add example images to notebook

notebooks/3.0-hfk-model-performance-visualisation.ipynb

@@ -807,14 +807,11 @@
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "0.022158753"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "MAE: 0.0060480572283267975\n"
+     ]
     },
     {
      "data": {
@@ -832,11 +829,16 @@
    "source": [
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
+    "from torchmetrics import MeanAbsoluteError\n",
     "\n",
     "plt.scatter(ys, preds, s=1)\n",
     "plt.plot([-0.03, 0.03],[-0.03,0.03])\n",
     "\n",
-    "np.mean(np.abs(np.array(ys) - np.array(preds)))"
+    "ys_arr = torch.tensor(np.array(ys).flatten())\n",
+    "preds_arr = torch.tensor(np.array(preds).flatten())\n",
+    "\n",
+    "mean_absolute_error = MeanAbsoluteError()\n",
+    "print(f\"MAE: {mean_absolute_error(preds_arr, ys_arr)}\")\n"
    ]
   },
   {
@@ -887,7 +889,7 @@
      "output_type": "stream",
      "text": [
       "Type: trichuris\n",
-      "MAE: 0.020948385819792747\n"
+      "MAE: 0.006043851841241121\n"
      ]
     },
     {
@@ -919,7 +921,7 @@
      "output_type": "stream",
      "text": [
       "Type: ascaris\n",
-      "MAE: 0.022454742342233658\n"
+      "MAE: 0.006212816573679447\n"
      ]
     },
     {
@@ -951,7 +953,7 @@
      "output_type": "stream",
      "text": [
       "Type: schistosoma\n",
-      "MAE: 0.02243957854807377\n"
+      "MAE: 0.006195892579853535\n"
      ]
     },
     {
@@ -983,7 +985,7 @@
      "output_type": "stream",
      "text": [
       "Type: hookworm\n",
-      "MAE: 0.02211937867105007\n"
+      "MAE: 0.005734680686146021\n"
      ]
     },
     {
@@ -1027,7 +1029,12 @@
     "            ys.append(y.numpy())\n",
     "    \n",
     "    print(f\"Type: {type}\")\n",
-    "    print(f\"MAE: {np.mean(np.abs(np.array(ys) - np.array(preds)))}\")\n",
+    "\n",
+    "    ys_arr = torch.tensor(np.array(ys).flatten())\n",
+    "    preds_arr = torch.tensor(np.array(preds).flatten())\n",
+    "\n",
+    "    mean_absolute_error = MeanAbsoluteError()\n",
+    "    print(f\"MAE: {mean_absolute_error(preds_arr, ys_arr)}\")\n",
     "    plt.scatter(ys, preds, s=1)\n",
     "    plt.plot([-0.03, 0.03],[-0.03,0.03])\n",
     "\n",
@@ -1054,19 +1061,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
-     "ename": "FileNotFoundError",
-     "evalue": "[Errno 2] No such file or directory: 'img/0.0000_I03528_X007_Y019_Z5498.jpg'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
-      "\u001b[1;32m/home/hku/master_thesis_models/notebooks/3.0-hfk-model-performance-visualisation.ipynb Cell 10'\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      <a href='vscode-notebook-cell://ssh-remote%2B192.168.240.119/home/hku/master_thesis_models/notebooks/3.0-hfk-model-performance-visualisation.ipynb#ch0000009vscode-remote?line=4'>5</a>\u001b[0m tile_size \u001b[39m=\u001b[39m \u001b[39m150\u001b[39m\n\u001b[1;32m      <a href='vscode-notebook-cell://ssh-remote%2B192.168.240.119/home/hku/master_thesis_models/notebooks/3.0-hfk-model-performance-visualisation.ipynb#ch0000009vscode-remote?line=6'>7</a>\u001b[0m \u001b[39m#img = Image.open(\"img/0.0137_I03524_X007_Y019_Z5634.jpg\") \u001b[39;00m\n\u001b[0;32m----> <a href='vscode-notebook-cell://ssh-remote%2B192.168.240.119/home/hku/master_thesis_models/notebooks/3.0-hfk-model-performance-visualisation.ipynb#ch0000009vscode-remote?line=7'>8</a>\u001b[0m img \u001b[39m=\u001b[39m Image\u001b[39m.\u001b[39;49mopen(\u001b[39m\"\u001b[39;49m\u001b[39mimg/0.0000_I03528_X007_Y019_Z5498.jpg\u001b[39;49m\u001b[39m\"\u001b[39;49m) \n\u001b[1;32m      <a href='vscode-notebook-cell://ssh-remote%2B192.168.240.119/home/hku/master_thesis_models/notebooks/3.0-hfk-model-performance-visualisation.ipynb#ch0000009vscode-remote?line=8'>9</a>\u001b[0m img_grey \u001b[39m=\u001b[39m ImageOps\u001b[39m.\u001b[39mgrayscale(img)\n\u001b[1;32m     <a href='vscode-notebook-cell://ssh-remote%2B192.168.240.119/home/hku/master_thesis_models/notebooks/3.0-hfk-model-performance-visualisation.ipynb#ch0000009vscode-remote?line=10'>11</a>\u001b[0m img_crop \u001b[39m=\u001b[39m img\u001b[39m.\u001b[39mcrop([\u001b[39m0\u001b[39m, \u001b[39m0\u001b[39m, tile_size\u001b[39m*\u001b[39m\u001b[39mint\u001b[39m(img\u001b[39m.\u001b[39mwidth\u001b[39m/\u001b[39mtile_size), tile_size\u001b[39m*\u001b[39m\u001b[39mint\u001b[39m(img\u001b[39m.\u001b[39mheight\u001b[39m/\u001b[39mtile_size)])\n",
-      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/PIL/Image.py:2953\u001b[0m, in \u001b[0;36mopen\u001b[0;34m(fp, mode, formats)\u001b[0m\n\u001b[1;32m   <a href='file:///home/hku/.local/lib/python3.8/site-packages/PIL/Image.py?line=2949'>2950</a>\u001b[0m     filename \u001b[39m=\u001b[39m fp\n\u001b[1;32m   <a href='file:///home/hku/.local/lib/python3.8/site-packages/PIL/Image.py?line=2951'>2952</a>\u001b[0m \u001b[39mif\u001b[39;00m filename:\n\u001b[0;32m-> <a href='file:///home/hku/.local/lib/python3.8/site-packages/PIL/Image.py?line=2952'>2953</a>\u001b[0m     fp \u001b[39m=\u001b[39m builtins\u001b[39m.\u001b[39;49mopen(filename, \u001b[39m\"\u001b[39;49m\u001b[39mrb\u001b[39;49m\u001b[39m\"\u001b[39;49m)\n\u001b[1;32m   <a href='file:///home/hku/.local/lib/python3.8/site-packages/PIL/Image.py?line=2953'>2954</a>\u001b[0m     exclusive_fp \u001b[39m=\u001b[39m \u001b[39mTrue\u001b[39;00m\n\u001b[1;32m   <a href='file:///home/hku/.local/lib/python3.8/site-packages/PIL/Image.py?line=2955'>2956</a>\u001b[0m \u001b[39mtry\u001b[39;00m:\n",
-      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'img/0.0000_I03528_X007_Y019_Z5498.jpg'"
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Error: no \"view\" mailcap rules found for type \"image/png\"\n",
+      "Error: no \"view\" mailcap rules found for type \"image/png\"\n",
+      "Error when invoking the open external command: Error in response: Unable to parse response as JSON: \n",
+      "Error when invoking the open external command: Error in response: Unable to parse response as JSON: \n",
+      "Error: no \"view\" mailcap rules found for type \"image/png\"\n",
+      "Error when invoking the open external command: Error in response: Unable to parse response as JSON: \n",
+      "Error: no \"view\" mailcap rules found for type \"image/png\"\n",
+      "Error when invoking the open external command: Error in response: Unable to parse response as JSON: \n"
      ]
     }
    ],
@@ -1077,8 +1086,22 @@
     "\n",
     "tile_size = 150\n",
     "\n",
+    "root_file_folder = \"img/\"\n",
+    "files = [\n",
+    "    \"-0.021_I04131_X020_Y022_Z5078.jpg\",\n",
+    "    \"-0.014_I04133_X020_Y022_Z5146.jpg\",\n",
+    "    \"-0.006_I04135_X020_Y022_Z5214.jpg\",\n",
+    "    \"+0.000_I04136_X020_Y022_Z5283.jpg\",\n",
+    "    \"+0.007_I04138_X020_Y022_Z5351.jpg\",\n",
+    "    \"+0.014_I04139_X020_Y022_Z5419.jpg\",\n",
+    "    \"+0.021_I04140_X020_Y022_Z5488.jpg\",\n",
+    "    \"+0.027_I04137_X020_Y022_Z5556.jpg\",\n",
+    "    \"+0.034_I04134_X020_Y022_Z5625.jpg\",\n",
+    "    \"+0.041_I04132_X020_Y022_Z5693.jpg\",\n",
+    "]\n",
+    "\n",
     "#img = Image.open(\"img/0.0137_I03524_X007_Y019_Z5634.jpg\") \n",
-    "img = Image.open(\"img/0.0000_I03528_X007_Y019_Z5498.jpg\") \n",
+    "img = Image.open(os.path.join(root_file_folder, files[0])) \n",
     "img_grey = ImageOps.grayscale(img)\n",
     "\n",
     "img_crop = img.crop([0, 0, tile_size*int(img.width/tile_size), tile_size*int(img.height/tile_size)])\n",