notebooks/result_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torchvision.ops import box_iou\n",
    "import os\n",
    "import pandas as pd\n",
    "import json\n",
    "import torch\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "BASE_DIR = \"/home/safal/raavan/smartphone_microscopy/AI_assisted_microscopy_system\"\n",
    "sample_types = [\n",
    "    \"smartphone_sample\",\n",
    "    \"smartphone_reference\",\n",
    "    \"brightfield_sample\",\n",
    "    \"brightfield_reference\",\n",
    "]\n",
    "model_type = \"retinanet\"\n",
    "sample_type = sample_types[2]\n",
    "fold = 1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_annotation_file = os.path.join(\n",
    "    BASE_DIR, \"outputs\", sample_type, model_type, f\"fold_{fold}\", \"results.bbox.json\"\n",
    ")\n",
    "gt_annotation_file = os.path.join(\n",
    "    BASE_DIR,\n",
    "    \"cysts_dataset_all\",\n",
    "    sample_type,\n",
    "    f\"fold_{fold}\",\n",
    "    f\"{sample_type}_coco_annos_val.json\",\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_precision_recall_f1(\n",
    "    pred_annotations_file,\n",
    "    gt_annotations_file,\n",
    "    conf_threshold: float = 0.3,\n",
    "    iou_threshold: float = 0.5,\n",
    "):\n",
    "    \"\"\"\n",
    "    This function calculates the precision, recall and f1 score for each class\n",
    "    in the given ground truth and predicted annotations.\n",
    "\n",
    "    Arguments:\n",
    "        pred_annotations_file: path to the predicted annotations file\n",
    "        gt_annotations_file: path to the ground truth annotations file\n",
    "        conf_threshold: confidence threshold to filter out predictions\n",
    "\n",
    "    Returns:\n",
    "        metrics_df: dataframe containing the precision, recall and f1 score for each class\n",
    "\n",
    "    \"\"\"\n",
    "    # Precision x Recall is obtained individually by each class\n",
    "    # Loop through each class and calculate the precision and recall\n",
    "\n",
    "    # Precision = TP / (TP + FP)\n",
    "    # Recall = TP / (TP + FN)\n",
    "    with open(gt_annotations_file) as f:\n",
    "        gt_annotations = json.load(f)\n",
    "\n",
    "    with open(pred_annotations_file) as f:\n",
    "        pred_annotations = json.load(f)\n",
    "\n",
    "    gt_annotations_df = pd.DataFrame(gt_annotations[\"annotations\"])\n",
    "    pred_annotations_df = pd.DataFrame(pred_annotations)\n",
    "\n",
    "    # change bbox width and height to x2, y2\n",
    "    pred_annotations_df[\"bbox\"] = pred_annotations_df[\"bbox\"].apply(\n",
    "        lambda x: [x[0], x[1], x[0] + x[2], x[1] + x[3]]\n",
    "    )\n",
    "    gt_annotations_df[\"bbox\"] = gt_annotations_df[\"bbox\"].apply(\n",
    "        lambda x: [x[0], x[1], x[0] + x[2], x[1] + x[3]]\n",
    "    )\n",
    "\n",
    "    categories = sorted(gt_annotations_df.category_id.unique())\n",
    "\n",
    "    # dataframe to store the precision, recall and f1 score for each class\n",
    "    metrics_df = pd.DataFrame(\n",
    "        columns=[\"category\", \"precision\", \"recall\", \"f1_score\", \"TP\", \"FP\"]\n",
    "    )\n",
    "\n",
    "    for category in categories:\n",
    "        # get the ground truth annotations for the current class\n",
    "        gt_annotations_df_class = gt_annotations_df[\n",
    "            gt_annotations_df.category_id == category\n",
    "        ]\n",
    "        # get the predicted annotations for the current class\n",
    "        pred_annotations_df_class = pred_annotations_df[\n",
    "            pred_annotations_df.category_id == category\n",
    "        ]\n",
    "\n",
    "        # sort the predicted annotations by score\n",
    "        pred_annotations_df_class = pred_annotations_df_class.sort_values(\n",
    "            by=\"score\", ascending=False\n",
    "        )\n",
    "\n",
    "        # filter predictions with score > conf_threshold\n",
    "        pred_annotations_df_class = pred_annotations_df_class[\n",
    "            pred_annotations_df_class.score > conf_threshold\n",
    "        ]\n",
    "\n",
    "        true_positives_class = 0\n",
    "        false_positives_class = 0\n",
    "\n",
    "        # get image ids for the current class from both ground truth and predicted annotations\n",
    "        image_ids = pred_annotations_df_class[\"image_id\"].unique()\n",
    "\n",
    "        for image in image_ids:\n",
    "            # get the ground truth annotations for the current image\n",
    "            gt_annotations_df_image = gt_annotations_df_class[\n",
    "                gt_annotations_df_class.image_id == image\n",
    "            ]\n",
    "            # get the predicted annotations for the current image\n",
    "            pred_annotations_df_image = pred_annotations_df_class[\n",
    "                pred_annotations_df_class.image_id == image\n",
    "            ]\n",
    "\n",
    "            # get the ground truth bounding boxes\n",
    "            gt_bboxes = torch.tensor(gt_annotations_df_image.bbox.to_list())\n",
    "\n",
    "            gt_matched = np.zeros(len(gt_bboxes))\n",
    "\n",
    "            # get the predicted bounding boxes\n",
    "            pred_bboxes = torch.tensor(pred_annotations_df_image.bbox.to_list())\n",
    "        \n",
    "\n",
    "            if len(gt_bboxes) == 0:\n",
    "                false_positives_class += len(pred_bboxes)\n",
    "                continue\n",
    "\n",
    "            # get the intersection over union for each predicted bounding box\n",
    "            ious = box_iou(pred_bboxes, gt_bboxes)\n",
    "\n",
    "            # get the maximum iou for each ground truth bounding box\n",
    "            max_ious, max_idxs = torch.max(ious, dim=1)\n",
    "\n",
    "            for iou_pred, gt_idx in zip(max_ious, max_idxs):\n",
    "                if (iou_pred > iou_threshold).item() and (gt_matched[gt_idx] == 0):\n",
    "                        true_positives_class += 1\n",
    "                        gt_matched[gt_idx] = 1\n",
    "                else:\n",
    "                    false_positives_class += 1\n",
    "\n",
    "\n",
    "        # calculate the precision and recall\n",
    "        eps = torch.finfo(torch.float32).eps\n",
    "        precision = true_positives_class / max(\n",
    "            true_positives_class + false_positives_class, eps\n",
    "        )\n",
    "        recall = true_positives_class / max(gt_annotations_df_class.shape[0], eps)\n",
    "\n",
    "        category_name = gt_annotations[\"categories\"][category][\"name\"]\n",
    "        f1_score = 2 * (precision * recall) / max(precision + recall, eps)\n",
    "\n",
    "        category_metrics_df = pd.DataFrame(\n",
    "            {\n",
    "                \"category\": category_name,\n",
    "                \"precision\": precision,\n",
    "                \"recall\": recall,\n",
    "                \"f1_score\": f1_score,\n",
    "                \"TP\": true_positives_class,\n",
    "                \"FP\": false_positives_class,\n",
    "            },\n",
    "            index=[0],\n",
    "        )\n",
    "\n",
    "        # concatenate the metrics for the current class to the metrics dataframe\n",
    "        metrics_df = pd.concat([metrics_df, category_metrics_df], axis=0)\n",
    "\n",
    "    return metrics_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "confidence_thresholds = np.arange(0.1, 1.0, 0.1)\n",
    "iou_thresholds = np.arange(0.1, 1.0, 0.1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iou_thresholds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calculating metrics for conf_threshold: 0.1 and iou_threshold: 0.1\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.1 and iou_threshold: 0.2\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.1 and iou_threshold: 0.30000000000000004\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.1 and iou_threshold: 0.4\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.1 and iou_threshold: 0.5\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.1 and iou_threshold: 0.6\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.1 and iou_threshold: 0.7000000000000001\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.1 and iou_threshold: 0.8\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.1 and iou_threshold: 0.9\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.2 and iou_threshold: 0.1\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.2 and iou_threshold: 0.2\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.2 and iou_threshold: 0.30000000000000004\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.2 and iou_threshold: 0.4\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.2 and iou_threshold: 0.5\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.2 and iou_threshold: 0.6\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.2 and iou_threshold: 0.7000000000000001\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.2 and iou_threshold: 0.8\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.2 and iou_threshold: 0.9\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.30000000000000004 and iou_threshold: 0.1\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.30000000000000004 and iou_threshold: 0.2\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.30000000000000004 and iou_threshold: 0.30000000000000004\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.30000000000000004 and iou_threshold: 0.4\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.30000000000000004 and iou_threshold: 0.5\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.30000000000000004 and iou_threshold: 0.6\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.30000000000000004 and iou_threshold: 0.7000000000000001\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.30000000000000004 and iou_threshold: 0.8\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.30000000000000004 and iou_threshold: 0.9\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.4 and iou_threshold: 0.1\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.4 and iou_threshold: 0.2\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.4 and iou_threshold: 0.30000000000000004\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.4 and iou_threshold: 0.4\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.4 and iou_threshold: 0.5\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.4 and iou_threshold: 0.6\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.4 and iou_threshold: 0.7000000000000001\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.4 and iou_threshold: 0.8\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.4 and iou_threshold: 0.9\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.5 and iou_threshold: 0.1\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.5 and iou_threshold: 0.2\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.5 and iou_threshold: 0.30000000000000004\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.5 and iou_threshold: 0.4\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.5 and iou_threshold: 0.5\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.5 and iou_threshold: 0.6\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.5 and iou_threshold: 0.7000000000000001\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.5 and iou_threshold: 0.8\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.5 and iou_threshold: 0.9\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.6 and iou_threshold: 0.1\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.6 and iou_threshold: 0.2\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.6 and iou_threshold: 0.30000000000000004\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.6 and iou_threshold: 0.4\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.6 and iou_threshold: 0.5\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.6 and iou_threshold: 0.6\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.6 and iou_threshold: 0.7000000000000001\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.6 and iou_threshold: 0.8\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.6 and iou_threshold: 0.9\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.7000000000000001 and iou_threshold: 0.1\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.7000000000000001 and iou_threshold: 0.2\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.7000000000000001 and iou_threshold: 0.30000000000000004\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.7000000000000001 and iou_threshold: 0.4\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.7000000000000001 and iou_threshold: 0.5\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.7000000000000001 and iou_threshold: 0.6\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.7000000000000001 and iou_threshold: 0.7000000000000001\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.7000000000000001 and iou_threshold: 0.8\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.7000000000000001 and iou_threshold: 0.9\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.8 and iou_threshold: 0.1\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.8 and iou_threshold: 0.2\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.8 and iou_threshold: 0.30000000000000004\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.8 and iou_threshold: 0.4\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.8 and iou_threshold: 0.5\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.8 and iou_threshold: 0.6\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.8 and iou_threshold: 0.7000000000000001\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.8 and iou_threshold: 0.8\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.8 and iou_threshold: 0.9\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.9 and iou_threshold: 0.1\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.9 and iou_threshold: 0.2\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.9 and iou_threshold: 0.30000000000000004\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.9 and iou_threshold: 0.4\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.9 and iou_threshold: 0.5\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.9 and iou_threshold: 0.6\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.9 and iou_threshold: 0.7000000000000001\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.9 and iou_threshold: 0.8\n",
      "Done\n",
      "Calculating metrics for conf_threshold: 0.9 and iou_threshold: 0.9\n",
      "Done\n"
     ]
    }
   ],
   "source": [
    "\n",
    "metrics_df = pd.DataFrame(\n",
    "    columns=[\"conf_threshold\", \"iou_threshold\", \"precision\", \"recall\", \"f1_score\"]\n",
    ")\n",
    "\n",
    "for conf_threshold in confidence_thresholds:\n",
    "    for iou_threshold in iou_thresholds:\n",
    "\n",
    "        print(\n",
    "            f\"Calculating metrics for conf_threshold: {conf_threshold} and iou_threshold: {iou_threshold}\"\n",
    "        )\n",
    "        metrics = calculate_precision_recall_f1(\n",
    "            pred_annotation_file, gt_annotation_file, conf_threshold=conf_threshold, iou_threshold=iou_threshold\n",
    "        )\n",
    "        metrics[\"conf_threshold\"] = conf_threshold.round(2)\n",
    "        metrics[\"iou_threshold\"] = iou_threshold.round(2)\n",
    "\n",
    "        metrics_df = pd.concat([metrics_df, metrics], axis=0)\n",
    "        print(\"Done\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics_df.reset_index(inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>conf_threshold</th>\n",
       "      <th>iou_threshold</th>\n",
       "      <th>precision</th>\n",
       "      <th>recall</th>\n",
       "      <th>f1_score</th>\n",
       "      <th>category</th>\n",
       "      <th>TP</th>\n",
       "      <th>FP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.324675</td>\n",
       "      <td>0.937500</td>\n",
       "      <td>0.482315</td>\n",
       "      <td>Crypto</td>\n",
       "      <td>150</td>\n",
       "      <td>312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.360248</td>\n",
       "      <td>0.983051</td>\n",
       "      <td>0.527273</td>\n",
       "      <td>Giardia</td>\n",
       "      <td>58</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.324675</td>\n",
       "      <td>0.937500</td>\n",
       "      <td>0.482315</td>\n",
       "      <td>Crypto</td>\n",
       "      <td>150</td>\n",
       "      <td>312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.360248</td>\n",
       "      <td>0.983051</td>\n",
       "      <td>0.527273</td>\n",
       "      <td>Giardia</td>\n",
       "      <td>58</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.324675</td>\n",
       "      <td>0.937500</td>\n",
       "      <td>0.482315</td>\n",
       "      <td>Crypto</td>\n",
       "      <td>150</td>\n",
       "      <td>312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.846154</td>\n",
       "      <td>0.372881</td>\n",
       "      <td>0.517647</td>\n",
       "      <td>Giardia</td>\n",
       "      <td>22</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>Crypto</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>159</th>\n",
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       "      <td>0.538462</td>\n",
       "      <td>0.237288</td>\n",
       "      <td>0.329412</td>\n",
       "      <td>Giardia</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
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       "    <tr>\n",
       "      <th>160</th>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>161</th>\n",
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       "      <td>Giardia</td>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>162 rows × 9 columns</p>\n",
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      "text/plain": [
       "     index  conf_threshold  iou_threshold  precision    recall  f1_score  \\\n",
       "0        0             0.1            0.1   0.324675  0.937500  0.482315   \n",
       "1        0             0.1            0.1   0.360248  0.983051  0.527273   \n",
       "2        0             0.1            0.2   0.324675  0.937500  0.482315   \n",
       "3        0             0.1            0.2   0.360248  0.983051  0.527273   \n",
       "4        0             0.1            0.3   0.324675  0.937500  0.482315   \n",
       "..     ...             ...            ...        ...       ...       ...   \n",
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       "160      0             0.9            0.9   0.000000  0.000000  0.000000   \n",
       "161      0             0.9            0.9   0.076923  0.033898  0.047059   \n",
       "\n",
       "    category   TP   FP  \n",
       "0     Crypto  150  312  \n",
       "1    Giardia   58  103  \n",
       "2     Crypto  150  312  \n",
       "3    Giardia   58  103  \n",
       "4     Crypto  150  312  \n",
       "..       ...  ...  ...  \n",
       "157  Giardia   22    4  \n",
       "158   Crypto    0    0  \n",
       "159  Giardia   14   12  \n",
       "160   Crypto    0    0  \n",
       "161  Giardia    2   24  \n",
       "\n",
       "[162 rows x 9 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "giardia_df = metrics_df[metrics_df.category == \"Giardia\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
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       "      <td>Giardia</td>\n",
       "      <td>26</td>\n",
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       "     index  conf_threshold  iou_threshold  precision    recall  f1_score  \\\n",
       "1        0             0.1            0.1   0.360248  0.983051  0.527273   \n",
       "3        0             0.1            0.2   0.360248  0.983051  0.527273   \n",
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       "161      0             0.9            0.9   0.076923  0.033898  0.047059   \n",
       "\n",
       "    category  TP   FP  \n",
       "1    Giardia  58  103  \n",
       "3    Giardia  58  103  \n",
       "5    Giardia  58  103  \n",
       "7    Giardia  58  103  \n",
       "9    Giardia  57  104  \n",
       "..       ...  ..  ...  \n",
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       "157  Giardia  22    4  \n",
       "159  Giardia  14   12  \n",
       "161  Giardia   2   24  \n",
       "\n",
       "[81 rows x 9 columns]"
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     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "giardia_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0</td>\n",
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       "    <tr>\n",
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       "      <td>0</td>\n",
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       "</table>\n",
       "<p>81 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     index  conf_threshold  iou_threshold  precision  recall  f1_score  \\\n",
       "0        0             0.1            0.1   0.324675  0.9375  0.482315   \n",
       "2        0             0.1            0.2   0.324675  0.9375  0.482315   \n",
       "4        0             0.1            0.3   0.324675  0.9375  0.482315   \n",
       "6        0             0.1            0.4   0.324675  0.9375  0.482315   \n",
       "8        0             0.1            0.5   0.320346  0.9250  0.475884   \n",
       "..     ...             ...            ...        ...     ...       ...   \n",
       "152      0             0.9            0.5   0.000000  0.0000  0.000000   \n",
       "154      0             0.9            0.6   0.000000  0.0000  0.000000   \n",
       "156      0             0.9            0.7   0.000000  0.0000  0.000000   \n",
       "158      0             0.9            0.8   0.000000  0.0000  0.000000   \n",
       "160      0             0.9            0.9   0.000000  0.0000  0.000000   \n",
       "\n",
       "    category   TP   FP  \n",
       "0     Crypto  150  312  \n",
       "2     Crypto  150  312  \n",
       "4     Crypto  150  312  \n",
       "6     Crypto  150  312  \n",
       "8     Crypto  148  314  \n",
       "..       ...  ...  ...  \n",
       "152   Crypto    0    0  \n",
       "154   Crypto    0    0  \n",
       "156   Crypto    0    0  \n",
       "158   Crypto    0    0  \n",
       "160   Crypto    0    0  \n",
       "\n",
       "[81 rows x 9 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crypto_df = metrics_df[metrics_df.category == \"Crypto\"]\n",
    "crypto_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_30068/932096624.py:2: FutureWarning: In a future version of pandas all arguments of DataFrame.pivot will be keyword-only.\n",
      "  giardia_df.pivot(\"conf_threshold\", \"iou_threshold\", \"precision\"),\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.heatmap(\n",
    "    giardia_df.pivot(\"conf_threshold\", \"iou_threshold\", \"precision\"),\n",
    "    annot=True,\n",
    "    fmt=\".2f\",\n",
    ");\n",
    "ax.invert_yaxis()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_30068/731401046.py:2: FutureWarning: In a future version of pandas all arguments of DataFrame.pivot will be keyword-only.\n",
      "  giardia_df.pivot(\"conf_threshold\", \"iou_threshold\", \"recall\"),\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(\n",
    "    giardia_df.pivot(\"conf_threshold\", \"iou_threshold\", \"recall\"),\n",
    "    annot=True,\n",
    "    fmt=\".2f\",\n",
    ");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_30068/2376446955.py:2: FutureWarning: In a future version of pandas all arguments of DataFrame.pivot will be keyword-only.\n",
      "  giardia_df.pivot(\"conf_threshold\", \"iou_threshold\", \"f1_score\"),\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(\n",
    "    giardia_df.pivot(\"conf_threshold\", \"iou_threshold\", \"f1_score\"),\n",
    "    annot=True,\n",
    "    fmt=\".2f\",\n",
    ");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1, 2, figsize=(10, 5))\n",
    "fig.suptitle(\n",
    "    f\"Precision-Recall Scatter Plot for {sample_type.replace('_', ' ')} using {model_type.replace('_', ' ').capitalize()}\"\n",
    ")\n",
    "\n",
    "for i in range(2):\n",
    "    if i == 0:\n",
    "        category = \"Crypto\"\n",
    "    else:\n",
    "        category = \"Giardia\"\n",
    "\n",
    "    ax = sns.scatterplot(\n",
    "        data=metrics_df[metrics_df[\"category\"] == category],\n",
    "        x=\"precision\",\n",
    "        y=\"recall\",\n",
    "        hue=\"iou_threshold\",\n",
    "        palette=\"tab10\",\n",
    "        style=\"conf_threshold\",\n",
    "        ax=axs[i],\n",
    "    )\n",
    "    axs[i].set_title(f\"{category.capitalize()}\")\n",
    "    axs[i].set_xlabel(\"Precision\")\n",
    "    axs[i].set_ylabel(\"Recall\")\n",
    "    axs[i].set_xticks(np.arange(0, 1.1, 0.1))\n",
    "    axs[i].set_yticks(np.arange(0, 1.1, 0.1))\n",
    "    if i == 0:\n",
    "        axs[i].get_legend().remove()\n",
    "\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.0)\n",
    "plt.tight_layout();"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.10.8 (main, Nov  1 2022, 14:18:21) [GCC 12.2.0]"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "a09bdcd8d95ec45310011d002ebb0ae06a2ec60abebd5286ddea637af0ac2275"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}