added python face stylizer example

examples/face_stylizer/python/[MediaPipe_Python_Tasks]_Face_Stylizer.ipynb

@@ -0,0 +1,243 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "h2q27gKz1H20"
+      },
+      "source": [
+        "##### Copyright 2023 The MediaPipe Authors. All Rights Reserved."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "TUfAcER1oUS6"
+      },
+      "outputs": [],
+      "source": [
+        "#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+        "# you may not use this file except in compliance with the License.\n",
+        "# You may obtain a copy of the License at\n",
+        "#\n",
+        "# https://www.apache.org/licenses/LICENSE-2.0\n",
+        "#\n",
+        "# Unless required by applicable law or agreed to in writing, software\n",
+        "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+        "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+        "# See the License for the specific language governing permissions and\n",
+        "# limitations under the License."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "L_cQX8dWu4Dv"
+      },
+      "source": [
+        "# Face Stylizer\n",
+        "\n",
+        "This notebook shows you how to use the MediaPipe Tasks Python API to generate stylize faces given a model and input image. This is an experimental feature, so please report any bugs or issues in this sample through the [GitHub sample repo](https://github.com/googlesamples/mediapipe)."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "O6PN9FvIx614"
+      },
+      "source": [
+        "## Imports and Setup\n",
+        "Let's start with installing MediaPipe and the related dependencies."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "gxbHBsF-8Y_l"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install mediapipe"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "a49D7h4TVmru"
+      },
+      "source": [
+        "## Download the face stylizer model"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "The next thing you will need to do is download the face stylizer model that will be used for this demo. This model is already trained with a pre-determined style that will be used for face stylization."
+      ],
+      "metadata": {
+        "id": "QHXsuWDxpOj4"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "OMjuVQiDYJKF"
+      },
+      "outputs": [],
+      "source": [
+        "#@title Start downloading here.\n",
+        "!wget -O face_stylizer.task -q https://storage.googleapis.com/mediapipe-models/face_stylizer/blaze_face_stylizer/float32/latest/face_stylizer_color_sketch.task"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "83PEJNp9yPBU"
+      },
+      "source": [
+        "## Download a test image\n",
+        "\n",
+        "After downloading the model, you will need to download an image that you can use for testing! It's worth noting that while this is working with a single image, you can download a collection of images to store in the `IMAGE_FILENAMES` array."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "tzXuqyIBlXer"
+      },
+      "outputs": [],
+      "source": [
+        "import urllib\n",
+        "IMAGE_FILENAMES = ['portrait.jpg']\n",
+        "\n",
+        "for name in IMAGE_FILENAMES:\n",
+        "  url = f'https://storage.googleapis.com/mediapipe-assets/{name}'\n",
+        "  urllib.request.urlretrieve(url, name)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "P8XRmapjySMN"
+      },
+      "source": [
+        "## Preview the downloaded image"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "You can ensure that everything has downloaded correctly by using the following code to display the downloaded image."
+      ],
+      "metadata": {
+        "id": "Eu_q-Z03r-ed"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "8rjHk72-lmHX"
+      },
+      "outputs": [],
+      "source": [
+        "import cv2\n",
+        "from google.colab.patches import cv2_imshow\n",
+        "import math\n",
+        "\n",
+        "# Height and width that will be used by the model\n",
+        "DESIRED_HEIGHT = 480\n",
+        "DESIRED_WIDTH = 480\n",
+        "\n",
+        "# Performs resizing and showing the image\n",
+        "def resize_and_show(image):\n",
+        "  h, w = image.shape[:2]\n",
+        "  if h < w:\n",
+        "    img = cv2.resize(image, (DESIRED_WIDTH, math.floor(h/(w/DESIRED_WIDTH))))\n",
+        "  else:\n",
+        "    img = cv2.resize(image, (math.floor(w/(h/DESIRED_HEIGHT)), DESIRED_HEIGHT))\n",
+        "  cv2_imshow(img)\n",
+        "\n",
+        "\n",
+        "# Preview the image(s)\n",
+        "images = {name: cv2.imread(name) for name in IMAGE_FILENAMES}\n",
+        "for name, image in images.items():\n",
+        "  print(name)\n",
+        "  resize_and_show(image)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Iy4r2_ePylIa"
+      },
+      "source": [
+        "## Running inference and visualizing the results\n",
+        "To run inference using the face stylizer MediaPipe Task, you will need to initialize the `FaceStylizer` using the model. Once the stylizer has been initialized, you can use the sytlize method to apply the pre-trained model style onto your image."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Yl_Oiye4mUuo"
+      },
+      "outputs": [],
+      "source": [
+        "import numpy as np\n",
+        "import mediapipe as mp\n",
+        "\n",
+        "from mediapipe.tasks import python\n",
+        "from mediapipe.tasks.python import vision\n",
+        "\n",
+        "\n",
+        "# Create the options that will be used for FaceStylizer\n",
+        "base_options = python.BaseOptions(model_asset_path='face_stylizer.task')\n",
+        "options = vision.FaceStylizerOptions(base_options=base_options)\n",
+        "\n",
+        "# Create the face stylizer\n",
+        "with vision.FaceStylizer.create_from_options(options) as stylizer:\n",
+        "\n",
+        "  # Loop through demo image(s)\n",
+        "  for image_file_name in IMAGE_FILENAMES:\n",
+        "\n",
+        "    # Create the MediaPipe image file that will be stylized\n",
+        "    image = mp.Image.create_from_file(image_file_name)\n",
+        "    # Retrieve the stylized image\n",
+        "    stylized_image = stylizer.stylize(image)\n",
+        "\n",
+        "    # Show the stylized image\n",
+        "    rgb_stylized_image = cv2.cvtColor(stylized_image.numpy_view(), cv2.COLOR_BGR2RGB)\n",
+        "    resize_and_show(rgb_stylized_image)"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "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": "3.7.13"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}