 else x,\n",
+    "            keys=(\"image\",),\n",
+    "            allow_missing_keys=True,\n",
     "        ),\n",
     "    ],\n",
     ")"