data-analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob\n",
    "import numpy as np\n",
    "from tensorflow.keras.applications.resnet50 import ResNet50\n",
    "from tensorflow.keras.preprocessing import image\n",
    "from tensorflow.python.keras import layers\n",
    "from tensorflow.keras.applications.resnet50 import preprocess_input, decode_predictions\n",
    "from tensorflow.python.keras import models\n",
    "import tensorflow as tf\n",
    "from sklearn.preprocessing import LabelBinarizer\n",
    "from sklearn import metrics\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_many(path):\n",
    "    \"\"\"\n",
    "    Read all imagens in directory.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    path: str\n",
    "        Dataset path of a class (COVID or NON-COVID).\n",
    "    \n",
    "    Returns\n",
    "    -------\n",
    "    out : [ndarray]\n",
    "        List of images.\n",
    "    \"\"\"\n",
    "    # Get the path of all images\n",
    "    list_imgs = list(glob.glob(path))\n",
    "    out = []\n",
    "    \n",
    "    # Load all images of the given paths\n",
    "    for i in range(len(list_imgs)):\n",
    "        # Read the image in shape of (244, 244, 3)\n",
    "        try:\n",
    "            img = image.load_img(list_imgs[i], target_size=(224, 224, 3))\n",
    "            x = image.img_to_array(img)\n",
    "            out.append(x)\n",
    "        # Print error\n",
    "        except ValueError:\n",
    "            print('Error reading the following image:', list_imgs[i])\n",
    "    \n",
    "    # Return the loaded images\n",
    "    return out\n",
    "\n",
    "\n",
    "def load_dir(paths):\n",
    "    \"\"\"\n",
    "    Read images of COVID and NON-COVID cases.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    paths: [str]\n",
    "        Original and augmented dataset paths.\n",
    "    \n",
    "    Returns\n",
    "    -------\n",
    "    X : [ndarray]\n",
    "        List of images.\n",
    "    Y : [str]\n",
    "        Labels of the images (i.e., 0 - NON-COVID; 1 - COVID).\n",
    "    \"\"\"\n",
    "    # Arrays of images of COVID and NON-COVID cases\n",
    "    covid = []\n",
    "    non_covid = []\n",
    "    \n",
    "    # Read images\n",
    "    for path in paths:\n",
    "        # Read images of covid cases\n",
    "        covid.extend(read_many('{}/COVID/*'.format(path)))\n",
    "        # Read images of non-covid cases\n",
    "        non_covid.extend(read_many('{}/NON_COVID/*'.format(path)))\n",
    "    \n",
    "    # Set COVID classes\n",
    "    y_covid = np.asarray([1] * len(covid))\n",
    "    y_non_covid = np.asarray([0] * len(non_covid))\n",
    "    \n",
    "    # Merge the read images\n",
    "    X = np.concatenate([np.array(covid), np.array(non_covid)]) / 255\n",
    "    Y = np.concatenate([np.array(y_covid), np.array(y_non_covid)])\n",
    "    lb = LabelBinarizer()\n",
    "    Y=lb.fit_transform(Y)\n",
    "    \n",
    "    assert len(X) == len(Y), 'The number of images and the number of classes are different!'\n",
    "    print('Images read:', len(X))\n",
    "    \n",
    "    # Return the read images and their labels\n",
    "    return (X, Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_models(path):\n",
    "    models_name=list(glob.glob(path+\"*\"))\n",
    "    models={}\n",
    "    \n",
    "    for model_name in models_name:\n",
    "        #mprint(models_name)\n",
    "        file=model_name.split(\"/\")[-1]\n",
    "        name=file.split(\".\")[0]\n",
    "        models[name]=tf.keras.models.load_model(model_name)\n",
    "        \n",
    "    return models\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Images read: 800\n"
     ]
    }
   ],
   "source": [
    "TestX, TestY = load_dir(['Dataset/Test'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "models=load_models(\"modelos/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['Rotation', 'Sharpness', 'Noise', 'Contrast', 'None'])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "models.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rotation\n",
      "Sharpness\n",
      "Noise\n",
      "Contrast\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "preds={}\n",
    "for name in models.keys():\n",
    "    print (name)\n",
    "    preds[name]=models[name].predict(TestX)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "None\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.97      0.93      0.95       600\n",
      "           1       0.81      0.92      0.86       200\n",
      "\n",
      "    accuracy                           0.93       800\n",
      "   macro avg       0.89      0.92      0.90       800\n",
      "weighted avg       0.93      0.93      0.93       800\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Noise\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.96      0.96      0.96       600\n",
      "           1       0.89      0.87      0.88       200\n",
      "\n",
      "    accuracy                           0.94       800\n",
      "   macro avg       0.92      0.92      0.92       800\n",
      "weighted avg       0.94      0.94      0.94       800\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Rotation\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.95      0.98      0.97       600\n",
      "           1       0.93      0.86      0.90       200\n",
      "\n",
      "    accuracy                           0.95       800\n",
      "   macro avg       0.94      0.92      0.93       800\n",
      "weighted avg       0.95      0.95      0.95       800\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Sharpness\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.97      0.98      0.98       600\n",
      "           1       0.93      0.92      0.92       200\n",
      "\n",
      "    accuracy                           0.96       800\n",
      "   macro avg       0.95      0.95      0.95       800\n",
      "weighted avg       0.96      0.96      0.96       800\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Contrast\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.95      0.98      0.97       600\n",
      "           1       0.94      0.85      0.89       200\n",
      "\n",
      "    accuracy                           0.95       800\n",
      "   macro avg       0.95      0.92      0.93       800\n",
      "weighted avg       0.95      0.95      0.95       800\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "lb = LabelBinarizer()\n",
    "metrics_names={\"balanced accuracy\": [],\"f1-score\":[],\"precision\":[],\"recall\":[]}\n",
    "confusion_matrix={}\n",
    "order=[\"None\",\"Noise\",\"Rotation\",\"Sharpness\",\"Contrast\"]\n",
    "data=[]\n",
    "for pred_name in order:\n",
    "    data.append(preds[pred_name])\n",
    "    Y=lb.fit_transform(preds[pred_name]>0.5)\n",
    "    print (pred_name)\n",
    "    metrics_names[\"balanced accuracy\"].append(metrics.balanced_accuracy_score(TestY, Y))\n",
    "    metrics_names[\"f1-score\"].append(metrics.f1_score(TestY, Y))\n",
    "    metrics_names[\"precision\"].append(metrics.precision_score(TestY, Y))\n",
    "    metrics_names[\"recall\"].append(metrics.recall_score(TestY, Y))\n",
    "    confusion_matrix[pred_name]=metrics.confusion_matrix(TestY,Y)\n",
    "    print(metrics.classification_report(TestY, Y))\n",
    "    print ('\\n'*10)\n",
    "\n",
    "\n",
    "df2 = pd.DataFrame.from_dict(metrics_names, orient='index',columns=order)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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>None</th>\n",
       "      <th>Noise</th>\n",
       "      <th>Rotation</th>\n",
       "      <th>Sharpness</th>\n",
       "      <th>Contrast</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>balanced accuracy</th>\n",
       "      <td>0.921667</td>\n",
       "      <td>0.917500</td>\n",
       "      <td>0.920000</td>\n",
       "      <td>0.946667</td>\n",
       "      <td>0.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f1-score</th>\n",
       "      <td>0.859155</td>\n",
       "      <td>0.881013</td>\n",
       "      <td>0.895833</td>\n",
       "      <td>0.924242</td>\n",
       "      <td>0.894737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>precision</th>\n",
       "      <td>0.809735</td>\n",
       "      <td>0.892308</td>\n",
       "      <td>0.934783</td>\n",
       "      <td>0.933673</td>\n",
       "      <td>0.944444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>recall</th>\n",
       "      <td>0.915000</td>\n",
       "      <td>0.870000</td>\n",
       "      <td>0.860000</td>\n",
       "      <td>0.915000</td>\n",
       "      <td>0.850000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       None     Noise  Rotation  Sharpness  Contrast\n",
       "balanced accuracy  0.921667  0.917500  0.920000   0.946667  0.916667\n",
       "f1-score           0.859155  0.881013  0.895833   0.924242  0.894737\n",
       "precision          0.809735  0.892308  0.934783   0.933673  0.944444\n",
       "recall             0.915000  0.870000  0.860000   0.915000  0.850000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f6a6022d130>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "ax = df2.plot.bar(rot=0,figsize=(15, 10),fontsize=20)\n",
    "for p in ax.patches:\n",
    "    ax.annotate(\"{:.2f}\".format(p.get_height()), (p.get_x() * 1.005, p.get_height() * 1.010),fontsize=16,rotation=90)\n",
    "    \n",
    "ax.set_ylabel(\"Pontuação\",fontsize=20)\n",
    "ax.set_xlabel(\"Métrica Testada\",fontsize=20)\n",
    "ax.legend(loc=0,fontsize=16)  \n",
    "#plt.tick_params( labelsize=17)\n",
    "\n",
    "\n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "for i in order:\n",
    "    plt.figure(figsize=(15,10))\n",
    "    sns.distplot(preds[i][TestY==1],kde=False,bins=10)\n",
    "    sns.distplot(preds[i][TestY==0],kde=False,bins=10)\n",
    "    plt.legend([\"Labeled as COVID\", \"labeled as NON-COVID\"])\n",
    "    plt.title(i,fontsize=23)\n",
    "    plt.ylabel(\"Count (#)\",fontsize=17)\n",
    "    plt.xlabel (\"Probability\",fontsize=17)\n",
    "    plt.tick_params( labelsize=17)\n",
    "    plt.show()\n",
    "    \n",
    "#sns.distplot(preds[\"None\"],kde=False,bins=10)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in order:\n",
    "    plt.figure(figsize=(15,10))\n",
    "    sns.heatmap(confusion_matrix[i], annot=True, fmt='g',annot_kws={\"size\": 16})\n",
    "    #plt.legend([\"Labeled as COVID\", \"labeled as NON-COVID\"])\n",
    "    plt.title(i,fontsize=23)\n",
    "    #plt.ylabel(\"Count (#)\",fontsize=17)\n",
    "    #plt.xlabel (\"Probability\",fontsize=17)\n",
    "    plt.tick_params( labelsize=17)\n",
    "    plt.show()\n",
    "    "
   ]
  }
 ],
 "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": "3.9.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}