DCT-Net/notebooks/inference.ipynb

{
 "nbformat": 4,
 "nbformat_minor": 0,
 "metadata": {
  "colab": {
   "provenance": [],
   "collapsed_sections": []
  },
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3"
  },
  "language_info": {
   "name": "python"
  }
 },
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "x[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/menyifang/DCT-Net/blob/main/notebooks/inference.ipynb)"
   ],
   "metadata": {
    "id": "D2MFmZtpVEp_"
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Step 1: Installation"
   ],
   "metadata": {
    "id": "zoNN1PYUOUgU"
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "7Tv2ZUgrGO6Z"
   },
   "outputs": [],
   "source": [
    "!pip install tensorflow\n",
    "!pip install \"modelscope[cv]\" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html"
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Step 2: Transfer image"
   ],
   "metadata": {
    "id": "kTiXDn7_OTMy"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "!wget 'https://invi-label.oss-cn-shanghai.aliyuncs.com/label/cartoon/image_cartoon.png'"
   ],
   "metadata": {
    "id": "lL2JQBL5Qqjn"
   },
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "### portrait stylization with 'anime' style\n",
    "\n",
    "import cv2\n",
    "from modelscope.outputs import OutputKeys\n",
    "from modelscope.pipelines import pipeline\n",
    "from modelscope.utils.constant import Tasks\n",
    "\n",
    "img_cartoon = pipeline(Tasks.image_portrait_stylization, \n",
    "                       model='damo/cv_unet_person-image-cartoon_compound-models')\n",
    "img_path = 'image_cartoon.png'\n",
    "result = img_cartoon(img_path)\n",
    "cv2.imwrite('result_anime.png', result[OutputKeys.OUTPUT_IMG])\n",
    "print('finished!')\n"
   ],
   "metadata": {
    "id": "IiuxwjdcJkAf"
   },
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "### portrait stylization with '3d' style\n",
    "\n",
    "import cv2\n",
    "from modelscope.outputs import OutputKeys\n",
    "from modelscope.pipelines import pipeline\n",
    "from modelscope.utils.constant import Tasks\n",
    "\n",
    "img_cartoon = pipeline(Tasks.image_portrait_stylization, \n",
    "                       model='damo/cv_unet_person-image-cartoon-3d_compound-models')\n",
    "img_path = 'image_cartoon.png'\n",
    "result = img_cartoon(img_path)\n",
    "cv2.imwrite('result_3d.png', result[OutputKeys.OUTPUT_IMG])\n",
    "print('finished!')"
   ],
   "metadata": {
    "id": "FvESA08aPC5a"
   },
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "### portrait stylization with 'handdrawn' style\n",
    "\n",
    "import cv2\n",
    "from modelscope.outputs import OutputKeys\n",
    "from modelscope.pipelines import pipeline\n",
    "from modelscope.utils.constant import Tasks\n",
    "\n",
    "img_cartoon = pipeline(Tasks.image_portrait_stylization, \n",
    "                       model='damo/cv_unet_person-image-cartoon-handdrawn_compound-models')\n",
    "img_path = 'image_cartoon.png'\n",
    "result = img_cartoon(img_path)\n",
    "cv2.imwrite('result_handdrawn.png', result[OutputKeys.OUTPUT_IMG])\n",
    "print('finished!')\n"
   ],
   "metadata": {
    "id": "MZdiNAuTPm-t"
   },
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "### portrait stylization with 'sketch' style\n",
    "\n",
    "import cv2\n",
    "from modelscope.outputs import OutputKeys\n",
    "from modelscope.pipelines import pipeline\n",
    "from modelscope.utils.constant import Tasks\n",
    "\n",
    "img_cartoon = pipeline(Tasks.image_portrait_stylization, \n",
    "                       model='damo/cv_unet_person-image-cartoon-sketch_compound-models')\n",
    "img_path = 'image_cartoon.png'\n",
    "result = img_cartoon(img_path)\n",
    "cv2.imwrite('result_sketch.png', result[OutputKeys.OUTPUT_IMG])\n",
    "print('finished!')"
   ],
   "metadata": {
    "id": "1Dut6IQ4PnMA"
   },
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "### portrait stylization with 'artstyle' style\n",
    "\n",
    "import cv2\n",
    "from modelscope.outputs import OutputKeys\n",
    "from modelscope.pipelines import pipeline\n",
    "from modelscope.utils.constant import Tasks\n",
    "\n",
    "img_cartoon = pipeline(Tasks.image_portrait_stylization, \n",
    "                       model='damo/cv_unet_person-image-cartoon-artstyle_compound-models')\n",
    "img_path = 'image_cartoon.png'\n",
    "result = img_cartoon(img_path)\n",
    "cv2.imwrite('result_artstyle.png', result[OutputKeys.OUTPUT_IMG])\n",
    "print('finished!')\n"
   ],
   "metadata": {
    "id": "gNchD8nGPnZE"
   },
   "execution_count": null,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Step 3: Visualize results"
   ],
   "metadata": {
    "id": "fShi4lT-ODdE"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "### Visualize source image and stylized result\n",
    "from matplotlib import pyplot as plt\n",
    "def vis_img(path):\n",
    "  img = cv2.imread(path,-1)\n",
    "  plt.imshow(img[..., ::-1])\n",
    "  plt.axis(\"off\")\n",
    "  plt.show()\n",
    "\n",
    "vis_img('image_cartoon.png')\n",
    "vis_img('result_anime.png')\n",
    "vis_img('result_3d.png')\n",
    "vis_img('result_handdrawn.png')\n",
    "vis_img('result_sketch.png')\n",
    "vis_img('result_artstyle.png')"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "k7Llm0SWMLKr",
    "outputId": "20b665ce-653e-48a9-c489-d66e93e1907f"
   },
   "execution_count": 21,
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": "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
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": "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
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": "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
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": "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
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": "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
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": "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
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ]
  }
 ]
}