fix: update evaluation script to improve logging and file handling

Author: tuke307

tree-disk-evaluations/evaluation/evaluation.ipynb

@@ -22,6 +22,7 @@
     "import logging\n",
     "import matplotlib.pyplot as plt\n",
     "from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n",
+    "from tqdm import tqdm\n",
     "\n",
     "# Import the required packages directly\n",
     "import treedisksegmentation\n",
@@ -49,7 +50,10 @@
     "YOLO_PITH_MODEL_PATH = \"../models/yolo11s-det-pith.pt\"\n",
     "YOLO_SEG_MODEL_PATH = \"../models/yolo11s-seg-tree.pt\"\n",
     "DEBUG = False\n",
-    "SAVE_RESULTS = False"
+    "SAVE_RESULTS = False\n",
+    "\n",
+    "# evluation folder\n",
+    "EVALUATION_RESULTS = \"./results/\""
    ]
   },
   {
@@ -140,7 +144,7 @@
     "        output_dir=OUTPUT_DIR,\n",
     "        cx=int(pith[0]),\n",
     "        cy=int(pith[1]),\n",
-    "        sigma=1.0,\n",
+    "        sigma=4.0,\n",
     "        th_low=5.0,\n",
     "        th_high=15.0,\n",
     "        save_results=SAVE_RESULTS,\n",
@@ -239,20 +243,20 @@
     "    plt.tight_layout()\n",
     "    \n",
     "    # Save the combined figure with Titles (set transparent background)\n",
-    "    plt.savefig('evaluation_plots.png', dpi=300, transparent=True)\n",
-    "    plt.savefig('evaluation_plots.pdf', transparent=True)\n",
+    "    plt.savefig(os.path.join(EVALUATION_RESULTS, 'evaluation_plots.png'), dpi=300, transparent=True)\n",
+    "    plt.savefig(os.path.join(EVALUATION_RESULTS, 'evaluation_plots.pdf'), transparent=True)\n",
     "    \n",
     "    # Save each subplot individually WITHOUT Title\n",
     "    fig.canvas.draw()  # Update the renderer\n",
     "    for i, ax in enumerate([ax1, ax2, ax3, ax4], start=1):\n",
     "        original_title = ax.get_title()\n",
     "        ax.set_title('')  # Remove title\n",
     "        extent = ax.get_tightbbox(fig.canvas.get_renderer()).transformed(fig.dpi_scale_trans.inverted())\n",
-    "        plt.savefig(f'evaluation_plot_{i}.png', dpi=300, bbox_inches=extent, transparent=True)\n",
-    "        plt.savefig(f'evaluation_plot_{i}.pdf', bbox_inches=extent, transparent=True)\n",
+    "        plt.savefig(os.path.join(EVALUATION_RESULTS, f'evaluation_plot_{i}.png'), dpi=300, bbox_inches=extent, transparent=True)\n",
+    "        plt.savefig(os.path.join(EVALUATION_RESULTS, f'evaluation_plot_{i}.pdf'), bbox_inches=extent, transparent=True)\n",
     "        ax.set_title(original_title)  # Optionally restore the title\n",
     "    \n",
-    "    logger.info(f\"Evaluation plots saved to {OUTPUT_DIR}\")\n"
+    "    logger.info(f\"Evaluation plots saved to {EVALUATION_RESULTS}\")"
    ]
   },
   {
@@ -338,8 +342,8 @@
     "    basic_results = []\n",
     "    \n",
     "    # Process each image\n",
-    "    for img_data in ground_truth_json:\n",
-    "        logger.info(f\"Processing {img_data['path']}...\")\n",
+    "    for img_data in tqdm(ground_truth_json, desc=\"Processing images\", unit=\"image\"):\n",
+    "        tqdm.write(f\"Processing {img_data['path']}...\")\n",
     "        predicted_age, visualization = process_image(img_data)\n",
     "        \n",
     "        # Store the basic result\n",
@@ -357,7 +361,7 @@
     "            # logger.info(f\"  Result: True age = {img_data['age']}, Predicted age = {predicted_age}\")\n",
     "        else:\n",
     "            result[\"predicted_age\"] = None\n",
-    "            logger.error(f\"  Failed to process {img_data['path']}\")\n",
+    "            tqdm.write(f\"  Failed to process {img_data['path']}\")\n",
     "        \n",
     "        basic_results.append(result)\n",
     "    \n",
@@ -370,12 +374,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "basic_results_file = os.path.join(EVALUATION_RESULTS, \"basic_results.json\")\n",
+    "\n",
     "# Run the evaluation\n",
     "logger.info(\"Starting evaluation of the tree disk analysis pipeline...\")\n",
     "basic_results = evaluate_pipeline()\n",
     "\n",
     "# Save basic results first\n",
-    "basic_results_file = \"basic_results.json\"\n",
     "with open(basic_results_file, \"w\") as f:\n",
     "    json.dump(basic_results, f, indent=2)\n",
     "    \n",
@@ -388,76 +393,18 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "basic_results_file = \"basic_results.json\"\n",
     "basic_results = json.load(open(basic_results_file))\n",
     "\n",
     "# calculate metrics on top of the basic results\n",
     "metrics = calculate_metrics(basic_results)\n",
     "\n",
     "# Save metrics to a separate file\n",
-    "metrics_file = \"metrics.json\"\n",
+    "metrics_file = os.path.join(EVALUATION_RESULTS, \"metrics.json\")\n",
     "with open(metrics_file, \"w\") as f:\n",
     "    json.dump(metrics, f, indent=2)\n",
     "    \n",
     "logger.info(f\"Metrics saved to {metrics_file}\")"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "images_data = \"/Volumes/Tony SSD/Projekte/Studienarbeit/Datasets/uruDendro/images\"\n",
-    "annotations_data = \"/Volumes/Tony SSD/Projekte/Studienarbeit/Datasets/uruDendro/annotations\"\n",
-    "\n",
-    "# retrieve all .png files in the folder\n",
-    "files = [f for f in os.listdir(images_data) if f.endswith('.png')]\n",
-    "\n",
-    "# delete macosx files\n",
-    "files = [f for f in files if not f.startswith('._')]\n",
-    "files = [f for f in files if not f.startswith('.')]\n",
-    "\n",
-    "print(files)\n",
-    "\n",
-    "# go trough annotations_data and retrieve the json files mathcing the image files, the image name must be exactly the same\n",
-    "annotations = []\n",
-    "for f in files:\n",
-    "    for a in os.listdir(annotations_data):\n",
-    "        if f.split('.')[0] in a:\n",
-    "            annotations.append(a)\n",
-    "\n",
-    "annotations = [f for f in annotations if not f.startswith('._')]\n",
-    "annotations = [f for f in annotations if not f.startswith('.')]\n",
-    "annotations = [f for f in annotations if not '-M' in f]\n",
-    "annotations = [f for f in annotations if not '-V' in f]\n",
-    "annotations = [f for f in annotations if not '-S' in f]\n",
-    "annotations = [f for f in annotations if not '-C' in f]\n",
-    "\n",
-    "print(annotations)\n",
-    "\n",
-    "print(len(files))\n",
-    "print(len(annotations))\n",
-    "\n",
-    "# read the json files and save the lenght (number of times) of the shapes key\n",
-    "shapes = []\n",
-    "for a in annotations:\n",
-    "    with open(os.path.join(annotations_data, a)) as f:\n",
-    "        data = json.load(f)\n",
-    "        shapes.append(len(data['shapes']))\n",
-    "\n",
-    "print(shapes)\n",
-    "\n",
-    "# create a json array with the image name and the number of shapes\n",
-    "data = []\n",
-    "for i in range(len(files)):\n",
-    "    data.append({\n",
-    "        \"path\": files[i],\n",
-    "        \"age\": shapes[i]\n",
-    "    })\n",
-    "\n",
-    "print(data)"
-   ]
   }
  ],
  "metadata": {