initial jupyter notebook + sample image

examples/python_unet/unet_inference.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "0c406267",
+   "metadata": {},
+   "source": [
+    "## Import MIGraphX Python Library"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c33a7caf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import migraphx"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "679b7860",
+   "metadata": {},
+   "source": [
+    "## Fetch U-NET ONNX Model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5303185a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!wget "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ecdc9943",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c34d0012",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ac3742a9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a5526b1f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1eab2d51",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}