remove task type from metric notebooks

Author: djdameln

notebooks/700_metrics/701a_aupimo.ipynb

@@ -71,7 +71,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -102,7 +102,6 @@
     "from matplotlib.ticker import MaxNLocator, PercentFormatter\n",
     "from scipy import stats\n",
     "\n",
-    "from anomalib import TaskType\n",
     "from anomalib.data import MVTec\n",
     "from anomalib.engine import Engine\n",
     "from anomalib.metrics import AUPIMO, Evaluator\n",
@@ -111,7 +110,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -132,18 +131,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "task = TaskType.SEGMENTATION\n",
     "datamodule = MVTec(\n",
     "    root=dataset_root,\n",
     "    category=\"leather\",\n",
     "    train_batch_size=32,\n",
     "    eval_batch_size=32,\n",
     "    num_workers=8,\n",
-    "    task=task,\n",
     ")"
    ]
   },
@@ -279,7 +276,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [

notebooks/700_metrics/701b_aupimo_advanced_i.ipynb

@@ -77,7 +77,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -98,7 +98,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -111,7 +111,6 @@
     "from matplotlib.ticker import PercentFormatter\n",
     "from scipy import stats\n",
     "\n",
-    "from anomalib import TaskType\n",
     "from anomalib.data import MVTec\n",
     "from anomalib.data.utils import read_image\n",
     "from anomalib.engine import Engine\n",
@@ -121,7 +120,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -130,7 +129,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -160,14 +159,12 @@
    "outputs": [],
    "source": [
     "# train the model\n",
-    "task = TaskType.SEGMENTATION\n",
     "datamodule = MVTec(\n",
     "    root=dataset_root,\n",
     "    category=\"leather\",\n",
     "    train_batch_size=32,\n",
     "    eval_batch_size=32,\n",
     "    num_workers=8,\n",
-    "    task=task,\n",
     ")\n",
     "evaluator = Evaluator(test_metrics=AUPIMO())\n",
     "model = Padim(\n",
@@ -379,7 +376,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -752,7 +749,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [

notebooks/700_metrics/701c_aupimo_advanced_ii.ipynb

@@ -114,7 +114,6 @@
     "from scipy import stats\n",
     "from torch import Tensor\n",
     "\n",
-    "from anomalib import TaskType\n",
     "from anomalib.data import MVTec\n",
     "from anomalib.data.utils import read_image\n",
     "from anomalib.engine import Engine\n",
@@ -154,14 +153,12 @@
    "outputs": [],
    "source": [
     "# train the model\n",
-    "task = TaskType.SEGMENTATION\n",
     "datamodule = MVTec(\n",
     "    root=dataset_root,\n",
     "    category=\"leather\",\n",
     "    train_batch_size=32,\n",
     "    eval_batch_size=32,\n",
     "    num_workers=8,\n",
-    "    task=task,\n",
     ")\n",
     "evaluator = Evaluator(test_metrics=AUPIMO())\n",
     "model = Padim(\n",