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neuronets · Oct 26, 2022 · 908c879 · 908c879
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Showing 2 changed files with 199 additions and 47 deletions.
diff --git a/guide/api_train_binary_segmentation.ipynb b/guide/api_train_binary_segmentation.ipynb
@@ -3,7 +3,10 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "ijHnNTIjDkt0"
+    "id": "ijHnNTIjDkt0",
+    "pycharm": {
+     "name": "#%% md\n"
+    }
    },
    "source": [
     "# Train a neural network for binary volumetric segmentation\n",
@@ -38,14 +41,17 @@
    },
    "outputs": [],
    "source": [
-    "!pip install --no-cache-dir nilearn https://github.com/neuronets/nobrainer/archive/refs/heads/enh/api.zip"
+    "!pip install --no-cache-dir nilearn nobrainer"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "Ht_CGSk1Dkt3"
+    "id": "Ht_CGSk1Dkt3",
+    "pycharm": {
+     "name": "#%%\n"
+    }
    },
    "outputs": [],
    "source": [
@@ -58,7 +64,10 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "hVCchp9uDkt3"
+    "id": "hVCchp9uDkt3",
+    "pycharm": {
+     "name": "#%% md\n"
+    }
    },
    "source": [
     "# Get sample features and labels\n",
@@ -70,7 +79,10 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "YpqTxNu4Dkt4"
+    "id": "YpqTxNu4Dkt4",
+    "pycharm": {
+     "name": "#%%\n"
+    }
    },
    "outputs": [],
    "source": [
@@ -81,7 +93,10 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "m3P3BUQKiCjg"
+    "id": "m3P3BUQKiCjg",
+    "pycharm": {
+     "name": "#%% md\n"
+    }
    },
    "source": [
     "Here is an example of one training pair, with the brainmask overlaid on the anatomical image."
@@ -90,7 +105,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [],
    "source": [
     "filepaths[0]"
@@ -100,7 +119,10 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "9tAhbM4ChgIj"
+    "id": "9tAhbM4ChgIj",
+    "pycharm": {
+     "name": "#%%\n"
+    }
    },
    "outputs": [],
    "source": [
@@ -113,7 +135,10 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "ScgF78rmDkt4"
+    "id": "ScgF78rmDkt4",
+    "pycharm": {
+     "name": "#%% md\n"
+    }
    },
    "source": [
     "# Convert medical images to TFRecords\n",
@@ -125,7 +150,10 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "n7lCL-55Ta4R"
+    "id": "n7lCL-55Ta4R",
+    "pycharm": {
+     "name": "#%%\n"
+    }
    },
    "outputs": [],
    "source": [
@@ -136,7 +164,10 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "Q3zPyRlbTa4R"
+    "id": "Q3zPyRlbTa4R",
+    "pycharm": {
+     "name": "#%%\n"
+    }
    },
    "outputs": [],
    "source": [
@@ -171,7 +202,10 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "X8u_owicTa4T"
+    "id": "X8u_owicTa4T",
+    "pycharm": {
+     "name": "#%%\n"
+    }
    },
    "outputs": [],
    "source": [
@@ -183,7 +217,10 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "RhJ7upa5Ta4T"
+    "id": "RhJ7upa5Ta4T",
+    "pycharm": {
+     "name": "#%%\n"
+    }
    },
    "outputs": [],
    "source": [
@@ -194,7 +231,10 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "oKQm8qrOTa4U"
+    "id": "oKQm8qrOTa4U",
+    "pycharm": {
+     "name": "#%%\n"
+    }
    },
    "outputs": [],
    "source": [
@@ -212,7 +252,10 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "OWqLu2xFTa4U"
+    "id": "OWqLu2xFTa4U",
+    "pycharm": {
+     "name": "#%%\n"
+    }
    },
    "outputs": [],
    "source": [
@@ -227,7 +270,10 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "4xJxR7Ddbd-0"
+    "id": "4xJxR7Ddbd-0",
+    "pycharm": {
+     "name": "#%%\n"
+    }
    },
    "outputs": [],
    "source": [
@@ -237,7 +283,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
    "source": [
     "1. Save model\n",
     "2. Load model back as a class instance\n",
@@ -248,7 +298,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [],
    "source": [
     "bem.save(\"data/testsave\")"
@@ -257,7 +311,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [],
    "source": [
     "from nobrainer.processing.segmentation import Segmentation\n",
@@ -267,7 +325,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [],
    "source": [
     "image_path = filepaths[0][0]\n",
@@ -278,7 +340,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [],
    "source": [
     "bem.fit(dataset_train=dataset_train,\n",
@@ -291,7 +357,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [],
    "source": []
   }
@@ -322,4 +392,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}