resnet50_test.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "import numpy as np\n",
    "from numpy.linalg import norm\n",
    "import matplotlib.pyplot as plt\n",
    "import tensorflow as tf\n",
    "from tensorflow.keras.preprocessing import image\n",
    "from tensorflow.keras.layers import GlobalMaxPooling2D\n",
    "from tensorflow.keras.applications.resnet50 import ResNet50, preprocess_input\n",
    "from sklearn.neighbors import NearestNeighbors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(44441, 2048)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_list = np.array(pickle.load(open('resnet50_features.pkl', 'rb')))\n",
    "feature_list.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(44441,)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_paths = np.array(pickle.load(open('resnet50_images.pkl', 'rb')))\n",
    "image_paths.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_1\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_1\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ resnet50 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Functional</span>)           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">7</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">7</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)     │    <span style=\"color: #00af00; text-decoration-color: #00af00\">23,587,712</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ global_max_pooling2d_1          │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)           │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">GlobalMaxPooling2D</span>)            │                        │               │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ resnet50 (\u001b[38;5;33mFunctional\u001b[0m)           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m7\u001b[0m, \u001b[38;5;34m2048\u001b[0m)     │    \u001b[38;5;34m23,587,712\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ global_max_pooling2d_1          │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m2048\u001b[0m)           │             \u001b[38;5;34m0\u001b[0m │\n",
       "│ (\u001b[38;5;33mGlobalMaxPooling2D\u001b[0m)            │                        │               │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">23,587,712</span> (89.98 MB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m23,587,712\u001b[0m (89.98 MB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">23,587,712</span> (89.98 MB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m23,587,712\u001b[0m (89.98 MB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# load the pre-trained ResNet50 model\n",
    "model = ResNet50(include_top=False, weights=\"imagenet\", input_shape=(224, 224, 3))\n",
    "model.trainable = False\n",
    "# model.summary()\n",
    "\n",
    "model = tf.keras.Sequential([model, GlobalMaxPooling2D()])\n",
    "model.build(input_shape=(None, 224, 224, 3))\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load resnet50 model\n",
    "# model = tf.keras.models.load_model(\"resnet50.keras\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>NearestNeighbors(algorithm=&#x27;kd_tree&#x27;, metric=&#x27;euclidean&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;NearestNeighbors<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.neighbors.NearestNeighbors.html\">?<span>Documentation for NearestNeighbors</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>NearestNeighbors(algorithm=&#x27;kd_tree&#x27;, metric=&#x27;euclidean&#x27;)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "NearestNeighbors(algorithm='kd_tree', metric='euclidean')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neighbors = NearestNeighbors(n_neighbors=5, algorithm=\"kd_tree\", metric=\"euclidean\")\n",
    "neighbors.fit(feature_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_path = \"./sample/image5.jpg\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 2s/step\n"
     ]
    }
   ],
   "source": [
    "img = image.load_img(image_path, target_size=(224, 224))\n",
    "img_array = image.img_to_array(img)\n",
    "expanded_img_array = np.expand_dims(img_array, axis=0)\n",
    "preprocessed_img = preprocess_input(expanded_img_array)\n",
    "res = model.predict(preprocessed_img).flatten()\n",
    "normalized_res = res / norm(res)  # L2 Normalization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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      "image/png": 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",
      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=224x224>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2048,)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "normalized_res.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "distances, indexes = neighbors.kneighbors([normalized_res])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.56242427 0.56304721 0.56671622 0.57186073 0.5731036 ]]\n"
     ]
    }
   ],
   "source": [
    "print(distances)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[17480 44064 14910 41463 28196]]\n"
     ]
    }
   ],
   "source": [
    "print(indexes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[30618, 9552, 27443, 6538, 44222]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output_images = image_paths[indexes].flatten()\n",
    "\n",
    "# convert ndarray to normal array\n",
    "output_images = output_images.tolist()\n",
    "\n",
    "# extract the numeral part of the path\n",
    "output_images = [int(x.split(\"\\\\\")[-1].split(\".\")[0]) for x in output_images]\n",
    "\n",
    "output_images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# modify the path to the image\n",
    "output_images = [f\"./data/images/{x}.jpg\" for x in output_images]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['./data/images/30618.jpg', './data/images/9552.jpg',\n",
       "       './data/images/27443.jpg', './data/images/6538.jpg',\n",
       "       './data/images/44222.jpg'], dtype='<U23')"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert to numpy array\n",
    "output_images = np.array(output_images)\n",
    "\n",
    "output_images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x2000 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot all the images in output_images in a grid\n",
    "plt.figure(figsize=(20, 20))\n",
    "for i in range(len(output_images)):\n",
    "    plt.subplot(1, 5, i+1)\n",
    "    img = image.load_img(output_images[i], target_size=(224, 224))\n",
    "    plt.imshow(img)\n",
    "    plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}