Siamese_Network_pytorch.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/somnathsingh31/Projects/blob/Temperory/Siamese_Network_pytorch.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install segmentation-models-pytorch\n",
        "!pip install -U git+https://github.com/albumentations-team/albumentations\n",
        "!pip install --upgrade opencv-contrib-python"
      ],
      "metadata": {
        "id": "ng5kt7rFN2VZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Download Full Dataset\n",
        "\n",
        "Market-1501 dataset :\n",
        "https://www.kaggle.com/pengcw1/market-1501"
      ],
      "metadata": {
        "id": "JEads6Mm4UEV"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "Tnclntis4TRX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b2b7879b-b881-4131-d560-7e19e96fb9ca"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'Person-Re-Id-Dataset'...\n",
            "remote: Enumerating objects: 12942, done.\u001b[K\n",
            "remote: Counting objects: 100% (12942/12942), done.\u001b[K\n",
            "remote: Compressing objects: 100% (12942/12942), done.\u001b[K\n",
            "remote: Total 12942 (delta 0), reused 12942 (delta 0), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (12942/12942), 27.68 MiB | 13.47 MiB/s, done.\n"
          ]
        }
      ],
      "source": [
        "!git clone https://github.com/parth1620/Person-Re-Id-Dataset"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "![siamese-network.png](data:image/png;base64,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)"
      ],
      "metadata": {
        "id": "d8e7znELOar-"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Imports"
      ],
      "metadata": {
        "id": "RaD5nA_jPV3H"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import sys\n",
        "sys.path.append('/content/Person-Re-Id-Dataset')"
      ],
      "metadata": {
        "id": "F8oFlfw3RXXx"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import torch\n",
        "import timm\n",
        "\n",
        "import torch.nn.functional as F\n",
        "from torch import nn\n",
        "from torch.utils.data import Dataset, DataLoader\n",
        "\n",
        "from skimage import io\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "from tqdm import tqdm"
      ],
      "metadata": {
        "id": "uJRSaF-H4tGs"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Configurations"
      ],
      "metadata": {
        "id": "umP_9Iz5PZNk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_dir = '/content/Person-Re-Id-Dataset/train/'\n",
        "csv_file = '/content/Person-Re-Id-Dataset/train.csv'\n",
        "\n",
        "batch_size = 32\n",
        "lr = 0.001       #learning rate\n",
        "epochs = 15\n",
        "device = 'cuda'"
      ],
      "metadata": {
        "id": "lerJzl1GPb6X"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv(csv_file)\n",
        "df.head(5)"
      ],
      "metadata": {
        "id": "8OpRLhSEPfyK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "771b65c2-5d93-4f14-f98e-93195a1a5c89"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                    Anchor                 Negative                 Positive\n",
              "0  1420_c5s3_052165_01.jpg  1334_c6s3_061492_05.jpg  1420_c3s3_051678_01.jpg\n",
              "1  1420_c3s3_061978_03.jpg  0234_c3s3_079494_02.jpg  1420_c6s3_085567_02.jpg\n",
              "2  1420_c5s3_062565_05.jpg  0475_c2s1_122816_08.jpg  1420_c3s3_051653_01.jpg\n",
              "3  1420_c6s3_085592_04.jpg  0662_c2s2_036662_05.jpg  1420_c1s6_013446_04.jpg\n",
              "4  0663_c5s3_085987_03.jpg  1463_c2s3_098102_02.jpg  0663_c3s3_085544_06.jpg"
            ],
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              "        document.querySelector('#df-187ae972-9efd-4641-9b8b-f1cdb97a4e68 button.colab-df-convert');\n",
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              "        const element = document.querySelector('#df-187ae972-9efd-4641-9b8b-f1cdb97a4e68');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-5fd11722-b5dd-4725-807f-08a2e3a174ad button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 4000,\n  \"fields\": [\n    {\n      \"column\": \"Anchor\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3285,\n        \"samples\": [\n          \"0206_c5s1_052801_04.jpg\",\n          \"0482_c3s1_139183_03.jpg\",\n          \"1080_c3s2_144344_01.jpg\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Negative\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3417,\n        \"samples\": [\n          \"0340_c6s1_080451_02.jpg\",\n          \"0741_c6s2_061343_01.jpg\",\n          \"0868_c3s2_108203_11.jpg\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Positive\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3219,\n        \"samples\": [\n          \"1152_c2s3_012407_01.jpg\",\n          \"0105_c2s1_017601_01.jpg\",\n          \"1286_c6s3_051367_01.jpg\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "row = df.iloc[4]     #selecting example 5\n",
        "\n",
        "img_A = io.imread(data_dir + row.Anchor)    #Anchor image in example 4\n",
        "img_N = io.imread(data_dir + row.Negative)    #Negative image in example 4\n",
        "img_P = io.imread(data_dir + row.Positive)    #Positive image in example 4"
      ],
      "metadata": {
        "id": "nlVfbL1fPkvr"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "f, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(10,5))\n",
        "\n",
        "ax1.set_title('Anchor image')\n",
        "ax1.imshow(img_A)\n",
        "\n",
        "ax2.set_title('Negative image')\n",
        "ax2.imshow(img_N)\n",
        "\n",
        "ax3.set_title('Positive image')\n",
        "ax3.imshow(img_P)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "pLA2K22SPmsP",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "outputId": "f0542033-2b5b-4c84-d1ed-6442d20e7761"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_df, valid_df = train_test_split(df, test_size =0.2, random_state=42)"
      ],
      "metadata": {
        "id": "pECVllpcPpud"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Create APN Dataset"
      ],
      "metadata": {
        "id": "B-WfDCYmPsTt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "class APN_Dataset(Dataset):\n",
        "\n",
        "  def __init__(self, df):\n",
        "    self.df = df\n",
        "\n",
        "  def __len__(self):\n",
        "    return len(self.df)\n",
        "\n",
        "  def __getitem__(self, idx):\n",
        "\n",
        "    row = self.df.iloc[idx]\n",
        "\n",
        "    img_A = io.imread(data_dir + row.Anchor)\n",
        "    img_N = io.imread(data_dir + row.Negative)\n",
        "    img_P = io.imread(data_dir + row.Positive)\n",
        "\n",
        "    img_A = torch.from_numpy(img_A).permute(2,0,1) / 255\n",
        "    img_P = torch.from_numpy(img_P).permute(2,0,1) / 255\n",
        "    img_N = torch.from_numpy(img_N).permute(2,0,1) / 255\n",
        "\n",
        "    return img_A, img_P, img_N"
      ],
      "metadata": {
        "id": "RcDARDmTPt88"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "trainset = APN_Dataset(train_df)\n",
        "validset = APN_Dataset(valid_df)\n",
        "\n",
        "print(f'size of train set {len(trainset)}')\n",
        "print(f'size of valid set {len(validset)}')"
      ],
      "metadata": {
        "id": "X-P7MZ0sPwnH",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "daa90729-d89f-4b49-cd47-09a487554798"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "size of train set 3200\n",
            "size of valid set 800\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "idx = 40\n",
        "A,P,N = trainset[idx]\n",
        "\n",
        "f, (ax1, ax2, ax3) = plt.subplots(1,3,figsize= (10,5))\n",
        "\n",
        "ax1.set_title('Anchor')\n",
        "ax1.imshow(A.numpy().transpose((1,2,0)), cmap = 'gray')\n",
        "\n",
        "ax2.set_title('Positive')\n",
        "ax2.imshow(P.numpy().transpose((1,2,0)), cmap = 'gray')\n",
        "\n",
        "ax3.set_title('Negative')\n",
        "ax3.imshow(N.numpy().transpose((1,2,0)), cmap = 'gray')\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "xeK5gZRqPxK7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 468
        },
        "outputId": "7f0491fb-fc8c-4eab-9341-acffef18fbcf"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "A.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5KcVQ9iHWz7j",
        "outputId": "fe7a6473-79e1-4d12-efa1-e1ac39b9163b"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "torch.Size([3, 128, 64])"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "A.numpy().transpose((1,2,0)).shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a1JgWTwPW60r",
        "outputId": "505c2758-7fef-42d5-e009-ff38f060046b"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(128, 64, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Load Dataset into Batches"
      ],
      "metadata": {
        "id": "_d1EgftpP5UX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "trainloader = DataLoader(trainset, batch_size=batch_size, shuffle=True)\n",
        "validloader = DataLoader(validset, batch_size=batch_size)"
      ],
      "metadata": {
        "id": "__Zd1aTQPz0L"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(f\"No. of batches in trainloader : {len(trainloader)}\")\n",
        "print(f\"No. of batches in validloader : {len(validloader)}\")"
      ],
      "metadata": {
        "id": "af2_B27tP9l0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "318895c7-0aed-4873-d71d-db660c38adf9"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "No. of batches in trainloader : 100\n",
            "No. of batches in validloader : 25\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for A,P,N in trainloader:\n",
        "  break;\n",
        "\n",
        "print(f\"One image batch shape : {A.shape}\")"
      ],
      "metadata": {
        "id": "u70vR5jfP_l4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "aab6554c-374c-443c-e55c-2ca69aff4a7b"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "One image batch shape : torch.Size([32, 3, 128, 64])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Create Model"
      ],
      "metadata": {
        "id": "-NTnh5yiQBlB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "class APN_Model(nn.Module):\n",
        "\n",
        "  def __init__(self, emb_size=512):\n",
        "    super(APN_Model, self).__init__()\n",
        "\n",
        "    self.efficientnet = timm.create_model('efficientnet_b0', pretrained=True)\n",
        "    self.efficientnet.classifier = nn.Linear(in_features=self.efficientnet.classifier.in_features, out_features=emb_size)\n",
        "\n",
        "\n",
        "  def forward(self, images):\n",
        "\n",
        "    embeddings = self.efficientnet(images)\n",
        "    return embeddings\n",
        "\n"
      ],
      "metadata": {
        "id": "H3Mah9XBQEnF"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model = APN_Model()\n",
        "model.to(device)"
      ],
      "metadata": {
        "id": "ePjHBQuPQFjZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "618c418c-8f01-403b-9774-34345c063448"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "APN_Model(\n",
              "  (efficientnet): EfficientNet(\n",
              "    (conv_stem): Conv2d(3, 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
              "    (bn1): BatchNormAct2d(\n",
              "      32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "      (drop): Identity()\n",
              "      (act): SiLU(inplace=True)\n",
              "    )\n",
              "    (blocks): Sequential(\n",
              "      (0): Sequential(\n",
              "        (0): DepthwiseSeparableConv(\n",
              "          (conv_dw): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=32, bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(32, 8, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(8, 32, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pw): Conv2d(32, 16, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "      )\n",
              "      (1): Sequential(\n",
              "        (0): InvertedResidual(\n",
              "          (conv_pw): Conv2d(16, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(96, 96, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), groups=96, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(96, 4, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(4, 96, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(96, 24, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            24, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "        (1): InvertedResidual(\n",
              "          (conv_pw): Conv2d(24, 144, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            144, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(144, 144, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=144, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            144, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(144, 6, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(6, 144, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(144, 24, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            24, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "      )\n",
              "      (2): Sequential(\n",
              "        (0): InvertedResidual(\n",
              "          (conv_pw): Conv2d(24, 144, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            144, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(144, 144, kernel_size=(5, 5), stride=(2, 2), padding=(2, 2), groups=144, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            144, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(144, 6, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(6, 144, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(144, 40, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            40, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "        (1): InvertedResidual(\n",
              "          (conv_pw): Conv2d(40, 240, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            240, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(240, 240, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=240, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            240, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(240, 10, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(10, 240, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(240, 40, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            40, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "      )\n",
              "      (3): Sequential(\n",
              "        (0): InvertedResidual(\n",
              "          (conv_pw): Conv2d(40, 240, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            240, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(240, 240, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), groups=240, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            240, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(240, 10, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(10, 240, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(240, 80, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            80, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "        (1): InvertedResidual(\n",
              "          (conv_pw): Conv2d(80, 480, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(480, 480, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=480, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(480, 20, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(20, 480, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(480, 80, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            80, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "        (2): InvertedResidual(\n",
              "          (conv_pw): Conv2d(80, 480, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(480, 480, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=480, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(480, 20, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(20, 480, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(480, 80, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            80, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "      )\n",
              "      (4): Sequential(\n",
              "        (0): InvertedResidual(\n",
              "          (conv_pw): Conv2d(80, 480, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(480, 480, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=480, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            480, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(480, 20, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(20, 480, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(480, 112, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            112, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "        (1): InvertedResidual(\n",
              "          (conv_pw): Conv2d(112, 672, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            672, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(672, 672, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=672, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            672, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(672, 28, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(28, 672, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(672, 112, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            112, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "        (2): InvertedResidual(\n",
              "          (conv_pw): Conv2d(112, 672, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            672, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(672, 672, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=672, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            672, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(672, 28, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(28, 672, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(672, 112, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            112, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "      )\n",
              "      (5): Sequential(\n",
              "        (0): InvertedResidual(\n",
              "          (conv_pw): Conv2d(112, 672, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            672, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(672, 672, kernel_size=(5, 5), stride=(2, 2), padding=(2, 2), groups=672, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            672, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(672, 28, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(28, 672, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(672, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "        (1): InvertedResidual(\n",
              "          (conv_pw): Conv2d(192, 1152, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            1152, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(1152, 1152, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1152, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            1152, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(1152, 48, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(48, 1152, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(1152, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "        (2): InvertedResidual(\n",
              "          (conv_pw): Conv2d(192, 1152, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            1152, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(1152, 1152, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1152, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            1152, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(1152, 48, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(48, 1152, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(1152, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "        (3): InvertedResidual(\n",
              "          (conv_pw): Conv2d(192, 1152, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            1152, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(1152, 1152, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), groups=1152, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            1152, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(1152, 48, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(48, 1152, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(1152, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "      )\n",
              "      (6): Sequential(\n",
              "        (0): InvertedResidual(\n",
              "          (conv_pw): Conv2d(192, 1152, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn1): BatchNormAct2d(\n",
              "            1152, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (conv_dw): Conv2d(1152, 1152, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1152, bias=False)\n",
              "          (bn2): BatchNormAct2d(\n",
              "            1152, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): SiLU(inplace=True)\n",
              "          )\n",
              "          (se): SqueezeExcite(\n",
              "            (conv_reduce): Conv2d(1152, 48, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (act1): SiLU(inplace=True)\n",
              "            (conv_expand): Conv2d(48, 1152, kernel_size=(1, 1), stride=(1, 1))\n",
              "            (gate): Sigmoid()\n",
              "          )\n",
              "          (conv_pwl): Conv2d(1152, 320, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "          (bn3): BatchNormAct2d(\n",
              "            320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "            (drop): Identity()\n",
              "            (act): Identity()\n",
              "          )\n",
              "          (drop_path): Identity()\n",
              "        )\n",
              "      )\n",
              "    )\n",
              "    (conv_head): Conv2d(320, 1280, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
              "    (bn2): BatchNormAct2d(\n",
              "      1280, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True\n",
              "      (drop): Identity()\n",
              "      (act): SiLU(inplace=True)\n",
              "    )\n",
              "    (global_pool): SelectAdaptivePool2d (pool_type=avg, flatten=Flatten(start_dim=1, end_dim=-1))\n",
              "    (classifier): Linear(in_features=1280, out_features=512, bias=True)\n",
              "  )\n",
              ")"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Create Train and Eval function"
      ],
      "metadata": {
        "id": "qCTbN0YqQIaQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def train_fn(model, dataloader, optimizer, criterion):\n",
        "\n",
        "  model.train()\n",
        "  total_loss = 0.0\n",
        "\n",
        "  for A,P,N in tqdm(dataloader):\n",
        "    A,P,N = A.to(device), P.to(device), N.to(device)\n",
        "\n",
        "    A_embeddings = model(A)\n",
        "    P_embeddings = model(P)\n",
        "    N_embeddings = model(N)\n",
        "\n",
        "    loss = criterion(A_embeddings, P_embeddings, N_embeddings)\n",
        "    optimizer.zero_grad()\n",
        "    loss.backward()\n",
        "    optimizer.step()\n",
        "\n",
        "    total_loss += loss.item()\n",
        "\n",
        "  return total_loss/len(dataloader)\n"
      ],
      "metadata": {
        "id": "95a5CYcYQH46"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def eval_fn(model, dataloader, criterion):\n",
        "\n",
        "  model.eval()\n",
        "  total_loss = 0.0\n",
        "\n",
        "  with torch.no_grad():\n",
        "    for A,P,N in tqdm(dataloader):\n",
        "      A,P,N = A.to(device), P.to(device), N.to(device)\n",
        "\n",
        "      A_embeddings = model(A)\n",
        "      P_embeddings = model(P)\n",
        "      N_embeddings = model(N)\n",
        "\n",
        "      loss = criterion(A_embeddings, P_embeddings, N_embeddings)\n",
        "\n",
        "      total_loss += loss.item()\n",
        "\n",
        "    return total_loss/len(dataloader)\n"
      ],
      "metadata": {
        "id": "GhG1oK9qQOdf"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "criterion = nn.TripletMarginLoss()\n",
        "optimizer = torch.optim.Adam(model.parameters(), lr = lr)"
      ],
      "metadata": {
        "id": "zdIUtk3dQReV"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Create Training Loop"
      ],
      "metadata": {
        "id": "FkjfpViLQTv9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "best_valid_loss = np.Inf\n",
        "\n",
        "for i in range(epochs):\n",
        "\n",
        "  train_loss = train_fn(model, trainloader, optimizer, criterion)\n",
        "  valid_loss = eval_fn(model, validloader, criterion)\n",
        "\n",
        "  if valid_loss<best_valid_loss:\n",
        "    torch.save(model.state_dict(), 'best_model.pt')\n",
        "    best_valid_loss = valid_loss\n",
        "    print('Saved_weights_success')\n",
        "\n",
        "  print(f'Epochs: {i+1}, training loss: {train_loss}, validation loss: {valid_loss}')"
      ],
      "metadata": {
        "id": "vJZuSPCQQWAt",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1b6282e1-4813-4be5-9a24-64ec8acfccb4"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:24<00:00,  4.13it/s]\n",
            "100%|██████████| 25/25 [00:04<00:00,  6.02it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saved_weights_success\n",
            "Epochs: 1, training loss: 0.5516876903176308, validation loss: 0.5317812311649323\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:22<00:00,  4.43it/s]\n",
            "100%|██████████| 25/25 [00:03<00:00,  6.88it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saved_weights_success\n",
            "Epochs: 2, training loss: 0.26606306701898574, validation loss: 0.30185092210769654\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:22<00:00,  4.40it/s]\n",
            "100%|██████████| 25/25 [00:03<00:00,  7.56it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saved_weights_success\n",
            "Epochs: 3, training loss: 0.1685124585032463, validation loss: 0.17068282425403594\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:22<00:00,  4.45it/s]\n",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epochs: 4, training loss: 0.09385800570249557, validation loss: 0.23183247089385986\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:22<00:00,  4.41it/s]\n",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epochs: 5, training loss: 0.08301855064928532, validation loss: 0.2710918176174164\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:22<00:00,  4.39it/s]\n",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epochs: 6, training loss: 0.07018200948834419, validation loss: 0.21578069448471068\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:23<00:00,  4.21it/s]\n",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saved_weights_success\n",
            "Epochs: 7, training loss: 0.07499162882566451, validation loss: 0.13443199902772904\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:22<00:00,  4.38it/s]\n",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epochs: 8, training loss: 0.07401489593088627, validation loss: 0.15541533946990968\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:22<00:00,  4.38it/s]\n",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epochs: 9, training loss: 0.04285682529211044, validation loss: 0.15297850131988525\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:22<00:00,  4.37it/s]\n",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epochs: 10, training loss: 0.057160858213901516, validation loss: 0.15332163363695145\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:22<00:00,  4.37it/s]\n",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epochs: 11, training loss: 0.04866060368716717, validation loss: 0.1559384736418724\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:22<00:00,  4.38it/s]\n",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epochs: 12, training loss: 0.025943200886249542, validation loss: 0.14229113191366197\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:22<00:00,  4.39it/s]\n",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epochs: 13, training loss: 0.03482782132923603, validation loss: 0.17012648582458495\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:22<00:00,  4.40it/s]\n",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epochs: 14, training loss: 0.04518987275660038, validation loss: 0.15541118055582046\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 100/100 [00:22<00:00,  4.48it/s]\n",
            "100%|██████████| 25/25 [00:04<00:00,  6.04it/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epochs: 15, training loss: 0.05774695716798305, validation loss: 0.219062984585762\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Get Anchor Embeddings"
      ],
      "metadata": {
        "id": "VQQbKYPRQbUG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def get_encoding_csv(model, anchor_img_names):\n",
        "  anchor_img_names_arr = np.array(anchor_img_names)\n",
        "  encodings=[]\n",
        "\n",
        "  model.eval()\n",
        "\n",
        "  with torch.no_grad():\n",
        "    for i in tqdm(anchor_img_names_arr):\n",
        "      A = io.imread(data_dir + i)\n",
        "      A = torch.from_numpy(A).permute(2,0,1) / 255\n",
        "      A = A.to(device)\n",
        "      A_encod = model(A.unsqueeze(0))  #(c, h, w) --> (batch, c, h, w)\n",
        "      encodings.append(A_encod.squeeze().cpu().detach().numpy())\n",
        "\n",
        "    encodings = np.array(encodings)\n",
        "    encodings = pd.DataFrame(encodings)\n",
        "    df_encod = pd.concat([anchor_img_names, encodings], axis = 1)\n",
        "\n",
        "  return df_encod\n",
        "\n"
      ],
      "metadata": {
        "id": "1OSKUvliQY9K"
      },
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.load_state_dict(torch.load('best_model.pt'))\n",
        "df_encod = get_encoding_csv(model, df['Anchor'])"
      ],
      "metadata": {
        "id": "rwwaSrVsQel0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_encod.to_csv('database.csv', index=False)\n",
        "df_encod.head()"
      ],
      "metadata": {
        "id": "jx8g5BuqQg_2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 255
        },
        "outputId": "46c83f41-2284-4026-ca36-e78260c9be6a"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                    Anchor         0         1         2         3         4  \\\n",
              "0  1420_c5s3_052165_01.jpg  0.222204  1.017838 -0.028982  0.262843 -0.925983   \n",
              "1  1420_c3s3_061978_03.jpg -0.192502  0.733488 -0.263567 -0.010000 -0.941879   \n",
              "2  1420_c5s3_062565_05.jpg  0.192758  1.070101  0.034034  0.076920 -1.022277   \n",
              "3  1420_c6s3_085592_04.jpg  0.651059  0.647719  0.173856 -0.074299 -0.725950   \n",
              "4  0663_c5s3_085987_03.jpg -0.925747 -0.893857  0.136262  0.910806  0.876688   \n",
              "\n",
              "          5         6         7         8  ...       502       503       504  \\\n",
              "0 -1.078484  0.339079 -0.578275  0.489616  ... -0.098472 -0.002318  0.037422   \n",
              "1 -0.931898  0.738613 -0.460869 -0.204183  ...  0.316220 -0.251310 -0.088696   \n",
              "2 -0.979101  0.355686 -0.403052  0.164210  ... -0.052594  0.145534  0.072171   \n",
              "3 -1.048395 -0.376032 -0.265730  0.805789  ... -0.088289  0.863032  0.346813   \n",
              "4  0.307464 -1.444915  0.497245  0.460524  ... -1.237588 -0.116029  0.181851   \n",
              "\n",
              "        505       506       507       508       509       510       511  \n",
              "0  0.413172  0.562238 -0.244824  0.534730  0.091330  0.070853 -0.248507  \n",
              "1  0.703292  0.715019 -0.251463  0.152632 -0.328917 -0.218638 -0.035166  \n",
              "2  0.509905  0.684078 -0.362885  0.260299 -0.098562 -0.005940 -0.122223  \n",
              "3  0.666844  0.446166 -0.453895  0.683162 -0.180144  0.890790 -0.025586  \n",
              "4 -1.201554 -0.579560 -0.082913  0.211925  0.099469 -0.038624 -0.111097  \n",
              "\n",
              "[5 rows x 513 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f4a2b3d3-3914-4758-be44-5f7436771656\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Anchor</th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "      <th>7</th>\n",
              "      <th>8</th>\n",
              "      <th>...</th>\n",
              "      <th>502</th>\n",
              "      <th>503</th>\n",
              "      <th>504</th>\n",
              "      <th>505</th>\n",
              "      <th>506</th>\n",
              "      <th>507</th>\n",
              "      <th>508</th>\n",
              "      <th>509</th>\n",
              "      <th>510</th>\n",
              "      <th>511</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1420_c5s3_052165_01.jpg</td>\n",
              "      <td>0.222204</td>\n",
              "      <td>1.017838</td>\n",
              "      <td>-0.028982</td>\n",
              "      <td>0.262843</td>\n",
              "      <td>-0.925983</td>\n",
              "      <td>-1.078484</td>\n",
              "      <td>0.339079</td>\n",
              "      <td>-0.578275</td>\n",
              "      <td>0.489616</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.098472</td>\n",
              "      <td>-0.002318</td>\n",
              "      <td>0.037422</td>\n",
              "      <td>0.413172</td>\n",
              "      <td>0.562238</td>\n",
              "      <td>-0.244824</td>\n",
              "      <td>0.534730</td>\n",
              "      <td>0.091330</td>\n",
              "      <td>0.070853</td>\n",
              "      <td>-0.248507</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1420_c3s3_061978_03.jpg</td>\n",
              "      <td>-0.192502</td>\n",
              "      <td>0.733488</td>\n",
              "      <td>-0.263567</td>\n",
              "      <td>-0.010000</td>\n",
              "      <td>-0.941879</td>\n",
              "      <td>-0.931898</td>\n",
              "      <td>0.738613</td>\n",
              "      <td>-0.460869</td>\n",
              "      <td>-0.204183</td>\n",
              "      <td>...</td>\n",
              "      <td>0.316220</td>\n",
              "      <td>-0.251310</td>\n",
              "      <td>-0.088696</td>\n",
              "      <td>0.703292</td>\n",
              "      <td>0.715019</td>\n",
              "      <td>-0.251463</td>\n",
              "      <td>0.152632</td>\n",
              "      <td>-0.328917</td>\n",
              "      <td>-0.218638</td>\n",
              "      <td>-0.035166</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1420_c5s3_062565_05.jpg</td>\n",
              "      <td>0.192758</td>\n",
              "      <td>1.070101</td>\n",
              "      <td>0.034034</td>\n",
              "      <td>0.076920</td>\n",
              "      <td>-1.022277</td>\n",
              "      <td>-0.979101</td>\n",
              "      <td>0.355686</td>\n",
              "      <td>-0.403052</td>\n",
              "      <td>0.164210</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.052594</td>\n",
              "      <td>0.145534</td>\n",
              "      <td>0.072171</td>\n",
              "      <td>0.509905</td>\n",
              "      <td>0.684078</td>\n",
              "      <td>-0.362885</td>\n",
              "      <td>0.260299</td>\n",
              "      <td>-0.098562</td>\n",
              "      <td>-0.005940</td>\n",
              "      <td>-0.122223</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1420_c6s3_085592_04.jpg</td>\n",
              "      <td>0.651059</td>\n",
              "      <td>0.647719</td>\n",
              "      <td>0.173856</td>\n",
              "      <td>-0.074299</td>\n",
              "      <td>-0.725950</td>\n",
              "      <td>-1.048395</td>\n",
              "      <td>-0.376032</td>\n",
              "      <td>-0.265730</td>\n",
              "      <td>0.805789</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.088289</td>\n",
              "      <td>0.863032</td>\n",
              "      <td>0.346813</td>\n",
              "      <td>0.666844</td>\n",
              "      <td>0.446166</td>\n",
              "      <td>-0.453895</td>\n",
              "      <td>0.683162</td>\n",
              "      <td>-0.180144</td>\n",
              "      <td>0.890790</td>\n",
              "      <td>-0.025586</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0663_c5s3_085987_03.jpg</td>\n",
              "      <td>-0.925747</td>\n",
              "      <td>-0.893857</td>\n",
              "      <td>0.136262</td>\n",
              "      <td>0.910806</td>\n",
              "      <td>0.876688</td>\n",
              "      <td>0.307464</td>\n",
              "      <td>-1.444915</td>\n",
              "      <td>0.497245</td>\n",
              "      <td>0.460524</td>\n",
              "      <td>...</td>\n",
              "      <td>-1.237588</td>\n",
              "      <td>-0.116029</td>\n",
              "      <td>0.181851</td>\n",
              "      <td>-1.201554</td>\n",
              "      <td>-0.579560</td>\n",
              "      <td>-0.082913</td>\n",
              "      <td>0.211925</td>\n",
              "      <td>0.099469</td>\n",
              "      <td>-0.038624</td>\n",
              "      <td>-0.111097</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 513 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f4a2b3d3-3914-4758-be44-5f7436771656')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-f4a2b3d3-3914-4758-be44-5f7436771656 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f4a2b3d3-3914-4758-be44-5f7436771656');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
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              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-8eedb92a-6f0d-440c-af01-4841dc03df2f\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8eedb92a-6f0d-440c-af01-4841dc03df2f')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-8eedb92a-6f0d-440c-af01-4841dc03df2f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_encod"
            }
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Inference"
      ],
      "metadata": {
        "id": "dVtNcaEkQjLN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def euclidean_dist(img_encod, anchor_encod_arr):\n",
        "  dist = np.sqrt(np.dot(img_encod-anchor_encod_arr, (img_encod-anchor_encod_arr).T))\n",
        "  return dist"
      ],
      "metadata": {
        "id": "ElGXlwz5Qm-V"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "idx = 15\n",
        "\n",
        "img_name = df_encod['Anchor'].iloc[idx]\n",
        "img_path = data_dir + img_name\n",
        "\n",
        "img = io.imread(img_path)\n",
        "img = torch.from_numpy(img).permute(2,0,1) / 255\n",
        "\n",
        "model.eval()\n",
        "with torch.no_grad():\n",
        "  img = img.to(device)\n",
        "  img_encod = model(img.unsqueeze(0))\n",
        "  img_encod = img_encod.detach().cpu().numpy()"
      ],
      "metadata": {
        "id": "ByS2zP5gQsAm"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "anchor_encod_arr = df_encod.iloc[:, 1:].to_numpy()\n",
        "anchor_img_names = df_encod['Anchor']"
      ],
      "metadata": {
        "id": "wF8PGtXzQvN7"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "distances = []\n",
        "\n",
        "for i in range(anchor_encod_arr.shape[0]):\n",
        "  dist = euclidean_dist(img_encod, anchor_encod_arr[i:1+1, :])\n",
        "  distances = np.append(distances, dist)"
      ],
      "metadata": {
        "id": "R8aI0QAIQxu-"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "closest_idx = np.argsort(distances)"
      ],
      "metadata": {
        "id": "cth8oJoRQ1x8"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from utils import plot_closest_imgs\n",
        "\n",
        "plot_closest_imgs(anchor_img_names, data_dir, img, img_path, closest_idx, distances, no_of_closest = 5);"
      ],
      "metadata": {
        "id": "UAy1dbmYQ2oQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 873
        },
        "outputId": "8ab7acb5-c763-4c96-a4e5-1ae92294a777"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x2000 with 7 Axes>"
            ],
            "image/png": 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    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "BtS1eTzUp2R4"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}