SimSwap colab.ipynb

@@ -127,9 +127,7 @@
         "outputId": "9691a7a4-192e-4ec2-c3c1-1f2c933d7b6a"
       },
       "source": [
-        "!pip install insightface==0.2.1 onnxruntime moviepy\n",
+        "!pip install insightface==0.2.1 onnxruntime imageio==2.4.1"
-        "!pip install googledrivedownloader\n",
-        "!pip install imageio==2.4.1"
       ],
       "execution_count": 3,
       "outputs": [
@@ -224,13 +222,9 @@
         "outputId": "e93c3f98-01df-458e-b791-c32f7343e705"
       },
       "source": [
-        "from google_drive_downloader import GoogleDriveDownloader\n",
-        "\n",
         "### it seems that google drive link may not be permenant, you can find this ID from our open url.\n",
-        "# GoogleDriveDownloader.download_file_from_google_drive(file_id='1TLNdIufzwesDbyr_nVTR7Zrx9oRHLM_N',\n",
+        "# !mkdir arcface_model && gdown --id 1TLNdIufzwesDbyr_nVTR7Zrx9oRHLM_N -O ./arcface_model/arcface_checkpoint.tar\n",
-        "#                                     dest_path='./arcface_model/arcface_checkpoint.tar')\n",
+        "# !gdown --id 1PXkRiBUYbu1xWpQyDEJvGKeqqUFthJcI -O checkpoints.zip\n",
-        "# GoogleDriveDownloader.download_file_from_google_drive(file_id='1PXkRiBUYbu1xWpQyDEJvGKeqqUFthJcI',\n",
-        "#                                     dest_path='./checkpoints.zip')\n",
         "\n",
         "!wget -P ./arcface_model https://github.com/neuralchen/SimSwap/releases/download/1.0/arcface_checkpoint.tar\n",
         "!wget https://github.com/neuralchen/SimSwap/releases/download/1.0/checkpoints.zip\n",
@@ -278,7 +272,7 @@
         "### open url(can be found at [our repo]/doc/guidance/preparation.md) and copy the assigned download link here.\n",
         "### many thanks to woctezuma for this very useful help\n",
         "!wget --no-check-certificate \"https://sh23tw.dm.files.1drv.com/y4mmGiIkNVigkSwOKDcV3nwMJulRGhbtHdkheehR5TArc52UjudUYNXAEvKCii2O5LAmzGCGK6IfleocxuDeoKxDZkNzDRSt4ZUlEt8GlSOpCXAFEkBwaZimtWGDRbpIGpb_pz9Nq5jATBQpezBS6G_UtspWTkgrXHHxhviV2nWy8APPx134zOZrUIbkSF6xnsqzs3uZ_SEX_m9Rey0ykpx9w\" -O antelope.zip\n",
-        "!unzip ./antelope.zip -d ./insightface_func/models/\n"
+        "!unzip ./antelope.zip -d ./insightface_func/models/"
       ],
       "execution_count": 6,
       "outputs": [
@@ -326,7 +320,6 @@
       "source": [
         "import cv2\n",
         "import torch\n",
-        "import fractions\n",
         "import numpy as np\n",
         "from PIL import Image\n",
         "import torch.nn.functional as F\n",
@@ -334,8 +327,7 @@
         "from models.models import create_model\n",
         "from options.test_options import TestOptions\n",
         "from insightface_func.face_detect_crop_multi import Face_detect_crop\n",
-        "from util.videoswap import video_swap\n",
+        "from util.videoswap import video_swap"
-        "from util.add_watermark import watermark_image"
       ],
       "execution_count": 7,
       "outputs": [
@@ -352,6 +344,26 @@
         }
       ]
     },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from IPython.display import HTML\n",
+        "from base64 import b64encode\n",
+        "\n",
+        "\n",
+        "def show_mp4(filename, width=720):\n",
+        "    mp4 = open(filename, 'rb').read()\n",
+        "    data_url = \"data:video/mp4;base64,\" + b64encode(mp4).decode()\n",
+        "    display(HTML(\"\"\"\n",
+        "    <video width=\"%d\" controls autoplay loop>\n",
+        "        <source src=\"%s\" type=\"video/mp4\">\n",
+        "    </video>\n",
+        "    \"\"\" % (width, data_url)))"
+      ]
+    },
     {
       "cell_type": "code",
       "metadata": {
@@ -360,7 +372,7 @@
       "source": [
         "transformer = transforms.Compose([\n",
         "        transforms.ToTensor(),\n",
-        "        #transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
+        "        # transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
         "    ])\n",
         "\n",
         "transformer_Arcface = transforms.Compose([\n",
@@ -388,10 +400,10 @@
       "source": [
         "opt = TestOptions()\n",
         "opt.initialize()\n",
-        "opt.parser.add_argument('-f') ## dummy arg to avoid bug\n",
+        "opt.parser.add_argument('-f')  # dummy arg to avoid bug\n",
         "opt = opt.parse()\n",
-        "opt.pic_a_path = './demo_file/Iron_man.jpg' ## or replace it with image from your own google drive\n",
+        "opt.pic_a_path = './demo_file/Iron_man.jpg'  # or replace it with image from your own google drive\n",
-        "opt.video_path = './demo_file/multi_people_1080p.mp4' ## or replace it with video from your own google drive\n",
+        "opt.video_path = './demo_file/multi_people_1080p.mp4'  # or replace it with video from your own google drive\n",
         "opt.output_path = './output/demo.mp4'\n",
         "opt.temp_path = './tmp'\n",
         "opt.Arc_path = './arcface_model/arcface_checkpoint.tar'\n",
@@ -405,7 +417,7 @@
         "model.eval()\n",
         "\n",
         "app = Face_detect_crop(name='antelope', root='./insightface_func/models')\n",
-        "app.prepare(ctx_id= 0, det_thresh=0.6, det_size=(640,640))\n",
+        "app.prepare(ctx_id=0, det_thresh=0.6, det_size=(640, 640))\n",
         "\n",
         "with torch.no_grad():\n",
         "    pic_a = opt.pic_a_path\n",
@@ -566,12 +578,32 @@
         }
       ]
     },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "show_mp4(opt.video_path)  # original video"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "img_a_align_crop_pil  # swappable face"
+      ]
+    },
     {
       "cell_type": "code",
       "metadata": {
         "id": "Rty2GsyZZrI6"
       },
-      "source": [],
+      "source": [
+        "show_mp4(opt.output_path)  # processed video"
+      ],
       "execution_count": null,
       "outputs": []
     }