Update imports for image transforms

cyclops/tasks/classification.py

@@ -7,9 +7,9 @@
 import numpy as np
 import pandas as pd
 from datasets import Dataset, DatasetDict, config
-from monai.transforms import Compose  # type: ignore
 from sklearn.compose import ColumnTransformer
 from sklearn.exceptions import NotFittedError
+from torchvision.transforms import Compose
 
 from cyclops.data.slicer import SliceSpec
 from cyclops.evaluate.evaluator import evaluate
@@ -419,7 +419,7 @@ def predict(
             splits_mapping = {"test": "test"}
         model_name, model = self.get_model(model_name)
         if transforms:
-            transforms = partial(apply_image_transforms, transforms=transforms)  # type: ignore
+            transforms = partial(apply_image_transforms, transforms=transforms)
         if isinstance(dataset, (Dataset, DatasetDict)):
             return model.predict(
                 dataset,

docs/source/tutorials/nihcxr/cxr_classification.ipynb

@@ -33,14 +33,15 @@
     "\n",
     "import numpy as np\n",
     "import plotly.express as px\n",
-    "from monai.transforms import Compose, Lambdad, Resized\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 (\n",
     "    SliceSpec,\n",
     "    filter_value,  # noqa: E402\n",
     ")\n",
+    "from cyclops.data.transforms import Lambdad, Resized\n",
     "from cyclops.data.utils import apply_transforms\n",
     "from cyclops.evaluate import evaluator\n",
     "from cyclops.evaluate.metrics.factory import create_metric\n",
@@ -635,9 +636,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "cyclops",
    "language": "python",
-   "name": "python3"
+   "name": "cyclops"
   },
   "language_info": {
    "codemirror_mode": {
@@ -649,7 +650,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.9.12"
   }
  },
  "nbformat": 4,

docs/source/tutorials/nihcxr/generate_nihcxr_report.py

@@ -8,14 +8,15 @@
 import numpy as np
 import numpy.typing as npt
 import plotly.express as px
-from monai.transforms import Compose, Lambdad, Resized  # type: ignore[attr-defined]
+from torchvision.transforms import Compose
 from torchxrayvision.models import DenseNet
 
 from cyclops.data.loader import load_nihcxr
 from cyclops.data.slicer import (
     SliceSpec,
     filter_value,  # noqa: E402
 )
+from cyclops.data.transforms import Lambdad, Resized
 from cyclops.data.utils import apply_transforms
 from cyclops.evaluate import evaluator
 from cyclops.evaluate.metrics.factory import create_metric
@@ -55,7 +56,7 @@
             allow_missing_keys=True,
         ),
         Lambdad(
-            ("image",),
+            keys=("image",),
             func=lambda x: np.mean(x, axis=0)[np.newaxis, :] if x.shape[0] != 1 else x,
         ),
     ],