U_2_Net.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "U-2-Net.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyP+kQOL9ZdYsB5BR2KkX7KC",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/dvschultz/ai/blob/master/U_2_Net.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FklCreH9fgWE",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 187
        },
        "outputId": "9a7be2c2-7ab7-48bd-d3e7-fc204c4ddd1b"
      },
      "source": [
        "!git clone https://github.com/NathanUA/U-2-Net\n",
        "%cd U-2-Net\n",
        "%mkdir saved_models\n",
        "%mkdir saved_models/u2net\n",
        "!gdown --id 1ao1ovG1Qtx4b7EoskHXmi2E9rp5CHLcZ -O /content/U-2-Net/saved_models/u2net/u2net.pth"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'U-2-Net'...\n",
            "remote: Enumerating objects: 241, done.\u001b[K\n",
            "remote: Total 241 (delta 0), reused 0 (delta 0), pack-reused 241\u001b[K\n",
            "Receiving objects: 100% (241/241), 8.25 MiB | 8.72 MiB/s, done.\n",
            "Resolving deltas: 100% (99/99), done.\n",
            "/content/U-2-Net\n",
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1ao1ovG1Qtx4b7EoskHXmi2E9rp5CHLcZ\n",
            "To: /content/U-2-Net/saved_models/u2net/u2net.pth\n",
            "176MB [00:01, 99.5MB/s]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NU5vstDpAtLI",
        "colab_type": "text"
      },
      "source": [
        "This command just empties the results folders of their default images"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jx4-xhtZl2vG",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!rm /content/U-2-Net/test_data/u2net_results/*\n",
        "!rm /content/U-2-Net/test_data/test_images/*"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-BZz9j5IALOa",
        "colab_type": "text"
      },
      "source": [
        "Add your own images to the `U-2-Net/test_data/test_images/` folder. Then run the following command."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j-whHHfhg-Bc",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "7197bc92-13ec-4b48-ffef-3e8ba899a390"
      },
      "source": [
        "!python u2net_test.py"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['/content/U-2-Net/test_data/test_images/out296.png', '/content/U-2-Net/test_data/test_images/out246.png', '/content/U-2-Net/test_data/test_images/out241.png', '/content/U-2-Net/test_data/test_images/out21.png', '/content/U-2-Net/test_data/test_images/out72.png', '/content/U-2-Net/test_data/test_images/out44.png', '/content/U-2-Net/test_data/test_images/out181.png', '/content/U-2-Net/test_data/test_images/out176.png', '/content/U-2-Net/test_data/test_images/out49.png', '/content/U-2-Net/test_data/test_images/out101.png', '/content/U-2-Net/test_data/test_images/out104.png', '/content/U-2-Net/test_data/test_images/out331.png', '/content/U-2-Net/test_data/test_images/out256.png', '/content/U-2-Net/test_data/test_images/out267.png', '/content/U-2-Net/test_data/test_images/out244.png', '/content/U-2-Net/test_data/test_images/out69.png', '/content/U-2-Net/test_data/test_images/out156.png', '/content/U-2-Net/test_data/test_images/out272.png', 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            "...load U2NET---173.6 MB\n",
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            "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2796: UserWarning: nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.\n",
            "  warnings.warn(\"nn.functional.upsample is deprecated. Use nn.functional.interpolate instead.\")\n",
            "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2973: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.\n",
            "  \"See the documentation of nn.Upsample for details.\".format(mode))\n",
            "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:1569: UserWarning: nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.\n",
            "  warnings.warn(\"nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.\")\n",
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          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ylso-m6BmEVZ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}