Barbershop_inference.ipynb

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  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uFcAwBaFnJon",
        "outputId": "074812b1-fbce-42a0-bab0-42cd4a269900"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Tue Oct 11 10:35:22 2022       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 460.32.03    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   70C    P8    11W /  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"
          ]
        }
      ],
      "source": [
        "!nvidia-smi"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xC3o205UnO_z",
        "outputId": "e1214097-d3d9-4f65-d715-e8ebe523a12b"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/drive/MyDrive"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QwYrY1pOnPc0",
        "outputId": "6dfee60b-6b3c-4761-a6f5-a655a75d7f90"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/drive/MyDrive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!git clone https://github.com/ZPdesu/Barbershop.git"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4nhCygC_nVbb",
        "outputId": "54205137-b8ff-43a6-d42d-43e7ff1c1971"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'Barbershop'...\n",
            "remote: Enumerating objects: 263, done.\u001b[K\n",
            "remote: Counting objects: 100% (46/46), done.\u001b[K\n",
            "remote: Compressing objects: 100% (19/19), done.\u001b[K\n",
            "remote: Total 263 (delta 29), reused 27 (delta 27), pack-reused 217\u001b[K\n",
            "Receiving objects: 100% (263/263), 85.81 MiB | 14.24 MiB/s, done.\n",
            "Resolving deltas: 100% (81/81), done.\n",
            "Checking out files: 100% (115/115), done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!wget https://github.com/ninja-build/ninja/releases/download/v1.8.2/ninja-linux.zip\n",
        "!sudo unzip ninja-linux.zip -d /usr/local/bin/\n",
        "!sudo update-alternatives --install /usr/bin/ninja ninja /usr/local/bin/ninja 1 --force "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FYeeTz3VokCi",
        "outputId": "bfe9cf28-f25d-4f9e-c462-cd1caea23f5e"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2022-10-11 10:41:08--  https://github.com/ninja-build/ninja/releases/download/v1.8.2/ninja-linux.zip\n",
            "Resolving github.com (github.com)... 20.205.243.166\n",
            "Connecting to github.com (github.com)|20.205.243.166|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/1335132/d2f252e2-9801-11e7-9fbf-bc7b4e4b5c83?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20221011%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20221011T104108Z&X-Amz-Expires=300&X-Amz-Signature=2d9c911fc35e2ea33ae70304e2c89d1d6c2b34dbd355377dacd10f787ce08f4e&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=1335132&response-content-disposition=attachment%3B%20filename%3Dninja-linux.zip&response-content-type=application%2Foctet-stream [following]\n",
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            "Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.110.133, 185.199.111.133, 185.199.108.133, ...\n",
            "Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.110.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 77854 (76K) [application/octet-stream]\n",
            "Saving to: ‘ninja-linux.zip’\n",
            "\n",
            "ninja-linux.zip     100%[===================>]  76.03K  --.-KB/s    in 0.002s  \n",
            "\n",
            "2022-10-11 10:41:09 (35.6 MB/s) - ‘ninja-linux.zip’ saved [77854/77854]\n",
            "\n",
            "Archive:  ninja-linux.zip\n",
            "  inflating: /usr/local/bin/ninja    \n",
            "update-alternatives: using /usr/local/bin/ninja to provide /usr/bin/ninja (ninja) in auto mode\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%cd /content/drive/MyDrive/Barbershop"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kFb9wXAenWX4",
        "outputId": "075be3b6-3469-4e45-8c0f-55976428bb31"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/drive/MyDrive/Barbershop\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Preprocess your own images. Please put the raw images in the unprocessed folder."
      ],
      "metadata": {
        "id": "Bvmrr3tznhY1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!python align_face.py"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "W8_gLoAIncJP",
        "outputId": "3e27b9ba-aa41-4dc6-8808-15845dd59fc3"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading Shape Predictor\n",
            "Downloading https://drive.google.com/uc?id=1huhv8PYpNNKbGCLOaYUjOgR1pY5pmbJx ... done\n",
            "90.jpg: Number of faces detected: 1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Produce realistic results:"
      ],
      "metadata": {
        "id": "cWO1GAoSnkrL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!python main.py --im_path1 90.png --im_path2 15.png --im_path3 117.png --sign realistic --smooth 5"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "at6dUqY-nk8S",
        "outputId": "22155d2c-a25f-4636-951f-f049339de18f"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading StyleGAN2 checkpoint: pretrained_models/ffhq.pt\n",
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1AT6bNR2ppK8f2ETL_evT27f3R_oyWNHS\n",
            "To: /content/drive/MyDrive/Barbershop/pretrained_models/ffhq.pt\n",
            "100% 133M/133M [00:03<00:00, 40.9MB/s]\n",
            "Loading StyleGAN2 from checkpoint: pretrained_models/ffhq.pt\n",
            "Setting up Perceptual loss...\n",
            "/usr/local/lib/python3.7/dist-packages/torchvision/models/_utils.py:209: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and will be removed in 0.15, please use 'weights' instead.\n",
            "  f\"The parameter '{pretrained_param}' is deprecated since 0.13 and will be removed in 0.15, \"\n",
            "/usr/local/lib/python3.7/dist-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and will be removed in 0.15. The current behavior is equivalent to passing `weights=VGG16_Weights.IMAGENET1K_V1`. You can also use `weights=VGG16_Weights.DEFAULT` to get the most up-to-date weights.\n",
            "  warnings.warn(msg)\n",
            "Downloading: \"https://download.pytorch.org/models/vgg16-397923af.pth\" to /root/.cache/torch/hub/checkpoints/vgg16-397923af.pth\n",
            "100% 528M/528M [00:02<00:00, 264MB/s]\n",
            "Loading model from: /content/drive/MyDrive/Barbershop/losses/lpips/weights/v0.1/vgg.pth\n",
            "...[net-lin [vgg]] initialized\n",
            "...Done\n",
            "Number of images: 3\n",
            "Images:   0% 0/3 [00:00<?, ?it/s]\n",
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            "Images: 100% 3/3 [02:24<00:00, 48.12s/it]\n",
            "Loading StyleGAN2 from checkpoint: pretrained_models/ffhq.pt\n",
            "Downloading: \"https://download.pytorch.org/models/resnet18-5c106cde.pth\" to /root/.cache/torch/hub/checkpoints/resnet18-5c106cde.pth\n",
            "100% 44.7M/44.7M [00:00<00:00, 299MB/s]\n",
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1lIKvQaFKHT5zC7uS4p17O9ZpfwmwlS62\n",
            "To: /content/drive/MyDrive/Barbershop/pretrained_models/seg.pth\n",
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            "/content/drive/MyDrive/Barbershop/models/Alignment.py:97: UserWarning: where received a uint8 condition tensor. This behavior is deprecated and will be removed in a future version of PyTorch. Use a boolean condition instead. (Triggered internally at  ../aten/src/ATen/native/TensorCompare.cpp:402.)\n",
            "  new_target_final = torch.where(OB_region, torch.from_numpy(new_target_inpainted), new_target)\n",
            "Loading StyleGAN2 from checkpoint: pretrained_models/ffhq.pt\n",
            "Setting up Perceptual loss...\n",
            "Loading model from: /content/drive/MyDrive/Barbershop/losses/masked_lpips/weights/v0.1/vgg.pth\n",
            "...[net-lin [vgg]] initialized\n",
            "...Done\n",
            "Setting up Perceptual loss...\n",
            "Loading model from: /content/drive/MyDrive/Barbershop/losses/masked_lpips/weights/v0.1/vgg.pth\n",
            "...[net-lin [vgg]] initialized\n",
            "...Done\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "Zj6snUefoJmY"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}