From 5e0c4933a694869e80696154de4ea447cff2dcb2 Mon Sep 17 00:00:00 2001 From: Aswani Date: Sat, 24 Jul 2021 00:03:20 -0700 Subject: [PATCH] fixed bug that was making parser pick up unkown args from the environment making it crash. Eg in colab it was picking up jupyter runtime dir in root location. Now we don't need the dummy variable -f in colab --- SimSwap colab.ipynb | 1091 +++++++++++++++++++-------------------- options/base_options.py | 2 +- 2 files changed, 546 insertions(+), 547 deletions(-) diff --git a/SimSwap colab.ipynb b/SimSwap colab.ipynb index 8af741fc..e039dad2 100644 --- a/SimSwap colab.ipynb +++ b/SimSwap colab.ipynb @@ -1,579 +1,578 @@ { - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "SimSwap colab.ipynb", + "provenance": [], + "collapsed_sections": [] + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + }, + "accelerator": "GPU" + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "7_gtFoV8BuRx" + }, + "source": [ + "This is a simple example of SimSwap on processing video with multiple faces. You can change the codes for inference based on our other scripts for image or single face swapping.\n", + "\n", + "Code path: https://github.com/neuralchen/SimSwap\n", + "\n", + "Paper path: https://arxiv.org/pdf/2106.06340v1.pdf or https://dl.acm.org/doi/10.1145/3394171.3413630" + ] + }, + { + "cell_type": "code", + "metadata": { "colab": { - "name": "SimSwap colab.ipynb", - "provenance": [], - "collapsed_sections": [] + "base_uri": "https://localhost:8080/" }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" + "id": "0Y1RfpzsCAl9", + "outputId": "a39470a0-9689-409d-a0a4-e2afd5d3b5dd" + }, + "source": [ + "## make sure you are using a runtime with GPU\n", + "## you can check at Runtime/Change runtime type in the top bar.\n", + "!nvidia-smi" + ], + "execution_count": 1, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Mon Jun 21 02:13:20 2021 \n", + "+-----------------------------------------------------------------------------+\n", + "| NVIDIA-SMI 465.27 Driver Version: 460.32.03 CUDA Version: 11.2 |\n", + "|-------------------------------+----------------------+----------------------+\n", + "| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n", + "| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n", + "| | | MIG M. |\n", + "|===============================+======================+======================|\n", + "| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n", + "| N/A 45C P8 10W / 70W | 0MiB / 15109MiB | 0% Default |\n", + "| | | N/A |\n", + "+-------------------------------+----------------------+----------------------+\n", + " \n", + "+-----------------------------------------------------------------------------+\n", + "| Processes: |\n", + "| GPU GI CI PID Type Process name GPU Memory |\n", + "| ID ID Usage |\n", + "|=============================================================================|\n", + "| No running processes found |\n", + "+-----------------------------------------------------------------------------+\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0Qzzx2UpDkqw" + }, + "source": [ + "## Installation\n", + "\n", + "All file changes made by this notebook are temporary. \n", + "You can try to mount your own google drive to store files if you want.\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, - "language_info": { - "name": "python" + "id": "VA_4CeWZCHLP", + "outputId": "4b0f176f-87e7-4772-8b47-c2098d8f3bf6" + }, + "source": [ + "!git clone https://github.com/neuralchen/SimSwap\n", + "!cd SimSwap && git pull" + ], + "execution_count": 2, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Cloning into 'SimSwap'...\n", + "remote: Enumerating objects: 362, done.\u001B[K\n", + "remote: Counting objects: 100% (362/362), done.\u001B[K\n", + "remote: Compressing objects: 100% (281/281), done.\u001B[K\n", + "remote: Total 362 (delta 149), reused 272 (delta 67), pack-reused 0\u001B[K\n", + "Receiving objects: 100% (362/362), 101.31 MiB | 32.47 MiB/s, done.\n", + "Resolving deltas: 100% (149/149), done.\n", + "Already up to date.\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Y5K4au_UCkKn", + "colab": { + "base_uri": "https://localhost:8080/" }, - "accelerator": "GPU" + "outputId": "9691a7a4-192e-4ec2-c3c1-1f2c933d7b6a" + }, + "source": [ + "!pip install insightface==0.2.1 onnxruntime moviepy\n", + "!pip install googledrivedownloader\n", + "!pip install imageio==2.4.1" + ], + "execution_count": 3, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Collecting insightface==0.2.1\n", + " Downloading https://files.pythonhosted.org/packages/ee/1e/6395bbe0db665f187c8e49266cda54fcf661f182192370d409423e4943e4/insightface-0.2.1-py2.py3-none-any.whl\n", + "Collecting onnxruntime\n", + "\u001B[?25l Downloading https://files.pythonhosted.org/packages/f9/76/3d0f8bb2776961c7335693df06eccf8d099e48fa6fb552c7546867192603/onnxruntime-1.8.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.5MB)\n", + "\u001B[K |████████████████████████████████| 4.5MB 10.2MB/s \n", + "\u001B[?25hRequirement already satisfied: moviepy in /usr/local/lib/python3.7/dist-packages (0.2.3.5)\n", + "Collecting onnx\n", + "\u001B[?25l Downloading https://files.pythonhosted.org/packages/3f/9b/54c950d3256e27f970a83cd0504efb183a24312702deed0179453316dbd0/onnx-1.9.0-cp37-cp37m-manylinux2010_x86_64.whl (12.2MB)\n", + "\u001B[K |████████████████████████████████| 12.2MB 51.4MB/s \n", + "\u001B[?25hRequirement already satisfied: matplotlib in /usr/local/lib/python3.7/dist-packages (from insightface==0.2.1) (3.2.2)\n", + "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from insightface==0.2.1) (4.41.1)\n", + "Requirement already satisfied: Pillow in /usr/local/lib/python3.7/dist-packages (from insightface==0.2.1) (7.1.2)\n", + "Requirement already satisfied: scikit-image in /usr/local/lib/python3.7/dist-packages (from insightface==0.2.1) (0.16.2)\n", + "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from 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/usr/local/lib/python3.7/dist-packages (from scikit-learn->insightface==0.2.1) (1.0.1)\n", + "Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from protobuf->onnxruntime) (57.0.0)\n", + "Installing collected packages: onnx, insightface, onnxruntime\n", + "Successfully installed insightface-0.2.1 onnx-1.9.0 onnxruntime-1.8.0\n", + "Requirement already satisfied: googledrivedownloader in /usr/local/lib/python3.7/dist-packages (0.4)\n", + "Requirement already satisfied: imageio==2.4.1 in /usr/local/lib/python3.7/dist-packages (2.4.1)\n", + "Requirement already satisfied: pillow in /usr/local/lib/python3.7/dist-packages (from imageio==2.4.1) (7.1.2)\n", + "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from imageio==2.4.1) (1.19.5)\n" + ], + "name": "stdout" + } + ] }, - "cells": [ + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "gQ7ZoIbLFCye", + "outputId": "bb35e7e2-14b7-4f36-d62a-499ba041cf64" + }, + "source": [ + "import os\n", + "os.chdir(\"SimSwap\")\n", + "!ls" + ], + "execution_count": 4, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "7_gtFoV8BuRx" - }, - "source": [ - "This is a simple example of SimSwap on processing video with multiple faces. You can change the codes for inference based on our other scripts for image or single face swapping.\n", - "\n", - "Code path: https://github.com/neuralchen/SimSwap\n", - "\n", - "Paper path: https://arxiv.org/pdf/2106.06340v1.pdf or https://dl.acm.org/doi/10.1145/3394171.3413630" - ] + "output_type": "stream", + "text": [ + " crop_224\t models\t\t test_one_image.py\n", + " data\t\t options\t\t test_video_swapmulti.py\n", + " demo_file\t output\t\t test_video_swapsingle.py\n", + " doc\t\t README.md\t\t test_wholeimage_swapmulti.py\n", + " insightface_func 'SimSwap colab.ipynb' test_wholeimage_swapsingle.py\n", + " LICENSE\t simswaplogo\t\t util\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, + "id": "gLti1J0pEFjJ", + "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", + "# dest_path='./arcface_model/arcface_checkpoint.tar')\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", + "!unzip ./checkpoints.zip -d ./checkpoints\n", + "!wget -P ./parsing_model/checkpoint https://github.com/neuralchen/SimSwap/releases/download/1.0/79999_iter.pth" + ], + "execution_count": 5, + "outputs": [ { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "0Y1RfpzsCAl9", - "outputId": "a39470a0-9689-409d-a0a4-e2afd5d3b5dd" - }, - "source": [ - "## make sure you are using a runtime with GPU\n", - "## you can check at Runtime/Change runtime type in the top bar.\n", - "!nvidia-smi" - ], - "execution_count": 1, - "outputs": [ - { - "output_type": "stream", - "text": [ - "Mon Jun 21 02:13:20 2021 \n", - "+-----------------------------------------------------------------------------+\n", - "| NVIDIA-SMI 465.27 Driver Version: 460.32.03 CUDA Version: 11.2 |\n", - "|-------------------------------+----------------------+----------------------+\n", - "| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n", - "| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n", - "| | | MIG M. |\n", - "|===============================+======================+======================|\n", - "| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n", - "| N/A 45C P8 10W / 70W | 0MiB / 15109MiB | 0% Default |\n", - "| | | N/A |\n", - "+-------------------------------+----------------------+----------------------+\n", - " \n", - "+-----------------------------------------------------------------------------+\n", - "| Processes: |\n", - "| GPU GI CI PID Type Process name GPU Memory |\n", - "| ID ID Usage |\n", - "|=============================================================================|\n", - "| No running processes found |\n", - "+-----------------------------------------------------------------------------+\n" - ], - "name": "stdout" - } - ] + "output_type": "stream", + "text": [ + "Downloading 1TLNdIufzwesDbyr_nVTR7Zrx9oRHLM_N into ./arcface_model/arcface_checkpoint.tar... Done.\n", + "Downloading 1PXkRiBUYbu1xWpQyDEJvGKeqqUFthJcI into ./checkpoints.zip... Done.\n", + "Archive: ./checkpoints.zip\n", + " creating: ./checkpoints/people/\n", + " inflating: ./checkpoints/people/iter.txt \n", + " inflating: ./checkpoints/people/latest_net_D1.pth \n", + " inflating: ./checkpoints/people/latest_net_D2.pth \n", + " inflating: ./checkpoints/people/latest_net_G.pth \n", + " inflating: ./checkpoints/people/loss_log.txt \n", + " inflating: ./checkpoints/people/opt.txt \n", + " creating: ./checkpoints/people/web/\n", + " creating: ./checkpoints/people/web/images/\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, + "id": "aSRnK5V4HI-k", + "outputId": "e688746c-c33a-485c-808c-54a7370f0c53" + }, + "source": [ + "## You can upload filed manually\n", + "# from google.colab import drive\n", + "# drive.mount('/content/gdrive')\n", + "\n", + "### Now onedrive file can be downloaded in Colab directly!\n", + "### If the link blow is not permanent, you can just download it from the \n", + "### 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" + ], + "execution_count": 6, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "0Qzzx2UpDkqw" - }, - "source": [ - "## Installation\n", - "\n", - "All file changes made by this notebook are temporary. \n", - "You can try to mount your own google drive to store files if you want.\n" - ] + "output_type": "stream", + "text": [ + "--2021-06-21 02:14:17-- https://sh23tw.dm.files.1drv.com/y4mmGiIkNVigkSwOKDcV3nwMJulRGhbtHdkheehR5TArc52UjudUYNXAEvKCii2O5LAmzGCGK6IfleocxuDeoKxDZkNzDRSt4ZUlEt8GlSOpCXAFEkBwaZimtWGDRbpIGpb_pz9Nq5jATBQpezBS6G_UtspWTkgrXHHxhviV2nWy8APPx134zOZrUIbkSF6xnsqzs3uZ_SEX_m9Rey0ykpx9w\n", + "Resolving sh23tw.dm.files.1drv.com (sh23tw.dm.files.1drv.com)... 13.107.42.12\n", + "Connecting to sh23tw.dm.files.1drv.com (sh23tw.dm.files.1drv.com)|13.107.42.12|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 248024513 (237M) [application/zip]\n", + "Saving to: ‘antelope.zip’\n", + "\n", + "antelope.zip 100%[===================>] 236.53M 6.16MB/s in 31s \n", + "\n", + "2021-06-21 02:14:48 (7.66 MB/s) - ‘antelope.zip’ saved [248024513/248024513]\n", + "\n", + "Archive: ./antelope.zip\n", + " creating: ./insightface_func/models/antelope/\n", + " inflating: ./insightface_func/models/antelope/glintr100.onnx \n", + " inflating: ./insightface_func/models/antelope/scrfd_10g_bnkps.onnx \n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "BsGmIMxLVxyO" + }, + "source": [ + "## Inference" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, + "id": "PfSsND36EMvn", + "outputId": "f28c98fd-4c6d-40fa-e3c7-99b606c7492a" + }, + "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", + "from torchvision import transforms\n", + "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.add_watermark import watermark_image" + ], + "execution_count": 7, + "outputs": [ { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "VA_4CeWZCHLP", - "outputId": "4b0f176f-87e7-4772-8b47-c2098d8f3bf6" - }, - "source": [ - "!git clone https://github.com/neuralchen/SimSwap\n", - "!cd SimSwap && git pull" - ], - "execution_count": 2, - "outputs": [ - { - "output_type": "stream", - "text": [ - "Cloning into 'SimSwap'...\n", - "remote: Enumerating objects: 362, done.\u001b[K\n", - "remote: Counting objects: 100% (362/362), done.\u001b[K\n", - "remote: Compressing objects: 100% (281/281), done.\u001b[K\n", - "remote: Total 362 (delta 149), reused 272 (delta 67), pack-reused 0\u001b[K\n", - "Receiving objects: 100% (362/362), 101.31 MiB | 32.47 MiB/s, done.\n", - "Resolving deltas: 100% (149/149), done.\n", - "Already up to date.\n" - ], - "name": "stdout" - } - ] + "output_type": "stream", + "text": [ + "Imageio: 'ffmpeg-linux64-v3.3.1' was not found on your computer; downloading it now.\n", + "Try 1. Download from https://github.com/imageio/imageio-binaries/raw/master/ffmpeg/ffmpeg-linux64-v3.3.1 (43.8 MB)\n", + "Downloading: 8192/45929032 bytes (0.0%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b1286144/45929032 bytes (2.8%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b3653632/45929032 bytes (8.0%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b7479296/45929032 bytes (16.3%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b11526144/45929032 bytes (25.1%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b15171584/45929032 bytes (33.0%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b18997248/45929032 bytes (41.4%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b22724608/45929032 bytes (49.5%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b26673152/45929032 bytes (58.1%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b30728192/45929032 bytes (66.9%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b34725888/45929032 bytes (75.6%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b38879232/45929032 bytes (84.7%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b42680320/45929032 bytes (92.9%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b45929032/45929032 bytes (100.0%)\n", + " Done\n", + "File saved as /root/.imageio/ffmpeg/ffmpeg-linux64-v3.3.1.\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "rxSbZ2EDNDlf" + }, + "source": [ + "transformer = transforms.Compose([\n", + " transforms.ToTensor(),\n", + " #transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n", + " ])\n", + "\n", + "transformer_Arcface = transforms.Compose([\n", + " transforms.ToTensor(),\n", + " transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n", + " ])\n", + "\n", + "detransformer = transforms.Compose([\n", + " transforms.Normalize([0, 0, 0], [1/0.229, 1/0.224, 1/0.225]),\n", + " transforms.Normalize([-0.485, -0.456, -0.406], [1, 1, 1])\n", + " ])" + ], + "execution_count": 8, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, + "id": "wwJOwR9LNKRz", + "outputId": "bdc82f7b-21c4-403f-94d1-b92911698b4a" + }, + "source": [ + "opt = TestOptions()\n", + "opt.initialize()\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.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", + "opt.isTrain = False\n", + "opt.use_mask = True ## new feature up-to-date\n", + "\n", + "crop_size = 224\n", + "\n", + "torch.nn.Module.dump_patches = True\n", + "model = create_model(opt)\n", + "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", + "\n", + "with torch.no_grad():\n", + " pic_a = opt.pic_a_path\n", + " # img_a = Image.open(pic_a).convert('RGB')\n", + " img_a_whole = cv2.imread(pic_a)\n", + " img_a_align_crop, _ = app.get(img_a_whole,crop_size)\n", + " img_a_align_crop_pil = Image.fromarray(cv2.cvtColor(img_a_align_crop[0],cv2.COLOR_BGR2RGB)) \n", + " img_a = transformer_Arcface(img_a_align_crop_pil)\n", + " img_id = img_a.view(-1, img_a.shape[0], img_a.shape[1], img_a.shape[2])\n", + "\n", + " # convert numpy to tensor\n", + " img_id = img_id.cuda()\n", + "\n", + " #create latent id\n", + " img_id_downsample = F.interpolate(img_id, scale_factor=0.5)\n", + " latend_id = model.netArc(img_id_downsample)\n", + " latend_id = latend_id.detach().to('cpu')\n", + " latend_id = latend_id/np.linalg.norm(latend_id,axis=1,keepdims=True)\n", + " latend_id = latend_id.to('cuda')\n", + "\n", + " video_swap(opt.video_path, latend_id, model, app, opt.output_path, temp_results_dir=opt.temp_path, use_mask=opt.use_mask)" + ], + "execution_count": 9, + "outputs": [ { - "cell_type": "code", - "metadata": { - "id": "Y5K4au_UCkKn", - "colab": { - "base_uri": "https://localhost:8080/" - }, - "outputId": "9691a7a4-192e-4ec2-c3c1-1f2c933d7b6a" - }, - "source": [ - "!pip install insightface==0.2.1 onnxruntime moviepy\n", - "!pip install googledrivedownloader\n", - "!pip install imageio==2.4.1" - ], - "execution_count": 3, - "outputs": [ - { - "output_type": "stream", - "text": [ - "Collecting insightface==0.2.1\n", - " Downloading https://files.pythonhosted.org/packages/ee/1e/6395bbe0db665f187c8e49266cda54fcf661f182192370d409423e4943e4/insightface-0.2.1-py2.py3-none-any.whl\n", - "Collecting onnxruntime\n", - "\u001b[?25l Downloading https://files.pythonhosted.org/packages/f9/76/3d0f8bb2776961c7335693df06eccf8d099e48fa6fb552c7546867192603/onnxruntime-1.8.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.5MB)\n", - "\u001b[K |████████████████████████████████| 4.5MB 10.2MB/s \n", - "\u001b[?25hRequirement already satisfied: moviepy in /usr/local/lib/python3.7/dist-packages (0.2.3.5)\n", - 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"Requirement already satisfied: googledrivedownloader in /usr/local/lib/python3.7/dist-packages (0.4)\n", - "Requirement already satisfied: imageio==2.4.1 in /usr/local/lib/python3.7/dist-packages (2.4.1)\n", - "Requirement already satisfied: pillow in /usr/local/lib/python3.7/dist-packages (from imageio==2.4.1) (7.1.2)\n", - "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from imageio==2.4.1) (1.19.5)\n" - ], - "name": "stdout" - } - ] + "output_type": "stream", + "text": [ + "------------ Options -------------\n", + "Arc_path: models/BEST_checkpoint.tar\n", + "aspect_ratio: 1.0\n", + "batchSize: 8\n", + "checkpoints_dir: ./checkpoints\n", + "cluster_path: features_clustered_010.npy\n", + "data_type: 32\n", + "dataroot: ./datasets/cityscapes/\n", + "display_winsize: 512\n", + "engine: None\n", + "export_onnx: None\n", + "f: /root/.local/share/jupyter/runtime/kernel-6d955151-4911-464a-824d-f0806d8071f6.json\n", + "feat_num: 3\n", + "fineSize: 512\n", + "fp16: False\n", + "gpu_ids: [0]\n", + "how_many: 50\n", + "image_size: 224\n", + "input_nc: 3\n", + "instance_feat: False\n", + "isTrain: False\n", + "label_feat: False\n", + "label_nc: 0\n", + "latent_size: 512\n", + "loadSize: 1024\n", + "load_features: False\n", + "local_rank: 0\n", + "max_dataset_size: inf\n", + "model: pix2pixHD\n", + "nThreads: 2\n", + "n_blocks_global: 6\n", + "n_blocks_local: 3\n", + "n_clusters: 10\n", + "n_downsample_E: 4\n", + "n_downsample_global: 3\n", + "n_local_enhancers: 1\n", + "name: people\n", + "nef: 16\n", + "netG: global\n", + "ngf: 64\n", + "niter_fix_global: 0\n", + "no_flip: False\n", + "no_instance: False\n", + "norm: batch\n", + "norm_G: spectralspadesyncbatch3x3\n", + "ntest: inf\n", + "onnx: None\n", + "output_nc: 3\n", + "output_path: ./output/\n", + "phase: test\n", + "pic_a_path: ./crop_224/gdg.jpg\n", + "pic_b_path: ./crop_224/zrf.jpg\n", + "resize_or_crop: scale_width\n", + "results_dir: ./results/\n", + "semantic_nc: 3\n", + "serial_batches: False\n", + "temp_path: ./temp_results\n", + "tf_log: False\n", + "use_dropout: False\n", + "use_encoded_image: False\n", + "verbose: False\n", + "video_path: ./demo_file/multi_people_1080p.mp4\n", + "which_epoch: latest\n", + "-------------- End ----------------\n", + "input mean and std: 127.5 127.5\n", + "find model: ./insightface_func/models/antelope/glintr100.onnx recognition\n", + "find model: ./insightface_func/models/antelope/scrfd_10g_bnkps.onnx detection\n", + "set det-size: (640, 640)\n" + ], + "name": "stdout" }, { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "gQ7ZoIbLFCye", - "outputId": "bb35e7e2-14b7-4f36-d62a-499ba041cf64" - }, - "source": [ - "import os\n", - "os.chdir(\"SimSwap\")\n", - "!ls" - ], - "execution_count": 4, - "outputs": [ - { - "output_type": "stream", - "text": [ - " crop_224\t models\t\t test_one_image.py\n", - " data\t\t options\t\t test_video_swapmulti.py\n", - " demo_file\t output\t\t test_video_swapsingle.py\n", - " doc\t\t README.md\t\t test_wholeimage_swapmulti.py\n", - " insightface_func 'SimSwap colab.ipynb' test_wholeimage_swapsingle.py\n", - " LICENSE\t simswaplogo\t\t util\n" - ], - "name": "stdout" - } - ] + "output_type": "stream", + "text": [ + "\r 0%| | 0/594 [00:00] 236.53M 6.16MB/s in 31s \n", - "\n", - "2021-06-21 02:14:48 (7.66 MB/s) - ‘antelope.zip’ saved [248024513/248024513]\n", - "\n", - "Archive: ./antelope.zip\n", - " creating: ./insightface_func/models/antelope/\n", - " inflating: ./insightface_func/models/antelope/glintr100.onnx \n", - " inflating: ./insightface_func/models/antelope/scrfd_10g_bnkps.onnx \n" - ], - "name": "stdout" - } - ] + "output_type": "stream", + "text": [ + "100%|██████████| 594/594 [08:45<00:00, 1.13it/s]\n" + ], + "name": "stderr" }, { - "cell_type": "markdown", - "metadata": { - "id": "BsGmIMxLVxyO" - }, - "source": [ - "## Inference" - ] + "output_type": "stream", + "text": [ + "[MoviePy] >>>> Building video ./output/demo.mp4\n", + "[MoviePy] Writing audio in demoTEMP_MPY_wvf_snd.mp3\n" + ], + "name": "stdout" }, { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "PfSsND36EMvn", - "outputId": "f28c98fd-4c6d-40fa-e3c7-99b606c7492a" - }, - "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", - "from torchvision import transforms\n", - "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.add_watermark import watermark_image" - ], - "execution_count": 7, - "outputs": [ - { - "output_type": "stream", - "text": [ - "Imageio: 'ffmpeg-linux64-v3.3.1' was not found on your computer; downloading it now.\n", - "Try 1. Download from https://github.com/imageio/imageio-binaries/raw/master/ffmpeg/ffmpeg-linux64-v3.3.1 (43.8 MB)\n", - "Downloading: 8192/45929032 bytes (0.0%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b1286144/45929032 bytes (2.8%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b3653632/45929032 bytes (8.0%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b7479296/45929032 bytes (16.3%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b11526144/45929032 bytes (25.1%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b15171584/45929032 bytes (33.0%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b18997248/45929032 bytes (41.4%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b22724608/45929032 bytes (49.5%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b26673152/45929032 bytes (58.1%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b30728192/45929032 bytes (66.9%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b34725888/45929032 bytes (75.6%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b38879232/45929032 bytes (84.7%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b42680320/45929032 bytes (92.9%)\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b45929032/45929032 bytes (100.0%)\n", - " Done\n", - "File saved as /root/.imageio/ffmpeg/ffmpeg-linux64-v3.3.1.\n" - ], - "name": "stdout" - } - ] + "output_type": "stream", + "text": [ + "100%|██████████| 438/438 [00:00<00:00, 877.18it/s]\n" + ], + "name": "stderr" }, { - "cell_type": "code", - "metadata": { - "id": "rxSbZ2EDNDlf" - }, - "source": [ - "transformer = transforms.Compose([\n", - " transforms.ToTensor(),\n", - " #transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n", - " ])\n", - "\n", - "transformer_Arcface = transforms.Compose([\n", - " transforms.ToTensor(),\n", - " transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n", - " ])\n", - "\n", - "detransformer = transforms.Compose([\n", - " transforms.Normalize([0, 0, 0], [1/0.229, 1/0.224, 1/0.225]),\n", - " transforms.Normalize([-0.485, -0.456, -0.406], [1, 1, 1])\n", - " ])" - ], - "execution_count": 8, - "outputs": [] + "output_type": "stream", + "text": [ + "[MoviePy] Done.\n", + "[MoviePy] Writing video ./output/demo.mp4\n" + ], + "name": "stdout" }, { - "cell_type": "code", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "wwJOwR9LNKRz", - "outputId": "bdc82f7b-21c4-403f-94d1-b92911698b4a" - }, - "source": [ - "opt = TestOptions()\n", - "opt.initialize()\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.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", - "opt.isTrain = False\n", - "opt.use_mask = True ## new feature up-to-date\n", - "\n", - "crop_size = 224\n", - "\n", - "torch.nn.Module.dump_patches = True\n", - "model = create_model(opt)\n", - "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", - "\n", - "with torch.no_grad():\n", - " pic_a = opt.pic_a_path\n", - " # img_a = Image.open(pic_a).convert('RGB')\n", - " img_a_whole = cv2.imread(pic_a)\n", - " img_a_align_crop, _ = app.get(img_a_whole,crop_size)\n", - " img_a_align_crop_pil = Image.fromarray(cv2.cvtColor(img_a_align_crop[0],cv2.COLOR_BGR2RGB)) \n", - " img_a = transformer_Arcface(img_a_align_crop_pil)\n", - " img_id = img_a.view(-1, img_a.shape[0], img_a.shape[1], img_a.shape[2])\n", - "\n", - " # convert numpy to tensor\n", - " img_id = img_id.cuda()\n", - "\n", - " #create latent id\n", - " img_id_downsample = F.interpolate(img_id, scale_factor=0.5)\n", - " latend_id = model.netArc(img_id_downsample)\n", - " latend_id = latend_id.detach().to('cpu')\n", - " latend_id = latend_id/np.linalg.norm(latend_id,axis=1,keepdims=True)\n", - " latend_id = latend_id.to('cuda')\n", - "\n", - " video_swap(opt.video_path, latend_id, model, app, opt.output_path, temp_results_dir=opt.temp_path, use_mask=opt.use_mask)" - ], - "execution_count": 9, - "outputs": [ - { - "output_type": "stream", - "text": [ - "------------ Options -------------\n", - "Arc_path: models/BEST_checkpoint.tar\n", - "aspect_ratio: 1.0\n", - "batchSize: 8\n", - "checkpoints_dir: ./checkpoints\n", - "cluster_path: features_clustered_010.npy\n", - "data_type: 32\n", - "dataroot: ./datasets/cityscapes/\n", - "display_winsize: 512\n", - "engine: None\n", - "export_onnx: None\n", - "f: /root/.local/share/jupyter/runtime/kernel-6d955151-4911-464a-824d-f0806d8071f6.json\n", - "feat_num: 3\n", - "fineSize: 512\n", - "fp16: False\n", - "gpu_ids: [0]\n", - "how_many: 50\n", - "image_size: 224\n", - "input_nc: 3\n", - "instance_feat: False\n", - "isTrain: False\n", - "label_feat: False\n", - "label_nc: 0\n", - "latent_size: 512\n", - "loadSize: 1024\n", - "load_features: False\n", - "local_rank: 0\n", - "max_dataset_size: inf\n", - "model: pix2pixHD\n", - "nThreads: 2\n", - "n_blocks_global: 6\n", - "n_blocks_local: 3\n", - "n_clusters: 10\n", - "n_downsample_E: 4\n", - "n_downsample_global: 3\n", - "n_local_enhancers: 1\n", - "name: people\n", - "nef: 16\n", - "netG: global\n", - "ngf: 64\n", - "niter_fix_global: 0\n", - "no_flip: False\n", - "no_instance: False\n", - "norm: batch\n", - "norm_G: spectralspadesyncbatch3x3\n", - "ntest: inf\n", - "onnx: None\n", - "output_nc: 3\n", - "output_path: ./output/\n", - "phase: test\n", - "pic_a_path: ./crop_224/gdg.jpg\n", - "pic_b_path: ./crop_224/zrf.jpg\n", - "resize_or_crop: scale_width\n", - "results_dir: ./results/\n", - "semantic_nc: 3\n", - "serial_batches: False\n", - "temp_path: ./temp_results\n", - "tf_log: False\n", - "use_dropout: False\n", - "use_encoded_image: False\n", - "verbose: False\n", - "video_path: ./demo_file/multi_people_1080p.mp4\n", - "which_epoch: latest\n", - "-------------- End ----------------\n", - "input mean and std: 127.5 127.5\n", - "find model: ./insightface_func/models/antelope/glintr100.onnx recognition\n", - "find model: ./insightface_func/models/antelope/scrfd_10g_bnkps.onnx detection\n", - "set det-size: (640, 640)\n" - ], - "name": "stdout" - }, - { - "output_type": "stream", - "text": [ - "\r 0%| | 0/594 [00:00>>> Building video ./output/demo.mp4\n", - "[MoviePy] Writing audio in demoTEMP_MPY_wvf_snd.mp3\n" - ], - "name": "stdout" - }, - { - "output_type": "stream", - "text": [ - "100%|██████████| 438/438 [00:00<00:00, 877.18it/s]\n" - ], - "name": "stderr" - }, - { - "output_type": "stream", - "text": [ - "[MoviePy] Done.\n", - "[MoviePy] Writing video ./output/demo.mp4\n" - ], - "name": "stdout" - }, - { - "output_type": "stream", - "text": [ - "100%|██████████| 595/595 [00:53<00:00, 11.15it/s]\n" - ], - "name": "stderr" - }, - { - "output_type": "stream", - "text": [ - "[MoviePy] Done.\n", - "[MoviePy] >>>> Video ready: ./output/demo.mp4 \n", - "\n" - ], - "name": "stdout" - } - ] + "output_type": "stream", + "text": [ + "100%|██████████| 595/595 [00:53<00:00, 11.15it/s]\n" + ], + "name": "stderr" }, { - "cell_type": "code", - "metadata": { - "id": "Rty2GsyZZrI6" - }, - "source": [], - "execution_count": null, - "outputs": [] + "output_type": "stream", + "text": [ + "[MoviePy] Done.\n", + "[MoviePy] >>>> Video ready: ./output/demo.mp4 \n", + "\n" + ], + "name": "stdout" } - ] + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Rty2GsyZZrI6" + }, + "source": [], + "execution_count": null, + "outputs": [] + } + ] } \ No newline at end of file diff --git a/options/base_options.py b/options/base_options.py index 4ee0209d..ea9f867e 100644 --- a/options/base_options.py +++ b/options/base_options.py @@ -69,7 +69,7 @@ def initialize(self): def parse(self, save=True): if not self.initialized: self.initialize() - self.opt = self.parser.parse_args() + self.opt, unknown_arg = self.parser.parse_known_args() self.opt.isTrain = self.isTrain # train or test str_ids = self.opt.gpu_ids.split(',')