Change read_network to use only model.xml (openvinotoolkit#198)

Author: helena-intel

notebooks/001-hello-world/001-hello-world.ipynb

@@ -2,114 +2,120 @@
  "cells": [
   {
    "cell_type": "markdown",
+   "id": "291dc37b",
+   "metadata": {},
    "source": [
     "# Hello World\n",
     "\n",
     "A very basic introduction to OpenVINO that shows how to do inference on a given IR model.\n",
     "\n",
     "We use a [MobileNetV3 model](https://docs.openvinotoolkit.org/latest/omz_models_model_mobilenet_v3_small_1_0_224_tf.html) from [Open Model Zoo](https://github.com/openvinotoolkit/open_model_zoo/). See the [TensorFlow to OpenVINO Notebook](101-tensorflow-to-openvino) for information on how this OpenVINO IR model was created.\n",
     "\n"
-   ],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "markdown",
+   "id": "e4c8cbe5",
+   "metadata": {},
    "source": [
     "## Imports"
-   ],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "41ee9436",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "import json\n",
     "\n",
     "import cv2\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "from openvino.inference_engine import IECore"
-   ],
-   "outputs": [],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "markdown",
+   "id": "55e49ae7",
+   "metadata": {},
    "source": [
     "## Load the network"
-   ],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "e3c4d6fc",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "ie = IECore()\n",
-    "net = ie.read_network(\n",
-    "    model=\"model/v3-small_224_1.0_float.xml\", weights=\"model/v3-small_224_1.0_float.bin\"\n",
-    ")\n",
+    "net = ie.read_network(model=\"model/v3-small_224_1.0_float.xml\")\n",
     "exec_net = ie.load_network(net, \"CPU\")\n",
     "\n",
-    "input_key = list(exec_net.input_info)[0]\n",
-    "output_key = list(exec_net.outputs.keys())[0]"
-   ],
-   "outputs": [],
-   "metadata": {}
+    "input_key = next(iter(exec_net.input_info))\n",
+    "output_key = next(iter(exec_net.outputs.keys()))"
+   ]
   },
   {
    "cell_type": "markdown",
+   "id": "a19fc080",
+   "metadata": {},
    "source": [
     "## Load an Image"
-   ],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "eca45b68",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# The MobileNet network expects images in RGB format\n",
     "image = cv2.cvtColor(cv2.imread(\"data/coco.jpg\"), cv2.COLOR_BGR2RGB)\n",
-    "input_image = cv2.resize(image, (224, 224))  # resize to MobileNet image shape\n",
-    "input_image = np.expand_dims(\n",
-    "    input_image.transpose(2, 0, 1), 0\n",
-    ")  # reshape to network input shape\n",
-    "plt.imshow(image)"
-   ],
-   "outputs": [],
-   "metadata": {}
+    "# resize to MobileNet image shape\n",
+    "input_image = cv2.resize(image, (224, 224))\n",
+    "# reshape to network input shape\n",
+    "input_image = np.expand_dims(input_image.transpose(2, 0, 1), 0)\n",
+    "plt.imshow(image);"
+   ]
   },
   {
    "cell_type": "markdown",
+   "id": "6be327b6",
+   "metadata": {},
    "source": [
     "## Do Inference"
-   ],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "1ed78a71",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "result = exec_net.infer(inputs={input_key: input_image})[output_key]\n",
     "result_index = np.argmax(result)"
-   ],
-   "outputs": [],
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "bf29578c",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# Convert the inference result to a class name.\n",
     "imagenet_classes = json.loads(open(\"utils/imagenet_class_index.json\").read())\n",
     "# The model description states that for this model, class 0 is background,\n",
     "# so we add 1 to the network output to get the class name\n",
-    "imagenet_classes = {\n",
-    "    int(key) + 1: value for key, value in imagenet_classes.items()\n",
-    "}\n",
+    "imagenet_classes = {int(key) + 1: value for key, value in imagenet_classes.items()}\n",
     "imagenet_classes[result_index]"
-   ],
-   "outputs": [],
-   "metadata": {}
+   ]
   }
  ],
  "metadata": {
@@ -133,4 +139,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}