{ "cells": [ { "cell_type": "markdown", "id": "cell-title", "metadata": {}, "source": [ "# Why Refractive Calibration Matters\n", "\n", "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/tlancaster6/AquaCal/blob/main/docs/tutorials/02_synthetic_validation.ipynb)\n", "\n", "Underwater imaging systems view targets through a flat air-water interface. A standard\n", "pinhole camera model ignores refraction at this interface, treating light as travelling\n", "in a straight line from camera to target. AquaCal corrects this using Snell's law.\n", "\n", "**But does it actually matter?** This tutorial answers that question with three\n", "controlled synthetic experiments:\n", "\n", "1. **Parameter Fidelity** — Can both models fit the data? Which one recovers correct parameters?\n", "2. **Depth Generalization** — Using the same calibration, how does 3D reconstruction accuracy vary with depth?\n", "3. **XY vs Z Anisotropy** — How does reconstruction precision differ between lateral (XY) and depth (Z) directions?\n", "\n", "Because we control all ground truth parameters, we can measure exactly where each\n", "model fails and why." ] }, { "cell_type": "code", "execution_count": 1, "id": "ae1whl2hdre", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Local environment — skipping install.\n" ] } ], "source": [ "# Colab setup — clones the repo and installs AquaCal if running on Google Colab.\n", "# This notebook imports test helpers from the repo's tests/ directory, so a full\n", "# clone is needed (not just pip install). When running locally, this cell is a no-op.\n", "import sys\n", "from pathlib import Path\n", "\n", "if \"google.colab\" in sys.modules:\n", " import os\n", " if not os.path.exists(\"/content/AquaCal/src\"):\n", " print(\"Colab detected — cloning repo and installing AquaCal...\")\n", " !git clone --depth 1 https://github.com/tlancaster6/AquaCal.git /content/AquaCal\n", " !pip install -q -e /content/AquaCal\n", " else:\n", " print(\"AquaCal repo already present.\")\n", " os.chdir(\"/content/AquaCal\")\n", " print(\"Done.\")\n", "else:\n", " print(\"Local environment — skipping install.\")" ] }, { "cell_type": "code", "execution_count": 2, "id": "cell-rig-size", "metadata": {}, "outputs": [], "source": [ "# Toggle rig size:\n", "# \"small\" — 4 cameras, 20 frames, ideal conditions. Fast, ~2 min total.\n", "# \"large\" — 12 cameras, 30 frames, realistic noise. Compelling results, ~60 min total.\n", "RIG_SIZE = \"large\"\n", "\n", "OUTPUT_DIR = Path(\"output\") # exported data artifacts" ] }, { "cell_type": "markdown", "id": "cell-setup-heading", "metadata": {}, "source": [ "## Setup and Imports" ] }, { "cell_type": "code", "execution_count": 3, "id": "cell-imports", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Imports complete.\n" ] } ], "source": [ "import sys\n", "from pathlib import Path\n", "\n", "import cv2\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "\n", "# Make sure project root is on path (needed when running as a notebook)\n", "_project_root = Path().resolve()\n", "while _project_root.name and not (_project_root / \"src\").exists():\n", " _project_root = _project_root.parent\n", "if str(_project_root) not in sys.path:\n", " sys.path.insert(0, str(_project_root))\n", "\n", "from aquacal.config.schema import BoardConfig, InterfaceParams\n", "from aquacal.core.board import BoardGeometry\n", "from aquacal.validation.reconstruction import triangulate_charuco_corners\n", "from aquacal.validation.reprojection import compute_reprojection_errors\n", "from tests.synthetic.experiment_helpers import (\n", " calibrate_synthetic,\n", " compute_per_camera_errors,\n", " evaluate_reconstruction,\n", ")\n", "from tests.synthetic.ground_truth import (\n", " SyntheticScenario,\n", " create_scenario,\n", " generate_dense_xy_grid,\n", " generate_real_rig_array,\n", " generate_real_rig_trajectory,\n", " generate_synthetic_detections,\n", ")\n", "\n", "# Consistent color palette for all plots\n", "COLOR_REFRACTIVE = \"#2196F3\" # Blue\n", "COLOR_NON_REFRACTIVE = \"#F44336\" # Red\n", "LABEL_REFRACTIVE = \"Refractive (AquaCal)\"\n", "LABEL_NON_REFRACTIVE = \"Non-refractive (pinhole)\"\n", "\n", "print(\"Imports complete.\")" ] }, { "cell_type": "markdown", "id": "cell-preset-heading", "metadata": {}, "source": [ "## Preset Configuration\n", "\n", "The `\"small\"` preset uses the `\"ideal\"` scenario: 4 cameras arranged in a grid,\n", "near the water surface (15 cm above), boards at 0.25–0.45 m depth, no noise.\n", "This is fast and lets you verify the math.\n", "\n", "The `\"large\"` preset uses the `\"realistic\"` scenario: 12 cameras with positions\n", "matching the real AquaCal hardware rig (idealized: common intrinsics, optical axes\n", "aligned to Z), water surface at ~1.03 m, boards at 1.1–2.0 m depth, 0.5 px noise.\n", "This produces compelling quantitative results." ] }, { "cell_type": "code", "execution_count": 4, "id": "cell-preset-config", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "RIG_SIZE = 'large'\n", " Scenario: realistic\n", " Test depths: [1.1, 1.2, 1.3, 1.4, 1.5, 1.7, 2.0, 2.5]\n" ] } ], "source": [ "if RIG_SIZE == \"small\":\n", " # create_scenario(\"ideal\"): 4 cameras at Z=0, water at Z=0.15, boards at Z=0.25-0.45m\n", " # All test/sweep depths must be > 0.15m (below water surface)\n", " SCENARIO_NAME = \"ideal\"\n", " TEST_DEPTHS = [0.22, 0.28, 0.35, 0.42, 0.50]\n", " N_GRID = 4 # smaller grid for 4-camera rig\n", " XY_EXTENT = 0.05\n", " XY_CENTER = (0.0, 0.0)\n", " TILT_DEG = 2.0\n", "else:\n", " # create_scenario(\"realistic\"): 12 cameras, water at ~1.03m, boards at 1.1-2.0m depth\n", " SCENARIO_NAME = \"realistic\"\n", " TEST_DEPTHS = [1.10, 1.20, 1.30, 1.40, 1.50, 1.70, 2.00, 2.50]\n", " N_GRID = 7\n", " XY_EXTENT = 0.5\n", " XY_CENTER = (-0.34, 0.55) # centroid of the 12-camera array\n", " TILT_DEG = 3.0\n", "\n", "print(f\"RIG_SIZE = {RIG_SIZE!r}\")\n", "print(f\" Scenario: {SCENARIO_NAME}\")\n", "print(f\" Test depths: {TEST_DEPTHS}\")" ] }, { "cell_type": "markdown", "id": "cell-exp1-heading", "metadata": {}, "source": [ "## Experiment 1: Parameter Fidelity\n", "\n", "**Question:** When we calibrate both models on identical data, do they recover\n", "the correct camera parameters?\n", "\n", "We generate a synthetic scenario with known ground truth, then run the full\n", "calibration pipeline twice — once with the refractive model (n_water = 1.333)\n", "and once with the non-refractive pinhole approximation (n_water = 1.0). Both\n", "optimizations minimize reprojection error on the same 2D observations.\n", "\n", "The key insight: **a model can fit 2D observations without learning correct 3D geometry**.\n", "If the model is wrong, it will compensate by adjusting focal length and camera positions." ] }, { "cell_type": "code", "execution_count": 5, "id": "cell-exp1-run", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "=== Experiment 1: Parameter Fidelity ===\n", "Scenario: 12-camera rig matching real hardware (idealized geometry)\n", " Cameras: 12\n", " Frames: 30\n", " Noise: 0.5 px\n", "\n", "Calibrating refractive model (n_water=1.333)...\n", "Stage 2: Extrinsic initialization...\n", "Stage 3: Joint refractive optimization...\n", "`ftol` termination condition is satisfied.\n", "Function evaluations 17, initial cost 3.3111e+04, final cost 3.4102e+03, first-order optimality 2.31e-03.\n", "Stage 4: Intrinsic refinement...\n", "`ftol` termination condition is satisfied.\n", "Function evaluations 21, initial cost 3.4102e+03, final cost 3.4054e+03, first-order optimality 1.50e+01.\n", " Reprojection RMS: 0.4984 px\n", "\n", "Calibrating non-refractive model (n_water=1.0)...\n", "Stage 2: Extrinsic initialization...\n", "Stage 3: Joint refractive optimization...\n", "`xtol` termination condition is satisfied.\n", "Function evaluations 42, initial cost 1.2535e+05, final cost 2.7124e+04, first-order optimality 4.26e-03.\n", "Stage 4: Intrinsic refinement...\n", "`xtol` termination condition is satisfied.\n", "Function evaluations 19, initial cost 2.7124e+04, final cost 1.5486e+04, first-order optimality 2.57e-03.\n", " Reprojection RMS: 1.3764 px\n", "\n", "Both calibrations complete.\n", " Note: similar reprojection errors (0.498 vs 1.376 px) — look at parameter errors next.\n", "\n", "Interface distance (water_z) recovery [refractive model only]:\n", " Ground truth: 1031.0 mm\n", " Estimated: 1032.2 mm\n", " Error: +1.19 mm (+0.115%)\n", "\n", "Calibration depth range: (1.13, 1.87) m\n" ] } ], "source": [ "print(\"=== Experiment 1: Parameter Fidelity ===\")\n", "scenario = create_scenario(SCENARIO_NAME, seed=42)\n", "print(f\"Scenario: {scenario.description}\")\n", "print(f\" Cameras: {len(scenario.intrinsics)}\")\n", "print(f\" Frames: {len(scenario.board_poses)}\")\n", "print(f\" Noise: {scenario.noise_std} px\")\n", "\n", "print(\"\\nCalibrating refractive model (n_water=1.333)...\")\n", "result_refr, _ = calibrate_synthetic(scenario, n_water=1.333, refine_intrinsics=True)\n", "errors_refr = compute_per_camera_errors(result_refr, scenario)\n", "print(f\" Reprojection RMS: {result_refr.diagnostics.reprojection_error_rms:.4f} px\")\n", "\n", "print(\"\\nCalibrating non-refractive model (n_water=1.0)...\")\n", "result_nonrefr, _ = calibrate_synthetic(scenario, n_water=1.0, refine_intrinsics=True)\n", "errors_nonrefr = compute_per_camera_errors(result_nonrefr, scenario)\n", "print(f\" Reprojection RMS: {result_nonrefr.diagnostics.reprojection_error_rms:.4f} px\")\n", "\n", "print(\"\\nBoth calibrations complete.\")\n", "print(f\" Note: similar reprojection errors ({result_refr.diagnostics.reprojection_error_rms:.3f} vs \"\n", " f\"{result_nonrefr.diagnostics.reprojection_error_rms:.3f} px) — \"\n", " \"look at parameter errors next.\")\n", "\n", "# Interface distance (water_z) recovery — refractive model only\n", "gt_wz = np.mean(list(scenario.water_zs.values()))\n", "est_wz = np.mean([c.water_z for c in result_refr.cameras.values()])\n", "wz_err_mm = (est_wz - gt_wz) * 1000\n", "wz_err_pct = (est_wz - gt_wz) / gt_wz * 100\n", "print(f\"\\nInterface distance (water_z) recovery [refractive model only]:\")\n", "print(f\" Ground truth: {gt_wz * 1000:.1f} mm\")\n", "print(f\" Estimated: {est_wz * 1000:.1f} mm\")\n", "print(f\" Error: {wz_err_mm:+.2f} mm ({wz_err_pct:+.3f}%)\")\n", "\n", "# Calibration depth range (for Experiment 2 plots)\n", "_board_zs = [bp.tvec[2] for bp in scenario.board_poses]\n", "CALIB_DEPTH_RANGE = (min(_board_zs), max(_board_zs))\n", "print(f\"\\nCalibration depth range: ({CALIB_DEPTH_RANGE[0]:.2f}, {CALIB_DEPTH_RANGE[1]:.2f}) m\")" ] }, { "cell_type": "markdown", "id": "cell-exp1-focal-heading", "metadata": {}, "source": [ "### Focal Length Recovery\n", "\n", "When refraction bends rays at the interface, a non-refractive model compensates by\n", "adjusting focal length. The result: a systematically biased focal length that happens\n", "to minimize 2D reprojection error but does not match the true optics." ] }, { "cell_type": "code", "execution_count": 6, "id": "cell-exp1-focal-plot", "metadata": {}, "outputs": [ { "data": { "image/png": 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3OH+v3qRfvIOkEf3Dhw+7lGLRys6qd62gnbTudV3zp0Uj5ArMFWQlLa//e2ltDz4FlcpmUECoi6YxhKcfa/smrT6ukwRJAxFRqnxaKeBXarW2RlMqtdLbgzqRk1Z6/0o7VtZBeN3rpJPmR2uV95OhrcD02epEg44jrTwfHiBrykfS9q3gW8fr8bbM0qrrml+v+edqTyczyqp28d///jfR1m2ahqCt+TRFwp8j75/4CV9nQaPCetyJ0mtrHYbw+f6a334yz5lWej9J14zQ6yYd6fY/s4zsJwAgvTDSDQDpQPM2Fcxo2yXNl/W3iEq6T6/ShhV4aaEpLVKk+ZoKpBQMaI9ZLc6loODxxx93iw5pCyEFqQqQwkcBT4S2lvJHzcJpex1tqaQ9n/Xa/jY7+sKv19YXcS3kFGlwpveqxao0Yqj3ormVSmVWMB4eiCsDQAGFAk6NMisA1WNOZP5qWun1FGiMGzfOpfLri79GNLVFmt6rTo5ozq5GWpX6rc9Ko+IKxLSVlUZKFVjrfSnIVr1qWy//pEVa24NotFlB/5QpU1yda1u0lBbx0wJbCgYV4KktKBVdAZpSmCPZw10p5v6CWZq+EIlvv/3WDhw4kGL2QPg2b5HQfH3Vu0546CSA5lNrhFXp9pqDntZF3lKjkxbKHNEJFi1El3RkX4vUaWszzf9W+1MAru2yFKgrYD+WW265xZ1MUSq6AmZlEuiEiT5H3a5AX+0ofNHB1GgrOD1e7Ubp7ToOdOJGbVDHrr/InLa/0jx81ZkW2dPj1HYiPTEWTm1Kx6bahhaeU5tWHfgnxIKkLde0UKLqWlNc1JZ1HCXtb3S86TPR1ACdjNHUjMsvv9x9vgCQ6QW2LjoAZBP+Fj0pbfMVbtasWV6DBg28fPnyeYUKFfJatmzp/frrr8ket27dOrdtVPHixd2WNmeeeabbZkdb+Yi2hdI2N6VLl3bPpeecO3eu23ZHlxPdMiy1i79FkbYn0rZS2iZIWziddtppbkuqZ555xjt06FCi13z66afTtPXPlClT3JZdep/Vq1f33n//fbdVkW4L9/3337utnfS64c+jLYO0lVlSuj8tf8JUX9WqVUvxPn/7svAyT58+3W1ppdfUReXUZ7N8+fJEvztnzhzviiuu8AoWLOgeV7NmTe+FF144ofYgn3/+uStLXFyct379+hQf8/vvv7t2o+2ecuXK5ZUtW9a7+uqrvWnTpkXUVtXOihYt6hUuXNjbv3+/lxbHa0PhdajrqrOkjlc2bRGm+tZ7K1mypNelS5dk27Id6/M8lrFjx7rX1ueV9D2vXr3a69Spk1epUiUvb968XrFixbzLLrvMfX5ppbbUpk0bd8yq/Pq8zz33XFcv4dup+dtbhW9Xl/Qz1vMUKVLEleX888/3Zs6cmeLjmjRp4o4r1dWAAQNCbSjplmEp1ZeOq/Bt+/x+6ZprrvFOOeUUd+zfd999bluz9NoyLLXPTVuh9evXz72mXrtp06beqlWrkm0Z5n+O6i+1vV94uVKr06R9JgBES5z+iXbgDwCIHRqx0uimv8IzMpZGRJX+r9H6pOsGAACA9MecbgBAIDTHNWnKq/ajVvqo5igjOrTwl+aBK5UYAAAEj5FuAEAgNDdai2RpTq5GVjXvWatBa16z5rsGtec4UvbDDz+4vZk1j1vzZSPZKx0AAJw4FlIDAARCi0dpQTYtVqaRVa0+rJWon3jiCQLuKNACcFq1XOn9EydOjEYRAACISYx0AwAAAAAQEOZ0AwAAAAAQEIJuAAAAAAACkqXndCckJNiGDRusYMGCFhcXF+3iAAAAAABihOd5tnv3brdgbHx8fPYMuhVwly9fPtrFAAAAAADEqPXr11u5cuWyZ9CtEW7/TRYqVCjaxQEAAAAAxIhdu3a5QWA/Ls2WQbefUq6Am6AbAAAAAJDRjjfVmYXUAAAAAAAICEE3AAAAAAABIegGAAAAACAgWXpONwAg8zp69KgdPnw42sUAsoVcuXJZjhw5ol0MAMAJIOgGAKT7npV///237dixg5oF0lGRIkWsVKlSx12wBwCQuRB0AwDSlR9wlyhRwk455RQCBCAdTmTt27fPNm3a5K6XLl2aOgWALISgGwCQrinlfsB96qmnUrNAOsmXL5/7qcBbxxep5gCQdbCQGgAg3fhzuDXCDSB9+ccVayUAQNZC0A0ASHfMOQU4rgAA/4egGwAAAACAgBB0AwCQjr777jurUaOG2+Lpuuuuy/C6vfTSS61Hjx6Bv87WrVvd3OK1a9dadjZx4kS3arhvzJgx1rJly6iWCQCQtbCQGgAgQ5w5ek+G1fTqLgUi/p2OHTvapEmT3P9z5sxp5cqVsxtuuMEef/xxy5s3b5qfp2fPnla7dm37+OOPrUCByMuRVrNnz7bLLrvMtm/fnigonDFjhgv4gzZkyBC79tpr7fTTT092X9OmTW3WrFk2b948O++88yyaK+mrnB9++KH99ddf7iSBPhudlGjcuPEJPWenTp1s0KBB9u2331rDhg3TvcwAgOyHkW4AAP6nWbNmtnHjRlu9erU9++yz9vLLL9ujjz4aUf38/vvvdvnll7ugPTwYDt/+6ciRI4HVebFixaxgwYIWJG1fNX78eLvjjjuS3ffHH3/Y999/b/fcc49NmDDBokUj8PXq1bMvv/zSnn76aVu6dKl98skn7kRFt27dTvh5c+fObbfccos9//zz6VpeAED2RdANAMD/5MmTx0qVKmXly5d3qeFNmjSxzz//PFQ/CQkJNmzYMDvjjDPcFk61atWyadOmhYI8LSCntGuNhur/Sk3WiLT+r5FvBYF6jTlz5rjgXCPFJUuWdCPiGhHW6HC4gwcPWr9+/Vx59HtnnXWWC3b1WgoepWjRou75NVKfNL18wIABdsEFFyT7fFVujeD7xo0bZ//617/ciH6VKlXspZdeOmab+Oijj1x5LrzwwmT3vfLKK3b11Vdbly5d7M0337T9+/cnun/lypV2ySWXuNeqWrWqq1+V/91333X3+/Wlred8ixcvdrf5qeyq47Zt21rZsmXdit5K59drhevatav7nf/+9792/fXX29lnn23VqlVzmQgagfeNGDHC/X7+/PldPev39uw5dlaG0svff//9ZO8NAICUkF4OIJG9TZJ/QU9v+Wf9QK0j0/v555/diG3FihVDtyngfv3119283sqVK9s333xj7dq1s+LFi9vFF1/sRsnPOeccF9DedNNNVrhwYfvhh/9r7w888IA988wzduaZZ7pAef369XbVVVe59GcFsK+++qoL5pYvX24VKlRwv9O+fXubO3euG1VVoLxmzRrbsmWLCw6nT5/ugkk9vlChQqF9nMPdeuutrswK8CtVquRu++WXX2zJkiXu92Xy5Mn2yCOP2KhRo6xOnTq2aNEiu+uuu1wQ2qFDhxTrRqnVOoGQ0ii+gu4XX3zRBe86SaCTErfddlvopEXr1q3diQbVy86dO09o/vmBAwfc6+uEhN670sf1GnqP559/vm3bts2Naqtu9T6SCs9AiI+Pd/WrEynKcFDQ3bdv32OeeDj33HNdtoLeg05yAABwLATdAAD8z8yZM92oswIqjTIrIFMwKro+dOhQNxpdv359d5sCaI1aKw29UaNGbpRco6sKtvX/cArEr7jiikRp4AqkfZon/M4777gRVKVmr1ixwqZOnepGgjXi7r9e+O+L5imnlMYuGtnVa7zxxhv28MMPh4JsjX4rIBalzw8fPtwFw6Lg89dff3XvKbWge926dVamTJlkt6tulHquOd2iExIamfeDbt3/22+/2aeffhr6fdVp8+bNI2qDGuHu3bt36Hr37t3dc6q+FHSvWrXKnQBQ4H884UG/5qcPHjzYOnfufMygW6Pr+oxVDwAAHA9BNwAA/6OU7dGjR9vevXvdnG4tqKbRZFEgp4AyPHCWQ4cOuRHi49HoaDilMD/22GNulFYj5Ar0la6sOdF+SnWOHDlcMH8yNNqtudUKuhWIKg1bKdai96lRcM3N1ui2T2VRUJkalTOlxeX0OhrhV72JUsD79OkTGmlftmyZG6UPD9j9ExiROHr0qAvWFWRrgTR9BjopomBY9D7TSicClA2gkwG7du1y710j6fqs/edLiTIL9BgAAI6HoBsAgP9RKrI/AqwAUqPE/oJh/jxfBckaaQ2n9PDjSZrmrJFajWIr5VyvqSCuTZs2LoCUlNLFT4QCX6VhL1y40AXLSmtXYCz+exo7dmyyud8K+FNz2mmnuVXTwymlWyP1hw8fdicuwgNk1aVSvdNC2QVJA2c9ZzgtjPbcc8/ZyJEjQ/OxNWLt151S/5VxoED6WDRH3J9/rvIpe0CZC/q89VzHCrr1fjWtAACA4yHoRkzJiPnKwpxlIOtT8KeFyDQqrNWqteiXgmuNRJ/s6LO/n7cWP2vVqlUoAA7f81rBpOZAf/3116H08qSraPtB7bFoFXWVV2nlCro1Uq+UdNHcao06ay6zRsTTSiP7mtseTs+v1/IXRPN99tlnLn1d6fVarE1Bv0b2S5cu7e4PX9RM/EBWj9Hcd3/UP2ndaRE6pa+L6knp+PqMRMGzUtw1t/zee+9NdsJDi7QpJX/BggXud1U+P9jX6PnxaOReo+FpyXAAAIDVywEASIX26daIr4I3bcOl0en777/f7eetwEujxy+88EJof+9IaDRWe2oroPzpp59cYK8AMHx+seZUayV0BbJaRE0re/tBoRZ402iu5qFv3rz5mCtuK6CeMmWKvf3228mC64EDB7r0ai0mpsBVW2tpMTSt6p0aBbRakC18tFsZARqpr169eqKLRo21+JsWNtPJA60irvel96wF2R588MFEz61Rf6WgK/VeK50rs0BBcdK6U5aAFrpTyvrdd99t//zzT6LH6DPTCQnN8daicXouPVbv009p12tpFF2foU48vPbaa26RvONRuTW/3l+cDgCAYyHoBgAgFZqbrEXNnnrqKTf/WYudaW60glSN2mpfbwWFWnwsUgpqNZJ70UUXuVXLFcjWrVs30WOUpq1AVitqa1EwzbtWOUQp7gqYtSq6RqxVztToObTNluYgayu0cHfeeafbMkyBtkbXNSqurc6O9Z70OJXVPwGgEWMF0f7893CaG964cWMXlGs0WSnoGnFXMKzXTpp2nitXLjfvXKnhNWvWtCeffNItbhbuoYcecq+vOtPq4Vq0Lun7UlCskyKap9+rVy93AkCj/F988UUo/V3TB/Q56DV0v0br9dkej8oXPgceAIBjifMiWW0kk9GCJ/pjri1HtGUIcDyklx8fW4bhZCjlViOyCthSWmgL2YdONmiRNG2t5qdmnyiN2CsYTxo4Z0Ya4b/88stdVsCxFpsLAscXAGTNeJQ53QAAIGItWrRwKdtaPVzp4LFCc821p3pGB9zh9t1+ox3dnDidPr2xNgkApB+CbgAAcELC97iOFSktagcAwLEQdAMAgKjKwjPdAADI/AupKS1NW36ceuqpbk9SLc7y448/RrtYAAAAAABk7ZFubTXSoEEDt7Loxx9/7Pbm1Pwwf19OAAAAAACysqgG3dqiQ4uvaJsS34lsuwIAAAAAQGYU1aD7/fffd3ts3nDDDfb111+7PUe1F2lqe18ePHjQXcKXaJeEhAR3AY4nIS4uQyopK7fHjKijrFw/OP5nq/m5/gVA+gkdW3FxgffV9NMAkH59ZVSD7tWrV9vo0aOtZ8+eNmDAAJs/f77de++9ljt3buvQoUOyxw8bNswGDhyY7PbNmze7vSuB4zlQsVKGVNLeTZssq8qIOsrS9fNQr8BfI+/g4ZZVHT582P0BOnLkiLsASD86pnR87ShT3nKcUiDQqs3K/TQAZJTdu3dn/qBbfzjOPfdcGzp0qLtep04d+/nnn23MmDEpBt39+/d3AXr4SLfS0zUX/FibkQO+vet+z5DKyF+iRJat9IyoI+on+9aPToDqD1DOnDndBUD60TEVHx9vRTast9xB79OdhfshAMgoefPmTdPjovqNqHTp0la1atVEt/3rX/+y6dOnp/j4PHnyuEtS+gOkC3A88RmU7pqV22NG1BH1k43rJz7e4uLiQhdkjO+++846d+5sv/32m7Vo0cLefffdDK36Sy+91GrXrm0jR44M9HW2bt3qvif897//tdNPPz1NvzNx4kS3n/iOHTsy9P089thj7nNYvHhxmh6/ZcsW951o4cKFVq5cuRQfEzq2PC/wvjor90MAkFHS2ldGNejWyuXLly9PdNuKFSusYsWKUSsTACAYe5tckGFVm3/WDxH/TseOHW3SpEluKtMDDzwQul2BU6tWrTL1HHVlgSlI1E4gBQoEl3Y8e/Zst+OIdh8pUqRI6PYZM2ZYrly5LGhDhgyxa6+9Ns0Bt9x000121VVXWWZ32mmnWfv27e3RRx+18ePHR7s4AIB0FNXTmPfff7/NmzfPpZevWrXK3njjDfvPf/5j3bp1i2axAAAxnCamnTUUVEabgvy0zov//fff7fLLL3cjpOHB8Ik814koVqyYFSxY0IK0b98+F4zecccdEf1evnz5rEQWSZW+/fbbbfLkybZt27ZoFwUAkF2C7vPOO8/eeecde/PNN6169eo2aNAgl8p16623RrNYAIAY1aRJEytVqpQb7T4WTYOqVq2am/KkUdfhwxMvfqfbdEK5U6dOLhitUKGCO6l8vFFkpQ5rtLpevXruuefMmePWP1F5tKWmAshatWrZtGnT3O+sXbvW/Y7SrvVa+r/SqVN7LgXnGikuWbKkGxHX3+FZs2YlKod2CenXr59bM0W/d9ZZZ7lgV6+lUW4pWrSoe35lB/jp2ErhFi2MesEFybMaVO7HH388dH3cuHEuVVwnOqpUqWIvvfTSMevno48+cuW58MILk9XZhx9+aDVr1nTPpfu1PoxP9RF+IkJp38oKeO2119znVLhwYbv55puTLYajeu/bt687oaA2od8L98cff7i6VD1qXZkbb7zR/vnn2POsj/ee1abKlCnjvhsBiG5mVtAXxJaoT9i5+uqrbenSpW7xnWXLlqW6XRgAAEHLkSOHC5ZfeOEF+/PPP1N8zIIFC1yApUBNf78UjD388MMuuAunQFyLhS5atMhth9mlS5dkU6pSotT2J554wv1NVCCpgPvVV191i4z+8ssvLkusXbt2bqtNBcYbN250QZ9OWuv/SqdO7bn27NnjUq2/+OILV65mzZpZy5YtXQDpU4qzToY///zz7vdefvllF1jqtfw1V/Q+9FrPPfdcsvLrxLnmXCvA96ncS5YssVtuucVd12juI4884tLF9Rqqc9Wh0vtT8+2337oTCCnp06ePq2/tgqLFVfWetJJ+alQ2TRuYOXOmu6guVU/hVJb8+fPbDz/8YE899ZQ7YfD555+HAnIF3BqR1u/qdu3IEl73SaX1PZ9//vnuvQIAsg+WlgUAIIzmb2skNLW5tSNGjLDGjRu7gEnOPvts+/XXX+3pp58OjfyKglsF26KR42effda++uorO+ecc45Z3wrurrjiitCos4IzjUbXr1/f3XbmmWe6UWsFw40aNXKjsBrt1Yit/p/ac4lGbTXi7FOGmUZV33//fbvnnnvcuipTp051QaRG/f3XC/99Ubp2Smns/mitXkNTxvw6UsCp0W+NmovqVkFy69at3XWN4qsO9Z5S2r1E1q1b50aBU6Ln89+nglil2et96eRIShQ06ySJnxJ/2223uRMRCoh9Okmh55XKlSvbqFGj3GP0OvqpEy5r1qxxJyNEJ0b03hX4K4MgpTKm5T3rPeqECAAg+yDoBgAgCc3r1hzp3r17J6sbjVJqlDPpwqAaaT569KgbLfeDNp+CYgXEm/6393Hz5s1Do5laPFQjwT6Njvu03onmMocHznLo0CG3zebxhD+XaKRbI/NKx9ZIteZ579+/PzTSrZW2VX4F8ydDo90TJkxwQbfmk2vk3N/yc+/evW6kWXOzw7PbVBadOEiNypna1iz+CQn/xIBObOhzSo3SysPnoGs3Ff+z8YV/fkkfo+dWsO0H3KKVx3UiQvclDbojec+aQqDPHCcuI1J3T2SxRgCxi6AbAIAkLrnkEmvatKn1798/0eh1JJKu5q3AWyOs/txeBZEpPU4pzeFBsihILlu2bKLHpbSFZlLhzyU6iaBR7GeeecaNOivAa9OmjQviRdfTQ9u2bd3ovra/0vtcv359KPXaf09jx45NNvfbP2GR2ure6bXA3bE+m0gek1aRvGelrCtFHgCQfRB0AwCQAs3xVZp50nRwLYSlfbHD6brSzI8VNIZLGkCnRqOnCq41En2yo89+OXUSQSn0fjCoBdJ8NWrUcIGl5in76eXhcufO7X5qRP9YlN6t8iqtXEG3Rur9FcS1iJtSqDUHOpKFUzWy//rrr6d4n3ZC0WJ1osBcafL6nIKi59aJBF380W6limsvcH1mSUXynrUInBamAwBkHwTdAACkQAGoAiQtKBauV69eLn1Y86E1ejt37lw33/d4q2+fCKVAa3Rai6cpGL744ott586dLnjW4mmpzX9OjeYma09tLTSmkVulf4eP3irtWs+pldD1vjU3W3OplVat+dFKhdfvafExzVnXyHhq+4Kr7jSPWaPoms8ebuDAgXbvvfe61Got5qa56z/++KMLmP009KT8zAM9RqunJ527fuqpp7rg9sEHH3Sj4tddd50FRSck/PahaQVKE9f8fZ1oSJrSH8l7Vlq5FurTPH4AQPYR9dXLAQDIrBTMJU0prlu3rltsbMqUKW67S61IrcedaBr68Si4V3CsVcw1wqqATenmWogrUloETgHrRRdd5AJvBbJ6P+FGjx7tUs4VRGpbK81B1pxkf4RewaNWRVeAq8XXUqPn0FZmCiSTBsB33nmnS7F/5ZVXXPCqYFULmx3rPelxft2nlJVw3333udXN//77b/vggw9Co/JB0ImH9957z9WlpiIoCNeCc2+99Vaqv5OW96zn1Ih9w4YNAys7ACDjxXla4SSL2rVrlztjrLP+OuMPHE9G7YuYlRdYYQEa6udkaPtHreisQCK1Ra+AE6WTDdoeTCnY8fHxbp9u7R2u0eLUVlPPSrTHuEbD/a3VUju+Sj7ez/JsPvae4CeLv2PZt35wfHwXQnrHo6SXAwCALKFFixa2cuVK++uvvxKtHJ4dbNmyxW0npkXoAADZC0E3AADIMnr06GHZkeah9+3bN9rFAAAEgKAbAABkSVrlOwvPkgMAxAgWUgMAAAAAICCMdAMAAAAxgkVlgYzHSDcAIN0l3WYLQPodV3EcXwCQpTDSDQBIN9obWVs5bdiwwYoXL+6ua09jACdO89YPHTpkmzdvdsdXrh3bqE4AyEIIugEA6UYBgfbo3rhxowu8AaSfU045xSpUqGCHjx6lWgEgCyHoBgCkK41uKzA4cuSIHSU4ANJFjhw5LGfOnC5z5DB1CgBZCkE3ACDdKTDIlSuXuwAAAMQyFlIDAAAAACAgBN0AAAAAAASE9HIAAJBpsIcwACC7YaQbAAAAAICAEHQDAAAAABAQgm4AAAAAAAJC0A0AAAAAQEAIugEAAAAACAhBNwAAAAAAASHoBgAAAAAgIATdAAAAAAAEhKAbAAAAAICAEHQDAAAAABCQnEE9MaJjb5MLAn+N/LN+CPw1AAAAACA7IOgGAGSpE3/CyT8AAJBVkF4OAAAAAEBACLoBAAAAAAgIQTcAAAAAAAFhTjcAAAAAIE1YvyVyjHQDAAAAABAQgm4AAAAAAAJC0A0AAAAAQEAIugEAAAAACAhBNwAAAAAAASHoBgAAAAAgIATdAAAAAABkx6D7scces7i4uESXKlWqRLNIAAAAAACkm5wWZdWqVbNZs2aFrufMGfUiAQAAAACQLqIe4SrILlWqVLSLAQAAAABA9gu6V65caWXKlLG8efNa/fr1bdiwYVahQoUUH3vw4EF38e3atcv9TEhIcBeYJcTFBV4NWbmuM6J+3OtQR9QP7YdjDCfWf9JPZ4o64u8Y9UMb4hiLZh+UVfqhtJYxqkH3BRdcYBMnTrRzzjnHNm7caAMHDrSGDRvazz//bAULFkz2eAXkekxSmzdvtgMHDmRQqTO3AxUrBf4aezdtsqwqI+pHqCPqh/bDMZZqP/RQr8D7oLyDh1tWRT+dOeqIv2PUD22IYyyafVBW6Yd2796d+YPu5s2bh/5fs2ZNF4RXrFjRpk6danfccUeyx/fv39969uyZaKS7fPnyVrx4cStUqFCGlTsz27vu98BfI3+JEpZVZUT9CHVE/dB+OMai2Q/RB1FHtCGOsWj2QfRD1E+stKG8efNmjfTycEWKFLGzzz7bVq1aleL9efLkcZek4uPj3QVm8Z4XeDVk5brOiPpxr0MdUT+0H46xKPZD9EHUEW2IYyyafRD9EPUTK20oPo1lzFTvZM+ePfb7779b6dKlo10UAAAAAABOWlSD7t69e9vXX39ta9eute+//95atWplOXLksLZt20azWAAAAAAApIuoppf/+eefLsDeunWrm5d98cUX27x589z/AQAAAADI6qIadE+ZMiWaLw8AAAAAQKAy1ZxuAAAAAACyE4JuAAAAAAACQtANAAAAAEBACLoBAAAAAAgIQTcAAAAAAAEh6AYAAAAAICAE3QAAAAAABISgGwAAAACAgBB0AwAAAAAQEIJuAAAAAAACQtANAAAAAEBACLoBAAAAAAgIQTcAAAAAAAEh6AYAAAAAICAE3QAAAAAABISgGwAAAACAgBB0AwAAAAAQEIJuAAAAAAACQtANAAAAAEBAckby4GXLltmUKVPs22+/tXXr1tm+ffusePHiVqdOHWvatKldf/31lidPnqDKCgAAAABA9hvpXrhwoTVp0sQF13PmzLELLrjAevToYYMGDbJ27dqZ53n24IMPWpkyZezJJ5+0gwcPBl9yAAAAAACyw0i3RrD79Olj06ZNsyJFiqT6uLlz59pzzz1nw4cPtwEDBqRnOQEAAAAAyJ5B94oVKyxXrlzHfVz9+vXd5fDhw+lRNgAAAAAAsn96eVoC7pN5PAAAAAAA2dEJr16+ceNGa9OmjVtIrVixYtayZUtbvXp1+pYOAAAAAIBYDLo7depk1atXt6+//tq+/PJLK1mypN1yyy3pWzoAAAAAAGIh6L7vvvts7969oeurVq2yfv36WdWqVa127dru/uXLlwdVTgAAAAAAsu8+3eXKlbN69erZU089Zddcc43ddNNNbuuwq666yi2cNmPGDLv11luDLS0AAAAAANkx6NaWYZrD3bVrV5s4caK98MILLuiePXu2HT161AXjuh8AAAAAAEQYdMsZZ5xhH3/8sU2ePNkaNWrkUsqfeeYZi4uLi+RpAAAAAACICREvpLZ161aXRj5//nxbtGiR25d7yZIlwZQOAAAAAIBYCLq/+OILt0K5tgjT/O7ffvvNJkyYYMOGDbO2bdta3759bf/+/cGWFgAAAACA7Bh0d+vWzQXW+/bts1GjRlmPHj3c7ZdddpktXLjQcuXK5VYxBwAAAAAAEQbdGzdutBYtWljevHmtWbNmtnnz5tB9efLksSFDhrgVzAEAAAAAQIQLqWmbMK1Orp9z5sxxW4UlVa1atbQ+HQAAAAAA2V6aR7rHjx9vd999t+3cudPatWtnI0eODLZkAAAAAADEykh37ty5rXv37sGWBgAAAACAWBvpnjdvXpqfUAut/fLLLydTJgAAAAAAYifovu2226xp06b29ttv2969e1N8zK+//moDBgywSpUq2YIFC9K7nAAAAAAAZM/0cgXUo0ePtoceeshuueUWO/vss61MmTJuJfPt27e7Pbv37NljrVq1ss8++8xq1KgRfMkBAAAAAMgOQbf24L733nvd5ccff3Srl69bt872799vtWrVsvvvv9/t112sWLHgSwwAAAAAQHZbSM137rnnugsAAAAAAEinLcMAAAAAAEAWDbqfeOIJi4uLsx49ekS7KAAAAAAAZJ+ge/78+fbyyy9bzZo1o10UAAAAAACyT9CtVc9vvfVWGzt2rBUtWjTaxQEAAAAAIDoLqR0+fNiaNWtmY8aMscqVK6dLAbp162YtWrSwJk2a2ODBg4/52IMHD7qLb9euXe5nQkKCu8AsIS4u8GrIynWdEfXjXoc6on5oPxxjUeyH6IOoI9oQx1g0+yD6IeonVtpQQhrLGFHQra3DlixZYullypQptnDhQpdenhbDhg2zgQMHJrt98+bNduDAgXQrV1Z2oGKlwF9j76ZNllVlRP0IdUT90H44xqLZD9EHUUe0IY6xaPZB9EPUT6y0od27dwezZVi7du1s/PjxbuGzk7F+/Xq777777PPPP7e8efOm6Xf69+9vPXv2TDTSXb58eStevLgVKlTopMqTXexd93vgr5G/RAnLqjKifoQ6on5oPxxj0eyH6IOoI9oQx1g0+yD6IeonVtpQ3jTGsREH3UeOHLEJEybYrFmzrF69epY/f/5E948YMSJNz7NgwQLbtGmT1a1bN3Tb0aNH7ZtvvrFRo0a5NPIcOXIk+p08efK4S1Lx8fHuArN4zwu8GrJyXWdE/bjXoY6oH9oPx1gU+yH6IOqINsQxFs0+iH6I+omVNhSfxjJGHHT//PPPoUB5xYoVie7Tll9p1bhxY1u6dGmi226//XarUqWK9evXL1nADQAAAABAVhNx0P3VV1+lywsXLFjQqlevnug2jZqfeuqpyW4HAAAAACArOqkx+z///NNdAAAAAABAOgTdWhb98ccft8KFC1vFihXdpUiRIjZo0KCTXtZ99uzZNnLkyJN6DgAAAAAAsmx6+YMPPhhavbxBgwbutjlz5thjjz3mtu0aMmRIEOUEAAAAACD7B92TJk2ycePG2TXXXBO6rWbNmla2bFnr2rUrQTcAAAAAACeaXr5t2za3wnhSuk33AQAAAACAEwy6a9Wq5fbRTkq36T4AAAAAAHCC6eVPPfWUtWjRwmbNmmX169d3t82dO9fWr19vH330UaRPBwAAAABAthXxSHejRo1sxYoV1qpVK9uxY4e7tG7d2pYvX24NGzYMppQAAAAAAGT3ke7Dhw9bs2bNbMyYMSyYBgAAAABAeo5058qVy5YsWRLJrwAAAAAAELMiTi9v166d26cbAAAAAACk80JqR44csQkTJriF1OrVq2f58+dPdP+IESMifUoAAAAAALKliIPun3/+2erWrev+rwXVwsXFxaVfyQAAAAAAiKWg++jRozZw4ECrUaOGFS1aNLhSAQAAAAAQa3O6c+TIYVdeeaXbJgwAAAAAAKTzQmrVq1e31atXR/prAAAAAADEnIiD7sGDB1vv3r1t5syZtnHjRtu1a1eiCwAAAAAAOMGF1K666ir385prrkm0cJrnee665n0DAAAAAIATCLq/+uor6g0AAAAAgCCC7kaNGkX6KwAAAAAAxKQ0z+l+6qmnbP/+/aHr3333nR08eDB0fffu3da1a9f0LyEAAAAAANk96O7fv78LrH3Nmze3v/76K3R937599vLLL6d/CQEAAAAAyO5BtxZKO9Z1AAAAAABwkluGAQAAAACAtCHoBgAAAAAgM6xePm7cOCtQoID7/5EjR2zixIl22mmnuevh870BAAAAAEAEQXeFChVs7NixoeulSpWy1157LdljAAAAAABAhEH32rVr0/pQAAAAAADAnG4AAAAAAILDQmoAAAAAABB0AwAAAACQtTDSDQAAAABAQAi6AQAAAADIDPt0+xISEmzVqlW2adMm9/9wl1xySXqVDQAAAACA2Aq6582bZ7fccoutW7fOPM9LdF9cXJwdPXo0PcsHAAAAAEDsBN2dO3e2c8891z788EMrXbq0C7QBAAAAAEA6BN0rV660adOm2VlnnRXprwIAAAAAEFMiXkjtggsucPO5AQAAAABAOox0L1myJPT/7t27W69evezvv/+2GjVqWK5cuRI9tmbNmml5SgAAAAAAsr00Bd21a9d2c7fDF07r1KlT6P/+fSykBgAAAABAhEH3mjVr0vIwAAAAAAAQadBdsWLF0P+/+eYbu+iiiyxnzsS/euTIEfv+++8TPRYAAAAAgFgW8UJql112mW3bti3Z7Tt37nT3AQAAAACAEwy6/bnbSW3dutXy588f6dMBAAAAAJBtpXmf7tatW7ufCrg7duxoefLkCd139OhRt8K50s4BAAAAAECEI92FCxd2F410FyxYMHRdl1KlStm///1ve/311y0So0ePdluMFSpUyF3q169vH3/8cUTPAQAAAABAlh/pfuWVV9zP008/3Xr37p0uqeTlypWzJ554wipXruyC+UmTJtm1115rixYtsmrVqp308wMAAAAAkCWCbt+jjz6abi/esmXLRNeHDBniRr/nzZtH0A0AAAAAiL2gu06dOikupKbb8ubNa2eddZab8x3pSuaaF/7222/b3r17XZo5AAAAAAAxF3Q3a9bMjUbXqFHDzj//fHfb/Pnz3UJqCrZ//fVXa9Kkic2YMcOlih/P0qVLXZB94MABK1CggL3zzjtWtWrVFB978OBBd/Ht2rXL/UxISHAXmCWkcEIkvWXlus6I+nGvQx1RP7QfjrEo9kP0QdQRbYhjLJp9EP0Q9RMrbSghjWWMOOjesmWL9erVyx5++OFEtw8ePNjWrVtnn332mUtBHzRoUJqC7nPOOccWL17s9vmeNm2adejQwb7++usUA+9hw4bZwIEDk92+efNmF7TD7EDFSoFXw95Nm7JsVWdE/Qh1RP3QfjjGotkP0QdRR7QhjrFo9kH0Q9RPrLSh3bt3p+lxcZ5WMIuAVitfsGCBSyMPt2rVKqtXr54Lnn/77Tc777zz0lyIcBolr1Spkr388stpGukuX768bd++3a1+DrO9TYPfti3/p99n2arOiPoR6oj6of1wjEWzH6IPoo5oQxxj0eyD6Ieon1hpQ7t27bKiRYu6GPhY8WjEI92at/39998nC7p1m+7zh9n9/0dKvxseWIfT3uDh+4P74uPj3QVm8ZGdQzkhWbmuM6J+3OtQR9QP7YdjLIr9EH0QdUQb4hiLZh9EP0T9xEobik9jGSMOurt3726dO3d2o90azfbndI8bN84GDBjgrn/66adWu3bt4z5X//79rXnz5lahQgU3Kv7GG2/Y7Nmz3e8DAAAAAJDVRRx0P/TQQ3bGGWfYqFGj7LXXXgvNyx47dqzdcsst7rqC8i5duhz3uTZt2mTt27e3jRs3urT1mjVruoD7iiuuOJH3AgAAAABA1g665dZbb3WX1OTLly9NzzN+/PgTeXkAAAAAALJv0C2HDh1yI9VJl0lXqjgAAAAAADiBoHvlypXWqVMnt3BaOC2CHhcXZ0ePHqVeAQAAAAA4kaC7Y8eOljNnTps5c6aVLl3aBdoAAAAAACAdgu7Fixe7lcurVKkS6a8CAAAAABBTIt78rGrVqrZly5ZgSgMAAAAAQCwH3U8++aT17dvX7ae9detW27VrV6ILAAAAAAA4wfTyJk2auJ+NGzdOdDsLqQEAAAAAcJJB91dffRXprwAAAAAAEJMiDrobNWoUTEkAAAAAAIj1Od3y7bffWrt27eyiiy6yv/76y9322muv2Zw5c9K7fAAAAAAAxE7QPX36dGvatKnly5fPFi5caAcPHnS379y504YOHRpEGQEAAAAAiI2ge/DgwTZmzBgbO3as5cqVK3R7gwYNXBAOAAAAAABOMOhevny5XXLJJcluL1y4sO3YsSPSpwMAAAAAINuKOOguVaqUrVq1Ktntms995plnple5AAAAAACIvaD7rrvusvvuu89++OEHi4uLsw0bNtjkyZOtd+/e1qVLl2BKCQAAAABALGwZ9sADD1hCQoI1btzY9u3b51LN8+TJ44Lu7t27B1NKAAAAAABiIejW6PaDDz5offr0cWnme/bssapVq1revHndqHeZMmWCKSkAAAAAANk96Pblzp3bBdu+n376yerWrWtHjx5Nr7IBAAAAABBbc7oBAAAAAEDaEHQDAAAAABAQgm4AAAAAAKI9p3vJkiXHvH/58uXpUR4AAAAAAGIv6K5du7ZbudzzvGT3+bfrJwAAAAAAiDDoXrNmTVofCgAAAAAAIgm6K1asSIUBAAAAABABFlIDAAAAACAgBN0AAAAAAASEoBsAAAAAgIAQdAMAAAAAEBCCbgAAAAAAorl6eZ06ddK8B/fChQtPtkwAAAAAAMRO0H3dddcFXxIAAAAAAGIx6H700UeDLwkAAAAAANkMc7oBAAAAAIjmSHe4o0eP2rPPPmtTp061P/74ww4dOpTo/m3btqVn+QAAAAAAiJ2R7oEDB9qIESPspptusp07d1rPnj2tdevWFh8fb4899lgwpQQAAAAAIBaC7smTJ9vYsWOtV69eljNnTmvbtq2NGzfOHnnkEZs3b14wpQQAAAAAIBaC7r///ttq1Kjh/l+gQAE32i1XX321ffjhh+lfQgAAAAAAYiXoLleunG3cuNH9v1KlSvbZZ5+5/8+fP9/y5MmT/iUEAAAAACBWgu5WrVrZF1984f7fvXt3e/jhh61y5crWvn1769SpUxBlBAAAAAAgNlYvf+KJJ0L/12JqFStWtO+//94F3i1btkzv8gEAAAAAEDtBd1IXXnihuwAAAAAAgJNMLx82bJhNmDAh2e267cknn4z06QAAAAAAyLYiDrpffvllq1KlSrLbq1WrZmPGjIk4gD/vvPOsYMGCVqJECbvuuuts+fLlkRYJAAAAAIDss2VY6dKlk91evHjx0KrmafX1119bt27d3P7en3/+uR0+fNiuvPJK27t3b6TFAgAAAAAg68/pLl++vH333Xd2xhlnJLpdt5UpUyai5/rkk08SXZ84caIb8V6wYIFdcsklkRYNAAAAAICsHXTfdddd1qNHDzcqffnll7vbtIVY3759rVevXidVmJ07d7qfxYoVO6nnAQAAAAAgSwbdffr0sa1bt1rXrl3t0KFD7ra8efNav379rH///idckISEBBfMN2jQwKpXr57iYw4ePOguvl27doV+VxeYJcTFBV4NWbmuM6J+3OtQR9QP7YdjLIr9EH0QdUQb4hiLZh9EP0T9xEobSkhjGSMOuuPi4twq5Q8//LAtW7bM8uXL5/bozpMnj50Mze3++eefbc6cOcdceG3gwIHJbt+8ebMdOHDgpF4/uzhQsVLgr7F30ybLqjKifoQ6on5oPxxj0eyH6IOoI9oQx1g0+yD6IeonVtrQ7t27g92nu0CBAqEF1U424L7nnnts5syZ9s0331i5cuVSfZxG0nv27JlopFtzzLWIW6FChU6qDNnF3nW/B/4a+UuUsKwqI+pHqCPqh/bDMRbNfog+iDqiDXGMRbMPoh+ifmKlDeXNmzeYoFtD6IMHD7bhw4fbnj173G3a8kvzuR988EGLj0/7guie51n37t3tnXfesdmzZydbnC0pBfcpBfh6zUheNzuL97zgXyML13VG1I97HeqI+qH9cIxFsR+iD6KOaEMcY9Hsg+iHqJ9YaUPxaSxjxEG3Auvx48fbE0884eZfi1LCH3vsMZfiPWTIkIhSyt944w177733XOCu7cikcOHCLm0dAAAAAICsLOKge9KkSTZu3Di75pprQrfVrFnTypYt6xZXiyToHj16tPt56aWXJrr9lVdesY4dO0ZaNAAAAAAAsnbQvW3bNqtSpUqy23Wb7ouE0ssBAAAAAMiuIk6Ur1Wrlo0aNSrZ7bpN9wEAAAAAgBMc6X7qqaesRYsWNmvWLKtfv767be7cubZ+/Xr76KOPIn06AAAAAACyrYhHuhs1amQrVqywVq1a2Y4dO9yldevWtnz5cmvYsGEwpQQAAAAAIDuPdK9evdpt6RUXF2dlypSJaME0AAAAAABiUZpHuitXrmybN28OXb/pppvsn3/+CapcAAAAAADETtCddKVxzd/eu3dvEGUCAAAAACA253QDAAAAAIB0Dro1l1uXpLcBAAAAAICTXEhN6eUdO3a0PHnyuOsHDhywzp07W/78+RM9bsaMGWl9SgAAAAAAsrU0B90dOnRIdL1du3ZBlAcAAAAAgNgLul955ZVgSwIAAAAAQDbDQmoAAAAAAASEoBsAAAAAgIAQdAMAAAAAEBCCbgAAAAAAAkLQDQAAAABAQAi6AQAAAAAICEE3AAAAAAABIegGAAAAACAgBN0AAAAAAASEoBsAAAAAgIAQdAMAAAAAEBCCbgAAAAAAAkLQDQAAAABAQAi6AQAAAAAICEE3AAAAAAABIegGAAAAACAgBN0AAAAAAASEoBsAAAAAgIAQdAMAAAAAEBCCbgAAAAAAAkLQDQAAAABAQAi6AQAAAAAICEE3AAAAAAABIegGAAAAACAgBN0AAAAAAASEoBsAAAAAgIAQdAMAAAAAEBCCbgAAAAAAAkLQDQAAAABAQAi6AQAAAAAICEE3AAAAAAABIegGAAAAACA7Bt3ffPONtWzZ0sqUKWNxcXH27rvvRrM4AAAAAABkn6B77969VqtWLXvxxRejWQwAAAAAAAKR06KoefPm7gIAAAAAQHbEnG4AAAAAALLjSHekDh486C6+Xbt2uZ8JCQnuArOEuLjAqyEr13VG1I97HeqI+qH9cIxFsR+iD6KOaEMcY9Hsg+iHqJ9YaUMJaSxjlgq6hw0bZgMHDkx2++bNm+3AgQNRKVNmc6BipcBfY++mTZZVZUT9CHVE/dB+OMai2Q/RB1FHtCGOsWj2QfRD1E+stKHdu3dnv6C7f//+1rNnz0Qj3eXLl7fixYtboUKFolq2zGLvut8Df438JUpYVpUR9SPUEfVD++EYi2Y/RB9EHdGGOMai2QfRD1E/sdKG8ubNm/2C7jx58rhLUvHx8e4Cs3jPC7wasnJdZ0T9uNehjqgf2g/HWBT7Ifog6og2xDEWzT6Ifoj6iZU2FJ/GMkY16N6zZ4+tWrUqdH3NmjW2ePFiK1asmFWoUCGaRQMAAAAA4KRFNej+8ccf7bLLLgtd91PHO3ToYBMnToxiyQAAAAAAyOJB96WXXmpeBqW4AAAAAACQ0TJ/ojwAAAAAAFkUQTcAAAAAAAEh6AYAAAAAICAE3QAAAAAABISgGwAAAACAgBB0AwAAAAAQEIJuAAAAAAACQtANAAAAAEBACLoBAAAAAAgIQTcAAAAAAAEh6AYAAAAAICAE3QAAAAAABISgGwAAAACAgBB0AwAAAAAQEIJuAAAAAAACQtANAAAAAEBACLoBAAAAAAgIQTcAAAAAAAEh6AYAAAAAICAE3QAAAAAABISgGwAAAACAgBB0AwAAAAAQEIJuAAAAAAACQtANAAAAAEBACLoBAAAAAAgIQTcAAAAAAAEh6AYAAAAAICAE3QAAAAAABISgGwAAAACAgBB0AwAAAAAQEIJuAAAAAAACQtANAAAAAEBACLoBAAAAAAgIQTcAAAAAAAEh6AYAAAAAICAE3QAAAAAABISgGwAAAACAgBB0AwAAAAAQEIJuAAAAAAACQtANAAAAAEBACLoBAAAAAAgIQTcAAAAAAAEh6AYAAAAAICAE3QAAAAAABCSnZQIvvviiPf300/b3339brVq17IUXXrDzzz/fspszR+8J/DWWBv4KALIq+iAAAIAYHOl+6623rGfPnvboo4/awoULXdDdtGlT27RpU7SLBgAAAABA1h7pHjFihN111112++23u+tjxoyxDz/80CZMmGAPPPBAtIuHDMQoHGhDiDb6IQDI3OinkRVFNeg+dOiQLViwwPr37x+6LT4+3po0aWJz585N9viDBw+6i2/Xrl3uZ0JCgrtkdvEWfBkT4uKCf42A6jq71I97nSzQHlNDG6J+Mnv7ca9DPxSV+skIWb0NZYSs3E9nBOon+vXjXod+Oir1c/bLwU9nXZTF21A0yhjVoHvLli129OhRK1myZKLbdf23335L9vhhw4bZwIEDk91+/fXXW86cOd3ccD3mzz//tHPOOcc6depk/fr1c4+59dZb7fDhwzZ16tTQCLse//vvv9vpp59uPXr0cBdp06aN5cuXz1577bXQ6+r/v/76q5UpU8Yefvhh69Kli7uvZcuWrrzjxo1z11W+d955xxYvXmynnXaaPfXUU64c0rVpU6tUqZK99NJL7vqAAQPsiy++sB9++MEKFCjgyqPHqk4uvfRSq1Onjj377LPusb169bL58+fbN998Y7lz57axY8da165dbe/evVa/fn1r1KiRPfHEE9YmvrDdc889rv5mzZrlfnfSpEnuvW3fvt3q1atnV199dage7777bldfyi6Ql19+2aX6a3599erVrW3btvbggw+6+zp06GC7d++2Gc2bu+uae6+5+H/88YdVrlzZPVfv3r3dfTfffLP7OWXKFPfzmWeecc+9cuVKq1ChgvXp08e6d+/u7mvdurUVLFjQKr07yV0fMmSIvfnmm/bzzz9bqVKlXFn13NKiRQsrV66cey5RWWfOnOlO3hQtWtRGjhzpyik6eVOlShUbNWqUu67MieENmrkTOvnz53efg7IsdPLnkksusfPOO8+GDx/uHnv//ffbokWLbPbs2ZYjRw6XedGtWzfbs2ePXXDBBda4cWMbOnTo/32uXbu6dvTpp5+663ps59tuc+27du3a1qpVK1dOufPOO+2ff/6xDz74wF0fPXq0DRo0yDZs2GBVq1a12267LXQSSv/fv3+/TZs2zV3Xe9Nl7dq1rh2pPJqaITfeeKPlypXLJk+e7K4/+eSTrhzLly939aXn1OPluuuuc3X1yiuvuOuDBw+2t99+23766ScrUaKEDZ3wtiunNG/e3CpWrOgyUOShhx5y71NtsXDhwvb8889bx44dzfM8u/zyy61GjRr23HPPucfqM/7+++/tu+++s7x587rPTJ/jgQMHrMHgwXbRRRe59iP33XefLV261L788kuLi4uziRMn2r333ms7d+50n4umnKic0rlzZ1u3bp19/PHH7rqOPR1LmpLSulYtu+GGG1w5RRk0avfvvvuuu54efYSOsaD6iKZ+H/G/Yyy9+4hK7z7hHhtkH/FGm9ttxowZgfQRKmeoj+jTJ5A+ot0/XwfeR+yaON369u0bbB9xzz2B9BG/HTzVqt/ymC14qau7r1TdK+2U4hVt9adj3fV/3fCA/b3oc9u+aoHlyl/Yat/xjM1/4W4zL8FK1LzUClWoZqtmvugee/Z199vW5fNs67K5Fp87r9Xr/IItGNPdahQtbA0aNAikj6gV3kc0bx5IHyGB9xHxhQP7HhHqI4YPD6SPGP7NVvtr3nvueu07h9uK90bavs3rrUDpSnbmlXfYkkkD3H3lL77B/Vw/5233s2aHobb6s/G2Z+Pvdkrx8nb2tT1s8bhe7r6yF15rOfMVtHVfve6uzxw3KrDvEV9//b8+ok2bQL9HBNpHxBcO9nvE0KH/9z2iefNAvkdU0veIgPuINu/+3zEWaB/xxhuB9BHDA441ZPa9DwYba8z43/eIVauC+x6RTn2EXist4jy18ihRB1G2bFl3QOnD9KmjUaemBnK8ke7y5cu7D7hQoUIZWnYAAAAAQOzatWuXC8Z1gudY8WhUR7p1dkZn/3TGLpyu66xDUnny5HGXpJSSrgsAAAAAABkhrTFoVCNVpS4oBUFpD+F58boePvINAAAAAEBWFPXVyzWXRHnx5557rtubW3nymjvgr2YOAAAAAEBWFfWg+6abbrLNmzfbI4884ibUa8GITz75JNniagAAAAAAZDVRXUgtPSaua+XD401cBwAAAAAgGvEoq48BAAAAABAQgm4AAAAAAAJC0A0AAAAAQEAIugEAAAAACAhBNwAAAAAAASHoBgAAAAAgIATdAAAAAAAEhKAbAAAAAICAEHQDAAAAABAQgm4AAAAAAAKS07Iwz/Pcz127dkW7KAAAAACAGLLrf3GoH5dmy6B79+7d7mf58uWjXRQAAAAAQAzavXu3FS5cONX747zjheWZWEJCgm3YsMEKFixocXFxFut0pkUnINavX2+FChWKdnEyHeqHOqINcYxFG/0Q9UMb4hijD8rc6Kepn0golFbAXaZMGYuPj8+eI916Y+XKlYt2MTIdBdwE3dQPbYhjjD4o86Kfpn5oQxxj9EGZG/009ZNWxxrh9rGQGgAAAAAAASHoBgAAAAAgIATd2UiePHns0UcfdT9B/dCGOMbogzIf+mnqhzbEMUYflLnRT1M/QcjSC6kBAAAAAJCZMdINAAAAAEBACLoBAAAAAAgIQTcAAAAAAAEh6AYAAAAAICAE3QAAAAAABISgOwtggXkA9EGZ1/79+6NdhExv9+7d0S5CprZhwwZbsmRJtIuBLI7vi9QT7SfzIujOxLZt2+b+EK9YsSLaRcn0EhISol2ETPtFd/v27bZ27drQbfxR/v82b95sy5Yts7lz50bl88kKVq1aZZMmTXLtCMkpUOrUqZP99ddfVE8qfvnlF7vyyivts88+o45S8PPPP9vZZ59to0aNon5SsH79eps+fbpNmDDB1q1bRx2lYOvWrbZx40b79ddfqZ8U/PHHHzZ16lSbPHmyO97i4uKopzB79+51P1UvfEcMDkF3Jv4i16hRI7v88svt/PPPt3bt2tm8efOiXaxM90WuT58+7v/x8fF0FCnUz/XXX+/a0WWXXWZPPPGEu50/Nv9Hf3gVCNx0003WoEEDu+eeezK2AWcBCrTVdhRUvvXWW7Znz55oFylT+emnn6xOnTp21llnWdmyZd1tnABM3g9dfPHFVq9ePatQoUJUPqfMbPHixXbRRRdZ5cqV7dNPP7Uffvgh2kXKdN+FVD/PPvus3XXXXXbHHXe4AQkkriP109dcc437W9aqVSv74osvqKKw+jnvvPNs8ODB9vDDD1vdunXd/xWIw9yJGvU/OiEhBN4B8pDp/Pnnn17ZsmW9fv36eV999ZX36aefeuecc47XsGFD79VXX4128TKFVatWeaVLl/bi4uK8W2+9NXR7QkJCVMuVWfz6669e0aJFvT59+nivvfaa98wzz3h58+b13n777WgXLVP45ZdfXP3079/f+/HHH713333Xi4+P95YsWRLtomU6N9xwg3fppZe6Y23kyJHe9u3bE90fq8ec2kq+fPm8Bx98MNHtSesnlu3fv99r0aKF9+9//zvUVtR3f/31197u3bu9WPfTTz+5NvTQQw95q1ev9s4880x3jMmRI0e8WLdu3Trv9NNP9x599FFvz5497nrOnDnddyL8H7Wb8uXLew8//LC3aNEi16bKlCnjVapUyRs9enTMV9OOHTu8c889130X2rt3r7d582ZvzJgxXv78+V2/tHz58piuoz/++MOrUaOGazPFihXzJk+e7MX63/YgEXRnQh999JELsrds2RK6bcOGDd7VV1/tXXzxxd60adO8WKYva127dvWuv/5610Gceuqp3o033hi6P9Y7im3btnlNmzb17r///tBt+mOj9tO3b18v1uto06ZN7gRWr169EgVKV1xxhfftt9+6L3QETv/3pf/w4cNe27ZtvQULFnjPPfecC7xfeuklV2dTpkyJ2Xb0119/uZN+jRs3Dt3Wo0cPd7169eruhKm+3MU6BUrnnXee98MPP7jrTZo0cV+A1Y50DD799NNerNJJG9WDAu7wNlSqVClv69atUS1bZvH66697559/vrdr167Qbddcc403btw413a+/PJLL9YpsFa/o75aF5k0aZI7maPvi/p/rH8fqlq1qjdjxoxEt+t68eLFvXvuucf1U7FI7WXo0KHuu/Rnn33m9ezZ0ytYsCCBd4BIL8+k9u3bZzt37nT/P3TokJUuXdrGjh1ruXLlstGjR7v5O7FKqS+nn366tW3b1m655RaX9jpr1iyXJuzfH8tzUtRu9P4vvfTS0G2nnHKKVa1a1aV6ytGjRy1WqX0o3bV9+/ah21544QX76quv7L777rMbbrjBWrZsafPnz7dYliNHDsuZM6drN0p7vffee23QoEEuDV+pekrT27Rpk8UqzcHNly+fvfbaa649KUXv3HPPdf3Siy++aHfeeafrx2PdkSNH7J9//rG7777btaf//Oc/bmpHlSpVbMaMGaGUxljz999/22OPPeaOKX9KgvqkwoULu7mnEutTFXbt2mU7duwIpQE/9dRT9sEHH9gnn3zivg/169fPnn/+eYtlWq9F0350bPly585tV1xxhfu/5sEfPnzYYpG+B6lu1Ib8Ocv6Pq3blYL/0ksvub76o48+slikNtO4cWO77rrrXHvp1auX+7vVuXNne+ONN9xjYv37dLoLMqLHiVm7dq072/TYY4+Fbjt06JD7qfSqAgUKhFLQYlV4aqJG5HSWTiPeSoX1HTx40FuzZo0Xa44ePRoaWQpPU1T6mUa7Y5k/Mht+Zvu9997zChcu7E2fPt1ll2hURel6yqaA540YMcK78sorQ1VRp04dN0LXu3dv78CBAzF5fPn9tI6n0047zf38559/Qo9ZunSpm87hZwXEKrWPyy67zOvQoYN32223eZ988knovp07d3rNmjVzmRSxzu+X9FNZSsoCgOetWLHCK1GihMseueqqq1xquTIB/VG69u3be5dffrnL5IpVyszKkSOHywrQdI5ly5Z5p5xyipuKqD4pT548bvpULFPWn/rplStXhtqO349369bNu/DCC913gljN3Eqabp50xFv9uKa6hmec4MQw0p0JVaxY0UaMGOHOgI8bNy50Rkqjk1qIRgtmLF++3GJZ/vz5QyMBGpFr0qSJOzP35Zdfhka8e/ToYf3794+50SYtKqeRyPD68Ue7dZbXp1ECtbFY4i8ip7rwaQGsOXPmWOvWra1IkSJWsGBBt8DamjVrLJb5o2yXXHKJFStWzP3/tttucyu+60y4sgNGjhwZGkGItTakflqrTSszolu3blaiRIlQvVWvXt1dVq5cabEsT548NnDgQJeN9Prrr7vRXV+hQoVCx1l4vxRL/BEktSm1G/1Un6yMJNVXLFPdaHGnb7/91h555BGXTaLvPvpbr+wJfSfSIqFa2TzW/saHq1+/vj344IOub65du7ZbsFCLzel68eLFXVZgLGZG6njyj68uXbq4xdNuvfVWtxuH2o5/X7ly5dxxp++UsbTIbNIsGr8+ypcv7zL+tGih/s6rHxowYIAbDT948GCUSpt9EHRnAn5jD9/r9eabb3apHl27dnUpMOoM/OBJqUL6whLLdeR3juE/lR7z5ptv2tdffx1Kx1cdhgdYsVo/oqkJ/pdb/ZF++umnrWnTphYLUqsf0ZcUBUiiY0xf6JTWqD/SsSRpHenkjehEhIKACy64wD7//HOX3qk+qWfPni7dM1YCJr9+Dhw4ELpNgffQoUMTTeVQvelEhE7eKIU61v+WNWzY0LUXpeK//fbb9ttvv4Xu00mJM844I9TWYrUf0u1+HahN1ahRw/0di7UU8/D68etG0zh0Yqto0aLub5gufir1okWL3M4BsfA3PrU2pH5GJ7a06r36IvXPfsq9gm1NVzjttNMslne00ckbDcLoe/O1115rS5cuDX2f1onAAgUKuBM32T2N+lg7/oR/J9LgnupLgbemvGiKgv72x0o7CtQJjpAjnfjpLB9++KFLjW7durVLF1K6lNJdtGqnUjlvvvlml87ZpUsXl16uFKJYryOtSil+mpAovap58+Yu1VwpnrFYP1oUI7x+/PTywYMHe23atHErmSvlTItjxYJI2o9oYSPtHqDUxliRUh0pFViL0Iiu161bN1mbiZXFwo5XP0nTErWiuVZdjqXpLanVkZ+SqHRXpb02aNDAa9WqldexY0c3rSNWdgw4Xj8U3oa0SKH+7i9cuNCL9fbjL2r53XffuTp54IEHvIkTJ7qFMLUDhVbrjtU60nGkNpTSwnuakqgFHStWrOitX7/ei9UdbfzF5WT27NmuznLlyuVdcsklbuqL0qgXL17sZXcnsuOPpv4UKVLE7faC9EHQnQnMmTPHfRnRKor16tXzqlWr5g0cODD0x0YrdGrOoFao1B+iWPojk1odaY6X5rz7X/oVOCm4fPzxx12nEgudaCT1I8OGDXN1oy8q8+fP92JJWupHX2Q071RzCGPlhERa6kgn/7Styu+//x56rH+iIpbmwKWlDX3wwQfui4rmD8ZSwHSsv2XhdaQAW8GSdpvQY37++WcvlhyvDelvmI4pzavUVmvhx1ws14+/XoKCba04rXaludyxcsImkjak9qPHdO7c2W0BFQv90PF2tAkPvHWMaf67Tq5r5e5Y2DIs0h1/dH3s2LHuu2IsfhcKEkF3JqB9lMMXTdOZXC1WpIWv/v77b3ebv1BILC5clFod6Q+O6sj/Y6Pg4Pnnn4+5L3JprZ933nnHjeDGSgZApPWjk1safdMe57EotX5I2Tb+SEosBdkn0oY+//xz92UmFvug1OpIGRKqo40bN7rb/EVBY3Ef6rS0IV8sLlp0rPbj148CcPVHsVg/aW1D+t44fPjwmAgo/e9+Tz31VGg73VmzZrkTDuGBZSz2N5HUT9K/7T/++GPMnfTLCP9/jwFkGJ3s0PwJzUfSfBItilaqVKnQ/cOGDXP3z5w508270CIQJUuWDG0FEQvSWkcffvihm5ujBR9UR1rQKBbmB0ZSP6oPrQ2ghTDCF8XKziJtP6ofLdJz0UUXucWfYkFa6+j99993P9UP+YuFxYITaUNa5EkLPuXNm9diQaT9UPjfMvrp5G0o/BjTXN3sLtLvQtp2Tuu1xJJIjzF9F9L9mpMbC8eYaBE0HTuamy1aY2PKlClu+8Ybb7zRbcGn40vrj/z555925plnWixJS/2oDal+/vrrL7fOhta6QQAyJLRHMm+//babm12uXDmX8qstQpLOy1H6yxlnnOENGTIk2bzTWBBpHfmpebEirfWjuaVKo4q1NsQxRh1l5DFGP83fMvoh+ukg8F3o+PzvfuFTnzTfPTyVWmsiaX2kWNxijvrJHAi6o9DolQKk/SXHjx/vUqU011bpQXfddZe3adOmRL8zaNAgb/Xq1V6soI6oH9oPxxh9UOZGP0390H44xjJDH7Rv374Ub/f//9lnn3klS5b0SpUq5fZ5j5X1bKifzImgO4PpgNeqiVdeeaW3du3a0O0jRozw6tev791xxx3JAu9YQx1RP7QfjjH6oMyNfpr6of1wjEUDO9pQP1lVbEz4yESWLVtme/bssR9//DHR3pL333+/24tS+5bec889bn/FWEUdUT+0H44x+qDMjX6a+qH9cIxFg+Yff/fdd+47s9aIWLdunfXq1ctGjhxpW7ZscXPZtb/90aNH7emnn7ZPPvnEvvjiC6tevbrFAuon8yLozmC33HKL9e3b1y2WokUMwoNrBd5Nmza1nTt3ugUNYhV1RP3QfjjG6IMyN/pp6of2wzEWLWvWrHHfpV944QU3iHX11VfbBx98YM8//3wo8D5w4IAVKVLEli5darVq1bJYQv1kTnEa7o52IbL7qpPbt293KyIfPHjQihYt6s6+aeXA0aNHW+HChe311193t/u2bdsWEytMC3VE/dB+OMbogzI3+mnqh/bDMZaZVnH//vvv3Srt2rHGN2DAAPv000/tmmuuCe1ooxHvWFjFnfrJIqKd357d55zMnDnTzd+uXr26d8MNN3gffPCBu/3w4cNuv8WLLrrIu+aaa7wtW7Z4sYY6on5oPxxj9EGZG/009UP74RjLDFjFnfrJ6gi6A/Tee+95p5xyituu6dVXX/U6duzoFSlSJLRBvQLvyZMne1WrVnVbGsTalk5CHVE/tB+OMfqgzI1+mvqh/XCMRQM7JVA/2QlBd0BWrlzpnXvuud5LL73krmtrMO31+q9//cvt+zp16tRQ4P3WW295a9as8WINdUT90H44xuiDMjf6aeqH9sMxFk3slED9ZBcE3QGckTt48KC3detWr3v37i5tfP369d7ZZ5/t/fvf//aWL1/uNWzY0AXeGuWONdQR9UP74RijD8rc6KepH9oPx1hmoUzRunXresWKFUu2pa6229U2vMoWjcVpmkL9ZB0E3en8JeXzzz/3evTo4a1evdrbtWuXu03Xr7/+em/37t3uuoLv4sWLexUqVPB27NgR+t3sjjqifmg/HGP0QZkb/TT1Q/vhGMtMjhw54k2ZMsWrUqWK17hx42TB9ZAhQ7ymTZt6GzZs8GIR9ZN1ZP8l/TKIVlWcMWOGWzVRK49rK7CCBQva4cOHbfHixVauXDkrUKCAe2yuXLls6NChbhVGrV6u340F1BH1Q/vhGKMPytzop6kf2g/HWLT4Gypp1599+/a5nzly5LA2bdrYQw895LYBa9++vbs9fNXyN954w0qXLm3ZHfWTxUU76s8ulDZ+xhlnhOZwh+vTp4935plnuvuUcl66dGk3Eh5rqCPqh/bDMUYflLnRT1M/tB+OsWhgpwTqJ7vLGe2gP7v4448/3Aj2VVddlWzfvLZt29qePXvs6aefdqPgH374oZ1xxhkWa6gj6of2wzFGH5S50U9TP7QfjrFo0Pfl999/331n1qi2MkS//PJLu+2222zcuHF2/fXX28033+z23R4yZIh17drV3nzzzZjYh1uon6yPoDudKKjev39/6HpCQkIobVwpMkqHUdCtdPMiRYpYLKKOqB/aD8cYfVDmRj9N/dB+OMaiYdWqVTZo0CB75plnrEuXLrZp0yaXOq608Y4dO7rv1TfccIPdeOONljNnTjv//PNjJuAW6ifri53WGrBatWrZli1b7D//+Y+7ro7AD7qnTZvmRrfz5csXswG3UEfUD+2HY4w+KHOjn6Z+aD8cYxk9R/nQoUMuE7R+/fouqP7zzz+tYcOGLnv03XfftTp16linTp3c3G0F3HrM6aefbtkd9ZPNRDu/PTsZP368lytXLjeHe+nSpd6vv/7q9e3b1ytSpIi3bNmyaBcvU6COqB/aD8cYfVDmRj9N/dB+OMaCxk4J1E+sIehOR0ePHvWmTp3qFS1a1CtXrpx31llneeecc463cOHC9HyZLI06on5oPxxj9EGZG/009UP74RjLCNOnT/fy5cvnPf744978+fPdbYcOHfIuvfRS77777gs9rlu3bt7YsWO9rVu3erGE+sle4vRPtEfbs5sNGzbYunXrXHq5FkwrWbJktIuU6VBH1A/th2OMPihzo5+mfmg/HGNBWbFihTVr1sz69Onj5nCH69u3r02fPt169+5ty5Ytc9M0v/vuu5hahJj6yX4IugEAAABkmFmzZlm3bt3ss88+s4oVKyba9WfRokU2duxY++STT9xcb/1f87pjCfWT/bB6OQAAAIAMw04J1E+sYfVyAAAAABmGnRKon1jDSDcAAACADKP52aNGjbLOnTvb4cOHrX379pYjRw6bOHGiu8ydOzem9uFOivrJfpjTDQAAACBDJSQkuAXT7r77bsufP7/lzZvXBd5vvvlmzM3hTgn1k70QdAMAAACICnZKoH5iAUE3AAAAAAABid3JEgAAAAAABIygGwAAAACAgBB0AwAAAAAQEIJuAAAAAAACQtANAAAAAEBACLoBAAAAAAgIQTcAAAAAAAEh6AYAAAAAICAE3QAAAAAABISgGwCATOrvv/+27t2725lnnml58uSx8uXLW8uWLe2LL76IdtEAAEAa5UzrAwEAQMZZu3atNWjQwIoUKWJPP/201ahRww4fPmyffvqpdevWzX777bdM83EcPXrU4uLiLD6ec/kAACTFX0cAADKhrl27ukD2v//9r11//fV29tlnW7Vq1axnz542b94895gRI0a4YDx//vxuFFy/s2fPntBzTJw40QXtM2fOtHPOOcdOOeUUa9Omje3bt88mTZpkp59+uhUtWtTuvfdeFzj7Dh48aL1797ayZcu6577gggts9uzZyZ73/ffft6pVq7pR+D/++MPmz59vV1xxhZ122mlWuHBha9SokS1cuDCDaw4AgMyFoBsAgExm27Zt9sknn7gRbQW9SSngFY0sP//88/bLL7+4IPrLL7+0vn37JnqsAmw9ZsqUKe45FTy3atXKPvroI3d57bXX7OWXX7Zp06aFfueee+6xuXPnut9ZsmSJ3XDDDdasWTNbuXJloud98sknbdy4ce71S5QoYbt377YOHTrYnDlz3ImBypUr21VXXeVuBwAgVsV5nudFuxAAAOD/0+i2RpdnzJjhAuS0UuDcuXNn27JlS2hE+vbbb7dVq1ZZpUqV3G26X4H2P//8YwUKFHC3KaDWqPeYMWPciLXmkOtnmTJlQs/dpEkTO//8823o0KGh5128eLHVqlUr1fIkJCS4EwRvvPGGXX311XzEAICYxJxuAAAymbSeD581a5YNGzbMze/etWuXHTlyxA4cOOBGoZVKLvrpB9xSsmRJF2D7Abd/26ZNm9z/ly5d6lLNlc4eTinnp556auh67ty5rWbNmokeo0D+oYcecqPpej49j8qiAB4AgFhF0A0AQCajtGzN5z7WYmlaaE2jx126dLEhQ4ZYsWLFXFr3HXfcYYcOHQoF3bly5Ur0e3relG7TqLRoTniOHDlswYIF7me48EA9X7587vfCKbV869at9txzz1nFihXdXO/69eu78gAAEKsIugEAyGQUQDdt2tRefPFFt8hZ0nndO3bscEGxAuXhw4eHVg2fOnXqSb92nTp13Ai1RqobNmwY0e9+99139tJLL7l53LJ+/fpQqjsAALGKhdQAAMiEFHAr+NU86unTp7tFzJYtW+YWRdPo8VlnneW2EHvhhRds9erVbp625mSfLKWV33rrrda+fXs3p3zNmjVujrnS2D/88MPjjtCrHCrnDz/84J5HI+IAAMQygm4AADIhLWam7bYuu+wy69Wrl1WvXt1tx/XFF1/Y6NGj3QJm2jJMK4jrvsmTJ7vAOD288sorLujW62qrseuuu85tB1ahQoVj/t748eNt+/btVrduXbvtttvcKL1WNQcAIJaxejkAAAAAAAFhpBsAAAAAgIAQdAMAAAAAEBCCbgAAAAAAAkLQDQAAAABAQAi6AQAAAAAICEE3AAAAAAABIegGAAAAACAgBN0AAAAAAASEoBsAAAAAgIAQdAMAAAAAEBCCbgAAAAAAAkLQDQAAAACABeP/AYLAL7seRwUoAAAAAElFTkSuQmCC", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Mean absolute focal length error:\n", " Refractive: 0.033%\n", " Non-refractive: 5.699%\n" ] } ], "source": [ "camera_names = sorted(scenario.intrinsics.keys(), key=lambda s: int(s.replace(\"cam\", \"\")))\n", "x = np.arange(len(camera_names))\n", "width = 0.35\n", "\n", "focal_refr = [errors_refr[cam][\"focal_length_error_pct\"] for cam in camera_names]\n", "focal_nonrefr = [errors_nonrefr[cam][\"focal_length_error_pct\"] for cam in camera_names]\n", "\n", "fig, ax = plt.subplots(figsize=(10, 5))\n", "ax.bar(x - width / 2, focal_refr, width, label=LABEL_REFRACTIVE, color=COLOR_REFRACTIVE)\n", "ax.bar(x + width / 2, focal_nonrefr, width, label=LABEL_NON_REFRACTIVE, color=COLOR_NON_REFRACTIVE)\n", "ax.set_xlabel(\"Camera\")\n", "ax.set_ylabel(\"Focal Length Error (%)\")\n", "ax.set_title(\"Focal Length Recovery Error vs Ground Truth\")\n", "ax.set_xticks(x)\n", "ax.set_xticklabels(camera_names, rotation=45, ha=\"right\")\n", "ax.axhline(0, color=\"black\", linewidth=0.5, linestyle=\"--\")\n", "ax.legend()\n", "ax.grid(axis=\"y\", alpha=0.3)\n", "plt.tight_layout()\n", "plt.show()\n", "plt.close()\n", "\n", "mean_focal_refr = np.mean([abs(e) for e in focal_refr])\n", "mean_focal_nonrefr = np.mean([abs(e) for e in focal_nonrefr])\n", "print(f\"Mean absolute focal length error:\")\n", "print(f\" Refractive: {mean_focal_refr:.3f}%\")\n", "print(f\" Non-refractive: {mean_focal_nonrefr:.3f}%\")" ] }, { "cell_type": "markdown", "id": "cell-exp1-z-heading", "metadata": {}, "source": [ "### Camera Z Position Recovery\n", "\n", "Along with focal length, the non-refractive model misplaces camera positions along\n", "the Z axis (depth). These two biases together produce a model that fits 2D projections\n", "but triangulates 3D positions incorrectly.\n", "\n", "Because the reference camera (cam0) is fixed at the world-frame origin during\n", "optimization, its raw Z error is always zero by construction. To reveal the\n", "systematic shift the model would have applied to the entire rig, we subtract\n", "the mean Z error of the free cameras from all cameras (mean-shift correction)." ] }, { "cell_type": "code", "execution_count": 7, "id": "cell-exp1-z-plot", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Mean absolute Z position error (mean-shift corrected):\n", " Refractive: 0.35 mm\n", " Non-refractive: 9.66 mm\n" ] } ], "source": [ "z_refr_raw = [errors_refr[cam][\"z_position_error_mm\"] for cam in camera_names]\n", "z_nonrefr_raw = [errors_nonrefr[cam][\"z_position_error_mm\"] for cam in camera_names]\n", "\n", "# The reference camera (cam0) is pinned at ground truth during optimization,\n", "# so its raw error is always 0. To reveal the systematic Z shift the model\n", "# would have applied to cam0, subtract the mean error of the free cameras\n", "# from all cameras. This gives each camera's estimated distance from its\n", "# true position, including the reference.\n", "ref_cam = camera_names[0]\n", "free_cams = camera_names[1:]\n", "\n", "mean_z_refr = np.mean([errors_refr[cam][\"z_position_error_mm\"] for cam in free_cams])\n", "mean_z_nonrefr = np.mean([errors_nonrefr[cam][\"z_position_error_mm\"] for cam in free_cams])\n", "\n", "z_refr = [v - mean_z_refr for v in z_refr_raw]\n", "z_nonrefr = [v - mean_z_nonrefr for v in z_nonrefr_raw]\n", "\n", "fig, ax = plt.subplots(figsize=(10, 5))\n", "ax.bar(x - width / 2, z_refr, width, label=LABEL_REFRACTIVE, color=COLOR_REFRACTIVE)\n", "ax.bar(x + width / 2, z_nonrefr, width, label=LABEL_NON_REFRACTIVE, color=COLOR_NON_REFRACTIVE)\n", "ax.set_xlabel(\"Camera\")\n", "ax.set_ylabel(\"Z Position Error (mm)\")\n", "ax.set_title(\"Camera Z Position Recovery Error (mean-shift corrected)\")\n", "ax.set_xticks(x)\n", "ax.set_xticklabels(camera_names, rotation=45, ha=\"right\")\n", "ax.axhline(0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", "ax.legend()\n", "ax.grid(axis=\"y\", alpha=0.3)\n", "plt.tight_layout()\n", "plt.show()\n", "plt.close()\n", "\n", "mean_z_refr_abs = np.mean([abs(e) for e in z_refr])\n", "mean_z_nonrefr_abs = np.mean([abs(e) for e in z_nonrefr])\n", "print(f\"Mean absolute Z position error (mean-shift corrected):\")\n", "print(f\" Refractive: {mean_z_refr_abs:.2f} mm\")\n", "print(f\" Non-refractive: {mean_z_nonrefr_abs:.2f} mm\")" ] }, { "cell_type": "markdown", "id": "cell-exp1-xy-heading", "metadata": {}, "source": [ "### Camera XY Position Recovery\n", "\n", "Top-down view of camera positions. Arrows show how far each estimated position\n", "is from ground truth. A good calibration produces very short arrows." ] }, { "cell_type": "code", "execution_count": 8, "id": "cell-exp1-xy-plot", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Mean XY position error:\n", " Refractive: 0.47 mm\n", " Non-refractive: 4.94 mm\n" ] } ], "source": [ "fig, ax = plt.subplots(figsize=(8, 8))\n", "\n", "for i, cam_name in enumerate(camera_names):\n", " C_gt = scenario.extrinsics[cam_name].C\n", " C_refr = result_refr.cameras[cam_name].extrinsics.C\n", " C_nonrefr = result_nonrefr.cameras[cam_name].extrinsics.C\n", "\n", " gt_label = \"Ground Truth\" if i == 0 else None\n", " refr_label = LABEL_REFRACTIVE if i == 0 else None\n", " nonrefr_label = LABEL_NON_REFRACTIVE if i == 0 else None\n", "\n", " ax.scatter(C_gt[0], C_gt[1], color=\"black\", s=120, zorder=3, label=gt_label, marker=\"o\")\n", " ax.scatter(C_refr[0], C_refr[1], color=COLOR_REFRACTIVE, s=60, zorder=4, label=refr_label, alpha=0.8)\n", " ax.scatter(C_nonrefr[0], C_nonrefr[1], color=COLOR_NON_REFRACTIVE, s=60, zorder=4, label=nonrefr_label, alpha=0.8)\n", "\n", " dx_refr = C_refr[0] - C_gt[0]\n", " dy_refr = C_refr[1] - C_gt[1]\n", " dx_nonrefr = C_nonrefr[0] - C_gt[0]\n", " dy_nonrefr = C_nonrefr[1] - C_gt[1]\n", "\n", " arrow_kw = dict(head_width=0.015, head_length=0.008, length_includes_head=True)\n", " ax.arrow(C_gt[0], C_gt[1], dx_refr, dy_refr, color=COLOR_REFRACTIVE, alpha=0.6, **arrow_kw)\n", " ax.arrow(C_gt[0], C_gt[1], dx_nonrefr, dy_nonrefr, color=COLOR_NON_REFRACTIVE, alpha=0.6, **arrow_kw)\n", "\n", "ax.set_xlabel(\"X Position (m)\")\n", "ax.set_ylabel(\"Y Position (m)\")\n", "ax.set_title(\"Camera XY Position Recovery (arrows = estimation error)\")\n", "ax.set_aspect(\"equal\")\n", "ax.legend()\n", "ax.grid(alpha=0.3)\n", "plt.tight_layout()\n", "plt.show()\n", "plt.close()\n", "\n", "mean_xy_refr = np.mean([errors_refr[cam][\"xy_position_error_mm\"] for cam in camera_names])\n", "mean_xy_nonrefr = np.mean([errors_nonrefr[cam][\"xy_position_error_mm\"] for cam in camera_names])\n", "print(f\"Mean XY position error:\")\n", "print(f\" Refractive: {mean_xy_refr:.2f} mm\")\n", "print(f\" Non-refractive: {mean_xy_nonrefr:.2f} mm\")" ] }, { "cell_type": "markdown", "id": "cell-exp1-takeaway", "metadata": {}, "source": [ "### Experiment 1 Takeaway\n", "\n", "Both models achieve similar reprojection error — the 2D fitting quality looks the same.\n", "But the non-refractive model absorbs the refraction effect into systematically biased\n", "focal lengths and camera positions. The refractive model recovers the true physical\n", "parameters.\n", "\n", "**Why it matters:** Biased parameters produce systematic 3D reconstruction errors\n", "that grow with depth — exactly what Experiment 2 will show." ] }, { "cell_type": "markdown", "id": "cell-exp2-heading", "metadata": {}, "source": [ "## Experiment 2: Depth Generalization\n", "\n", "**Question:** How does 3D reconstruction accuracy vary with depth for each model?\n", "\n", "Real underwater surveys rarely stay at exactly the calibration depth. Fish tracking\n", "systems follow animals at varying depths; coral surveys cover different depth strata.\n", "\n", "Using the same calibrations from Experiment 1, we evaluate 3D reconstruction accuracy\n", "at a range of individual test depths. The refractive model should perform consistently\n", "because it learned the correct geometry; the non-refractive model's biased parameters\n", "produce depth-dependent errors." ] }, { "cell_type": "code", "execution_count": 9, "id": "cell-exp2-setup", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "=== Experiment 2: Depth Generalization ===\n", "Using calibrations from Experiment 1\n", " Refractive RMS: 0.4984 px\n", " Non-refractive RMS: 1.3764 px\n", "Test depths: [1.1, 1.2, 1.3, 1.4, 1.5, 1.7, 2.0, 2.5]\n", "\n", "Evaluating at test depths...\n" ] } ], "source": [ "print(\"=== Experiment 2: Depth Generalization ===\")\n", "print(f\"Using calibrations from Experiment 1\")\n", "print(f\" Refractive RMS: {result_refr.diagnostics.reprojection_error_rms:.4f} px\")\n", "print(f\" Non-refractive RMS: {result_nonrefr.diagnostics.reprojection_error_rms:.4f} px\")\n", "print(f\"Test depths: {TEST_DEPTHS}\")\n", "\n", "board_exp2 = BoardGeometry(scenario.board_config)\n", "print(\"\\nEvaluating at test depths...\")" ] }, { "cell_type": "code", "execution_count": 10, "id": "cell-exp2-depth-sweep", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Evaluating Z = 1.10 m...\n", " Evaluating Z = 1.20 m...\n", " Evaluating Z = 1.30 m...\n", " Evaluating Z = 1.40 m...\n", " Evaluating Z = 1.50 m...\n", " Evaluating Z = 1.70 m...\n", " Evaluating Z = 2.00 m...\n", " Evaluating Z = 2.50 m...\n", "Depth sweep complete.\n" ] } ], "source": [ "results_refr_exp2 = []\n", "results_nonrefr_exp2 = []\n", "# Save intermediates for Experiment 3 (XY vs Z anisotropy)\n", "exp2_test_poses = []\n", "exp2_test_detections = []\n", "\n", "for depth in TEST_DEPTHS:\n", " print(f\" Evaluating Z = {depth:.2f} m...\")\n", "\n", " test_poses = generate_dense_xy_grid(\n", " depth=depth,\n", " n_grid=N_GRID,\n", " xy_extent=XY_EXTENT,\n", " xy_center=XY_CENTER,\n", " tilt_deg=TILT_DEG,\n", " frame_offset=1000,\n", " seed=42 + int(depth * 100),\n", " )\n", "\n", " test_detections = generate_synthetic_detections(\n", " intrinsics=scenario.intrinsics,\n", " extrinsics=scenario.extrinsics,\n", " water_zs=scenario.water_zs,\n", " board=board_exp2,\n", " board_poses=test_poses,\n", " noise_std=scenario.noise_std,\n", " seed=42 + int(depth * 100),\n", " )\n", "\n", " exp2_test_poses.append(test_poses)\n", " exp2_test_detections.append(test_detections)\n", "\n", " err_refr = evaluate_reconstruction(result_refr, board_exp2, test_detections)\n", " err_nonrefr = evaluate_reconstruction(result_nonrefr, board_exp2, test_detections)\n", "\n", " # Reprojection error at this test depth using GT board poses\n", " test_poses_dict = {bp.frame_idx: bp for bp in test_poses}\n", " reproj_refr = compute_reprojection_errors(result_refr, test_detections, test_poses_dict)\n", " reproj_nonrefr = compute_reprojection_errors(result_nonrefr, test_detections, test_poses_dict)\n", "\n", " true_dist = scenario.board_config.square_size\n", " scale_refr = 1.0 + (err_refr.signed_mean / true_dist)\n", " scale_nonrefr = 1.0 + (err_nonrefr.signed_mean / true_dist)\n", "\n", " results_refr_exp2.append({\n", " \"depth\": depth,\n", " \"signed_mean_mm\": err_refr.signed_mean * 1000,\n", " \"rmse_mm\": err_refr.rmse * 1000,\n", " \"scale\": scale_refr,\n", " \"reproj_rms_px\": reproj_refr.rms,\n", " \"spatial\": err_refr.spatial,\n", " })\n", " results_nonrefr_exp2.append({\n", " \"depth\": depth,\n", " \"signed_mean_mm\": err_nonrefr.signed_mean * 1000,\n", " \"rmse_mm\": err_nonrefr.rmse * 1000,\n", " \"scale\": scale_nonrefr,\n", " \"reproj_rms_px\": reproj_nonrefr.rms,\n", " \"spatial\": err_nonrefr.spatial,\n", " })\n", "\n", "print(\"Depth sweep complete.\")" ] }, { "cell_type": "markdown", "id": "cell-exp2-plots-heading", "metadata": {}, "source": [ "### Signed Error vs Depth\n", "\n", "The shaded region marks the calibration depth range. The refractive model maintains\n", "low, uniform error at all depths. The non-refractive model shows systematic\n", "depth-dependent bias because its wrong geometry produces scale errors that grow\n", "with distance from the water surface." ] }, { "cell_type": "code", "execution_count": 11, "id": "cell-exp2-signed-error-plot", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "depths_plot = [r[\"depth\"] for r in results_refr_exp2]\n", "signed_refr = [r[\"signed_mean_mm\"] for r in results_refr_exp2]\n", "signed_nonrefr = [r[\"signed_mean_mm\"] for r in results_nonrefr_exp2]\n", "\n", "fig, ax = plt.subplots(figsize=(9, 5))\n", "ax.axvspan(CALIB_DEPTH_RANGE[0], CALIB_DEPTH_RANGE[1], alpha=0.15, color=\"gray\", label=\"Calibration Range\")\n", "ax.plot(depths_plot, signed_refr, marker=\"o\", color=COLOR_REFRACTIVE, label=LABEL_REFRACTIVE, linewidth=2)\n", "ax.plot(depths_plot, signed_nonrefr, marker=\"s\", color=COLOR_NON_REFRACTIVE, label=LABEL_NON_REFRACTIVE, linewidth=2)\n", "ax.axhline(0, color=\"black\", linewidth=0.8, linestyle=\"--\")\n", "ax.set_xlabel(\"Test Depth (m)\")\n", "ax.set_ylabel(\"Signed Mean Error (mm)\")\n", "ax.set_title(\"Signed Error vs Test Depth\")\n", "ax.legend()\n", "ax.grid(alpha=0.3)\n", "plt.tight_layout()\n", "plt.show()\n", "plt.close()" ] }, { "cell_type": "code", "execution_count": 12, "id": "cell-exp2-rmse-plot", "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Maximum RMSE across all test depths:\n", " Refractive: 0.42 mm\n", " Non-refractive: 0.95 mm\n" ] } ], "source": [ "rmse_refr = [r[\"rmse_mm\"] for r in results_refr_exp2]\n", "rmse_nonrefr = [r[\"rmse_mm\"] for r in results_nonrefr_exp2]\n", "\n", "fig, ax = plt.subplots(figsize=(9, 5))\n", "ax.axvspan(CALIB_DEPTH_RANGE[0], CALIB_DEPTH_RANGE[1], alpha=0.15, color=\"gray\", label=\"Calibration Range\")\n", "ax.plot(depths_plot, rmse_refr, marker=\"o\", color=COLOR_REFRACTIVE, label=LABEL_REFRACTIVE, linewidth=2)\n", "ax.plot(depths_plot, rmse_nonrefr, marker=\"s\", color=COLOR_NON_REFRACTIVE, label=LABEL_NON_REFRACTIVE, linewidth=2)\n", "ax.set_xlabel(\"Test Depth (m)\")\n", "ax.set_ylabel(\"Reconstruction RMSE (mm)\")\n", "ax.set_title(\"Reconstruction RMSE vs Test Depth\")\n", "ax.legend()\n", "ax.grid(alpha=0.3)\n", "plt.tight_layout()\n", "plt.show()\n", "plt.close()\n", "\n", "max_rmse_refr = max(rmse_refr)\n", "max_rmse_nonrefr = max(rmse_nonrefr)\n", "print(f\"Maximum RMSE across all test depths:\")\n", "print(f\" Refractive: {max_rmse_refr:.2f} mm\")\n", "print(f\" Non-refractive: {max_rmse_nonrefr:.2f} mm\")" ] }, { "cell_type": "markdown", "id": "esyuoifefbv", "metadata": {}, "source": [ "### Reprojection Error vs Depth\n", "\n", "Reprojection error measures how well the calibrated model explains the 2D observations\n", "at each test depth using the ground-truth board poses. Unlike 3D reconstruction error,\n", "this is a purely 2D metric — but it still degrades for the non-refractive model\n", "because refraction bends rays by a depth-dependent amount that a fixed pinhole model\n", "cannot accommodate." ] }, { "cell_type": "code", "execution_count": 13, "id": "xy0s3tjfra7", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "reproj_refr = [r[\"reproj_rms_px\"] for r in results_refr_exp2]\n", "reproj_nonrefr = [r[\"reproj_rms_px\"] for r in results_nonrefr_exp2]\n", "\n", "fig, ax = plt.subplots(figsize=(9, 5))\n", "ax.axvspan(CALIB_DEPTH_RANGE[0], CALIB_DEPTH_RANGE[1], alpha=0.15, color=\"gray\", label=\"Calibration Range\")\n", "ax.plot(depths_plot, reproj_refr, marker=\"o\", color=COLOR_REFRACTIVE, label=LABEL_REFRACTIVE, linewidth=2)\n", "ax.plot(depths_plot, reproj_nonrefr, marker=\"s\", color=COLOR_NON_REFRACTIVE, label=LABEL_NON_REFRACTIVE, linewidth=2)\n", "ax.set_xlabel(\"Test Depth (m)\")\n", "ax.set_ylabel(\"Reprojection RMS (px)\")\n", "ax.set_title(\"Reprojection Error vs Test Depth (using GT board poses)\")\n", "ax.legend()\n", "ax.grid(alpha=0.3)\n", "plt.tight_layout()\n", "plt.show()\n", "plt.close()" ] }, { "cell_type": "markdown", "id": "n83xeuvbm2k", "metadata": {}, "source": [ "### Spatial Error Distribution\n", "\n", "Are reconstruction errors uniform across the field of view, or concentrated in\n", "certain regions? The heatmaps below show mean signed reconstruction error binned\n", "by XY position for the shallowest and deepest test depths.\n", "\n", "The non-refractive model's error is not only larger but spatially structured — it\n", "varies across the field of view because refraction angle depends on the incidence\n", "geometry, which a fixed pinhole distortion model cannot capture." ] }, { "cell_type": "code", "execution_count": 14, "id": "o1uyl9tnnmg", "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Pick shallowest and deepest test depths for comparison\n", "depth_indices = [0, len(TEST_DEPTHS) - 1]\n", "depth_labels = [\"Shallowest\", \"Deepest\"]\n", "\n", "fig, axes = plt.subplots(len(depth_indices), 2, figsize=(14, 6 * len(depth_indices)))\n", "\n", "# Compute shared color scale across all panels\n", "all_errors_mm = []\n", "for di in depth_indices:\n", " for results in [results_refr_exp2, results_nonrefr_exp2]:\n", " sp = results[di][\"spatial\"]\n", " if sp is not None:\n", " all_errors_mm.extend((sp.signed_errors * 1000).tolist())\n", "if all_errors_mm:\n", " vmax = max(abs(min(all_errors_mm)), abs(max(all_errors_mm)))\n", "else:\n", " vmax = 1.0\n", "\n", "# Hexbin gridsize: use equal x-y bin widths. The data spans ~2*XY_EXTENT in\n", "# both X and Y. A gridsize of 25 gives bins of roughly 40 mm width, which is\n", "# fine enough to show spatial structure without being too noisy.\n", "HEXBIN_GRIDSIZE = 25\n", "\n", "for row, (di, dlabel) in enumerate(zip(depth_indices, depth_labels)):\n", " depth_val = TEST_DEPTHS[di]\n", " for col, (results, model_label) in enumerate([\n", " (results_refr_exp2, \"Refractive\"),\n", " (results_nonrefr_exp2, \"Non-refractive\"),\n", " ]):\n", " ax = axes[row, col]\n", " sp = results[di][\"spatial\"]\n", " if sp is not None and len(sp.signed_errors) > 0:\n", " hb = ax.hexbin(\n", " sp.positions[:, 0], sp.positions[:, 1],\n", " C=sp.signed_errors * 1000,\n", " reduce_C_function=np.mean,\n", " gridsize=HEXBIN_GRIDSIZE,\n", " cmap=\"RdBu_r\", vmin=-vmax, vmax=vmax,\n", " mincnt=1,\n", " )\n", " plt.colorbar(hb, ax=ax, label=\"Mean Signed Error (mm)\")\n", " ax.set_xlabel(\"X (m)\")\n", " ax.set_ylabel(\"Y (m)\")\n", " ax.set_title(f\"{model_label} — {dlabel} ({depth_val:.2f} m)\")\n", " ax.set_aspect(\"equal\")\n", " ax.grid(alpha=0.3)\n", "\n", "plt.tight_layout()\n", "plt.show()\n", "plt.close()" ] }, { "cell_type": "code", "execution_count": 15, "id": "cell-exp2-scale-plot", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "scale_refr = [r[\"scale\"] for r in results_refr_exp2]\n", "scale_nonrefr = [r[\"scale\"] for r in results_nonrefr_exp2]\n", "\n", "fig, ax = plt.subplots(figsize=(9, 5))\n", "ax.axvspan(CALIB_DEPTH_RANGE[0], CALIB_DEPTH_RANGE[1], alpha=0.15, color=\"gray\", label=\"Calibration Range\")\n", "ax.plot(depths_plot, scale_refr, marker=\"o\", color=COLOR_REFRACTIVE, label=LABEL_REFRACTIVE, linewidth=2)\n", "ax.plot(depths_plot, scale_nonrefr, marker=\"s\", color=COLOR_NON_REFRACTIVE, label=LABEL_NON_REFRACTIVE, linewidth=2)\n", "ax.axhline(1.0, color=\"black\", linewidth=0.8, linestyle=\"--\", label=\"True scale (1.0)\")\n", "ax.set_xlabel(\"Test Depth (m)\")\n", "ax.set_ylabel(\"Scale Factor (measured / true)\")\n", "ax.set_title(\"Scale Factor vs Test Depth\")\n", "ax.legend()\n", "ax.grid(alpha=0.3)\n", "plt.tight_layout()\n", "plt.show()\n", "plt.close()" ] }, { "cell_type": "markdown", "id": "cell-exp2-takeaway", "metadata": {}, "source": [ "### Experiment 2 Takeaway\n", "\n", "The refractive model's error stays low and uniform across all test depths — it learned\n", "the actual geometry and produces consistent 3D measurements regardless of depth. The\n", "non-refractive model's error grows with depth because its biased focal lengths and\n", "camera positions produce scale distortions that worsen as targets move further from\n", "the cameras.\n", "\n", "This is particularly important for applications where the measurement depth varies:\n", "animal tracking, reef surveys, or any scenario where targets move in depth." ] }, { "cell_type": "markdown", "id": "786e1hog66", "metadata": {}, "source": [ "## Experiment 3: XY vs Z Precision Anisotropy\n", "\n", "**Question:** Is reconstruction precision uniform in all directions, or does the\n", "camera geometry create a preferred axis?\n", "\n", "When all cameras look straight down (optical axes parallel to Z), they have wide\n", "angular separation in XY — each camera views the same target from a different lateral\n", "position. But along Z (depth), all viewing angles are nearly identical. This creates\n", "**anisotropic triangulation geometry**: the system resolves XY position far more\n", "precisely than Z.\n", "\n", "This geometric anisotropy affects both models, but the non-refractive model adds\n", "systematic Z bias from its wrong parameters on top. Using the same test data from\n", "Experiment 2, we decompose triangulation error into lateral (XY) and depth (Z)\n", "components to quantify both effects." ] }, { "cell_type": "code", "execution_count": null, "id": "jq300wte3tn", "metadata": {}, "outputs": [], "source": "print(\"=== Experiment 3: XY vs Z Precision Anisotropy ===\")\nprint(\"Reusing test data from Experiment 2\\n\")\n\n# For each test depth, triangulate corners and compare to ground truth positions.\n# Decompose the 3D position error into XY (lateral) and Z (depth) components.\n\ndef compute_xyz_errors(calibration, test_poses, test_detections, board):\n \"\"\"Triangulate corners, compare to GT, return per-depth XY/Z error arrays.\"\"\"\n results = []\n poses_by_frame = {bp.frame_idx: bp for bp in test_poses}\n\n xy_errors = []\n z_errors = []\n signed_z_errors = []\n\n for frame_idx in test_detections.frames:\n tri_corners = triangulate_charuco_corners(calibration, test_detections, frame_idx)\n if not tri_corners:\n continue\n\n bp = poses_by_frame[frame_idx]\n R_board, _ = cv2.Rodrigues(bp.rvec)\n\n for corner_id, tri_pos in tri_corners.items():\n if corner_id not in board.corner_positions:\n continue\n p_board = board.corner_positions[corner_id]\n p_gt = R_board @ p_board + bp.tvec\n\n err = tri_pos - p_gt\n xy_errors.append(np.linalg.norm(err[:2]))\n z_errors.append(abs(err[2]))\n signed_z_errors.append(err[2])\n\n xy_arr = np.array(xy_errors)\n z_arr = np.array(z_errors)\n signed_z_arr = np.array(signed_z_errors)\n xy_rmse = np.sqrt(np.mean(xy_arr**2))\n z_rmse = np.sqrt(np.mean(z_arr**2))\n ratio = z_rmse / xy_rmse if xy_rmse > 0 else float(\"inf\")\n\n return {\n \"xy_rmse_mm\": xy_rmse * 1000,\n \"z_rmse_mm\": z_rmse * 1000,\n \"xy_mean_signed_mm\": np.mean(xy_arr) * 1000,\n \"z_mean_signed_mm\": np.mean(signed_z_arr) * 1000,\n \"ratio\": ratio,\n \"xy_errors_mm\": xy_arr * 1000,\n \"z_errors_mm\": z_arr * 1000,\n \"n_points\": len(xy_errors),\n }\n\n\nexp3_refr = []\nexp3_nonrefr = []\n\nfor i, depth in enumerate(TEST_DEPTHS):\n test_poses = exp2_test_poses[i]\n test_detections = exp2_test_detections[i]\n\n r_refr = compute_xyz_errors(result_refr, test_poses, test_detections, board_exp2)\n r_nonrefr = compute_xyz_errors(result_nonrefr, test_poses, test_detections, board_exp2)\n r_refr[\"depth\"] = depth\n r_nonrefr[\"depth\"] = depth\n exp3_refr.append(r_refr)\n exp3_nonrefr.append(r_nonrefr)\n\n print(f\" Z = {depth:.2f} m:\")\n print(f\" Refractive: XY = {r_refr['xy_rmse_mm']:.3f} mm, \"\n f\"Z = {r_refr['z_rmse_mm']:.3f} mm, ratio = {r_refr['ratio']:.1f}x\")\n print(f\" Non-refractive: XY = {r_nonrefr['xy_rmse_mm']:.3f} mm, \"\n f\"Z = {r_nonrefr['z_rmse_mm']:.3f} mm, ratio = {r_nonrefr['ratio']:.1f}x\")\n\nprint(\"\\nAnisotropy analysis complete.\")" }, { "cell_type": "markdown", "id": "za4sw19u32", "metadata": {}, "source": [ "### XY vs Z RMSE across Depth\n", "\n", "The grouped bar chart below compares lateral (XY) and depth (Z) reconstruction RMSE\n", "for both models at each test depth. The refractive model shows the baseline geometric\n", "anisotropy; the non-refractive model amplifies it with systematic Z bias from its\n", "wrong parameters." ] }, { "cell_type": "code", "execution_count": 17, "id": "k8b55kn4xc8", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "depths_exp3 = [r[\"depth\"] for r in exp3_refr]\n", "x_pos = np.arange(len(depths_exp3))\n", "w = 0.2 # bar width\n", "\n", "fig, ax = plt.subplots(figsize=(12, 5))\n", "ax.bar(x_pos - 1.5 * w, [r[\"xy_rmse_mm\"] for r in exp3_refr], w,\n", " label=\"Refractive XY\", color=COLOR_REFRACTIVE, alpha=0.7)\n", "ax.bar(x_pos - 0.5 * w, [r[\"z_rmse_mm\"] for r in exp3_refr], w,\n", " label=\"Refractive Z\", color=COLOR_REFRACTIVE)\n", "ax.bar(x_pos + 0.5 * w, [r[\"xy_rmse_mm\"] for r in exp3_nonrefr], w,\n", " label=\"Non-refractive XY\", color=COLOR_NON_REFRACTIVE, alpha=0.7)\n", "ax.bar(x_pos + 1.5 * w, [r[\"z_rmse_mm\"] for r in exp3_nonrefr], w,\n", " label=\"Non-refractive Z\", color=COLOR_NON_REFRACTIVE)\n", "ax.set_xlabel(\"Test Depth (m)\")\n", "ax.set_ylabel(\"RMSE (mm)\")\n", "ax.set_title(\"Reconstruction RMSE by Component\")\n", "ax.set_xticks(x_pos)\n", "ax.set_xticklabels([f\"{d:.2f}\" for d in depths_exp3])\n", "ax.legend(ncol=2)\n", "ax.grid(axis=\"y\", alpha=0.3)\n", "plt.tight_layout()\n", "plt.show()\n", "plt.close()" ] }, { "cell_type": "markdown", "id": "nrfoe2awvrj", "metadata": {}, "source": [ "### Anisotropy Ratio vs Depth\n", "\n", "The ratio Z_RMSE / XY_RMSE quantifies how many times worse depth precision is\n", "compared to lateral precision. A ratio of 1 would indicate isotropic precision;\n", "higher values indicate a \"cigar-shaped\" error distribution elongated along Z.\n", "\n", "Both models show anisotropy from the rig geometry, but the non-refractive model's\n", "ratio is higher because its systematic Z bias adds to the geometric limitation." ] }, { "cell_type": "code", "execution_count": 18, "id": "hcier5addmj", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Anisotropy ratio (refractive): 2.1x – 2.5x (mean 2.3x)\n", "Anisotropy ratio (non-refractive): 0.4x – 5.8x (mean 2.3x)\n" ] } ], "source": [ "ratios_refr = [r[\"ratio\"] for r in exp3_refr]\n", "ratios_nonrefr = [r[\"ratio\"] for r in exp3_nonrefr]\n", "\n", "fig, ax = plt.subplots(figsize=(9, 5))\n", "ax.axvspan(CALIB_DEPTH_RANGE[0], CALIB_DEPTH_RANGE[1], alpha=0.15, color=\"gray\", label=\"Calibration Range\")\n", "ax.plot(depths_exp3, ratios_refr, marker=\"o\", color=COLOR_REFRACTIVE,\n", " label=LABEL_REFRACTIVE, linewidth=2)\n", "ax.plot(depths_exp3, ratios_nonrefr, marker=\"s\", color=COLOR_NON_REFRACTIVE,\n", " label=LABEL_NON_REFRACTIVE, linewidth=2)\n", "ax.axhline(1.0, color=\"black\", linewidth=0.8, linestyle=\"--\", label=\"Isotropic (ratio = 1)\")\n", "ax.set_xlabel(\"Test Depth (m)\")\n", "ax.set_ylabel(\"Z RMSE / XY RMSE\")\n", "ax.set_title(\"Depth-to-Lateral Precision Ratio vs Test Depth\")\n", "ax.legend()\n", "ax.grid(alpha=0.3)\n", "plt.tight_layout()\n", "plt.show()\n", "plt.close()\n", "\n", "print(f\"Anisotropy ratio (refractive): {min(ratios_refr):.1f}x – {max(ratios_refr):.1f}x \"\n", " f\"(mean {np.mean(ratios_refr):.1f}x)\")\n", "print(f\"Anisotropy ratio (non-refractive): {min(ratios_nonrefr):.1f}x – {max(ratios_nonrefr):.1f}x \"\n", " f\"(mean {np.mean(ratios_nonrefr):.1f}x)\")" ] }, { "cell_type": "markdown", "id": "rcfmwkdjign", "metadata": {}, "source": [ "### Error Distribution: Shallowest vs Deepest\n", "\n", "Violin plots show the full distribution of per-point errors at the shallowest\n", "and deepest test depths for both models. The non-refractive model's Z distribution\n", "is dramatically wider — its systematic bias stacks on top of the geometric\n", "anisotropy that both models share." ] }, { "cell_type": "code", "execution_count": 19, "id": "uot6gtkn3st", "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Shallowest (1.10 m):\n", " Refractive — XY median: 0.667 mm, Z median: 1.293 mm\n", " Non-refractive — XY median: 24.034 mm, Z median: 48.312 mm\n", "Deepest (2.50 m):\n", " Refractive — XY median: 0.849 mm, Z median: 1.341 mm\n", " Non-refractive — XY median: 43.759 mm, Z median: 252.402 mm\n" ] } ], "source": [ "# 2x2 grid: rows = shallowest/deepest, cols = refractive/non-refractive\n", "shallow_refr, deep_refr = exp3_refr[0], exp3_refr[-1]\n", "shallow_nonrefr, deep_nonrefr = exp3_nonrefr[0], exp3_nonrefr[-1]\n", "\n", "fig, axes = plt.subplots(2, 2, figsize=(12, 9), sharey=True)\n", "\n", "panels = [\n", " (axes[0, 0], shallow_refr, f\"Refractive — {shallow_refr['depth']:.2f} m\"),\n", " (axes[0, 1], shallow_nonrefr, f\"Non-refractive — {shallow_nonrefr['depth']:.2f} m\"),\n", " (axes[1, 0], deep_refr, f\"Refractive — {deep_refr['depth']:.2f} m\"),\n", " (axes[1, 1], deep_nonrefr, f\"Non-refractive — {deep_nonrefr['depth']:.2f} m\"),\n", "]\n", "\n", "for ax, result, label in panels:\n", " data = [result[\"xy_errors_mm\"], result[\"z_errors_mm\"]]\n", " parts = ax.violinplot(data, positions=[0, 1], showmedians=True, showextrema=False)\n", "\n", " for pc, color in zip(parts[\"bodies\"], [\"#4CAF50\", \"#FF9800\"]):\n", " pc.set_facecolor(color)\n", " pc.set_alpha(0.7)\n", " parts[\"cmedians\"].set_color(\"black\")\n", "\n", " ax.set_xticks([0, 1])\n", " ax.set_xticklabels([\"XY Error\", \"Z Error\"])\n", " ax.set_title(label)\n", " ax.grid(axis=\"y\", alpha=0.3)\n", "\n", "axes[0, 0].set_ylabel(\"Absolute Error (mm)\")\n", "axes[1, 0].set_ylabel(\"Absolute Error (mm)\")\n", "fig.text(0.01, 0.73, \"Shallowest\", va=\"center\", rotation=\"vertical\", fontsize=12, fontweight=\"bold\")\n", "fig.text(0.01, 0.28, \"Deepest\", va=\"center\", rotation=\"vertical\", fontsize=12, fontweight=\"bold\")\n", "fig.suptitle(\"Per-Point Error Distributions\", fontsize=13, y=1.01)\n", "plt.tight_layout()\n", "plt.show()\n", "plt.close()\n", "\n", "print(f\"Shallowest ({shallow_refr['depth']:.2f} m):\")\n", "print(f\" Refractive — XY median: {np.median(shallow_refr['xy_errors_mm']):.3f} mm, \"\n", " f\"Z median: {np.median(shallow_refr['z_errors_mm']):.3f} mm\")\n", "print(f\" Non-refractive — XY median: {np.median(shallow_nonrefr['xy_errors_mm']):.3f} mm, \"\n", " f\"Z median: {np.median(shallow_nonrefr['z_errors_mm']):.3f} mm\")\n", "print(f\"Deepest ({deep_refr['depth']:.2f} m):\")\n", "print(f\" Refractive — XY median: {np.median(deep_refr['xy_errors_mm']):.3f} mm, \"\n", " f\"Z median: {np.median(deep_refr['z_errors_mm']):.3f} mm\")\n", "print(f\" Non-refractive — XY median: {np.median(deep_nonrefr['xy_errors_mm']):.3f} mm, \"\n", " f\"Z median: {np.median(deep_nonrefr['z_errors_mm']):.3f} mm\")" ] }, { "cell_type": "markdown", "id": "fhfl0pbqik", "metadata": {}, "source": [ "### Experiment 3 Takeaway\n", "\n", "Reconstruction precision is highly anisotropic: Z (depth) errors are consistently\n", "larger than XY (lateral) errors for both models. The refractive model shows the\n", "**baseline geometric anisotropy** — an inherent consequence of the downward-looking\n", "camera arrangement where all cameras share a similar viewing angle along Z. The\n", "non-refractive model makes it worse: its systematic parameter bias amplifies Z\n", "error while leaving XY relatively unchanged, producing even higher anisotropy ratios.\n", "\n", "**Practical implications:**\n", "- **XY tracking** (e.g. horizontal position of fish) is inherently precise with\n", " either model\n", "- **Depth estimation** (Z) is the limiting factor — and the non-refractive model\n", " makes it substantially worse\n", "- Applications that only need 2D plan-view tracking can expect significantly\n", " better precision than the overall 3D RMSE suggests\n", "- For depth-critical applications, use the refractive model *and* consider adding\n", " cameras at oblique angles to improve Z triangulation geometry" ] }, { "cell_type": "markdown", "id": "01fqoaepwpeo", "metadata": {}, "source": [ "### Exported Data\n", "\n", "The CSVs below capture the per-record data behind all plots in this notebook,\n", "so downstream consumers can reproduce statistics and figures without running AquaCal." ] }, { "cell_type": "code", "execution_count": null, "id": "e3jl81minof", "metadata": {}, "outputs": [], "source": "# --- Exp1: per-camera parameter errors ---\n# Compute mean Z shift of free cameras for mean-shift correction\n_free = [c for c in camera_names if c != camera_names[0]]\n_mz = {\n \"refractive\": np.mean([errors_refr[c][\"z_position_error_mm\"] for c in _free]),\n \"non_refractive\": np.mean([errors_nonrefr[c][\"z_position_error_mm\"] for c in _free]),\n}\n\nrows_exp1 = []\nfor cam in camera_names:\n for label, errors, result in [\n (\"refractive\", errors_refr, result_refr),\n (\"non_refractive\", errors_nonrefr, result_nonrefr),\n ]:\n C_gt = scenario.extrinsics[cam].C\n C_est = result.cameras[cam].extrinsics.C\n rows_exp1.append({\n \"camera\": cam,\n \"model\": label,\n \"focal_length_error_pct\": errors[cam][\"focal_length_error_pct\"],\n \"z_position_error_mm\": errors[cam][\"z_position_error_mm\"] - _mz[label],\n \"xy_position_error_mm\": errors[cam][\"xy_position_error_mm\"],\n \"gt_x_m\": C_gt[0], \"gt_y_m\": C_gt[1], \"gt_z_m\": C_gt[2],\n \"est_x_m\": C_est[0], \"est_y_m\": C_est[1], \"est_z_m\": C_est[2],\n \"reprojection_rms_px\": result.diagnostics.reprojection_error_rms,\n })\ndf_exp1 = pd.DataFrame(rows_exp1)\n\n# --- Exp2: depth-generalization metrics ---\nrows_exp2 = []\nfor r_refr, r_nonrefr in zip(results_refr_exp2, results_nonrefr_exp2):\n for label, r in [(\"refractive\", r_refr), (\"non_refractive\", r_nonrefr)]:\n rows_exp2.append({\n \"test_depth_m\": r[\"depth\"],\n \"model\": label,\n \"signed_mean_mm\": r[\"signed_mean_mm\"],\n \"rmse_mm\": r[\"rmse_mm\"],\n \"scale_factor\": r[\"scale\"],\n \"calib_depth_min_m\": CALIB_DEPTH_RANGE[0],\n \"calib_depth_max_m\": CALIB_DEPTH_RANGE[1],\n })\ndf_exp2 = pd.DataFrame(rows_exp2)\n\n# --- Exp2: spatial error distribution (positions + signed errors per depth) ---\nrows_spatial = []\nfor r_refr, r_nonrefr in zip(results_refr_exp2, results_nonrefr_exp2):\n for label, r in [(\"refractive\", r_refr), (\"non_refractive\", r_nonrefr)]:\n sp = r[\"spatial\"]\n if sp is not None and len(sp.signed_errors) > 0:\n for i in range(len(sp.signed_errors)):\n rows_spatial.append({\n \"test_depth_m\": r[\"depth\"],\n \"model\": label,\n \"x_m\": sp.positions[i, 0],\n \"y_m\": sp.positions[i, 1],\n \"z_m\": sp.positions[i, 2],\n \"signed_error_mm\": sp.signed_errors[i] * 1000,\n })\ndf_spatial = pd.DataFrame(rows_spatial)\n\n# --- Exp3: XY vs Z anisotropy ---\nrows_exp3 = []\nfor r_refr, r_nonrefr in zip(exp3_refr, exp3_nonrefr):\n for label, r in [(\"refractive\", r_refr), (\"non_refractive\", r_nonrefr)]:\n rows_exp3.append({\n \"test_depth_m\": r[\"depth\"],\n \"model\": label,\n \"xy_rmse_mm\": r[\"xy_rmse_mm\"],\n \"z_rmse_mm\": r[\"z_rmse_mm\"],\n \"xy_mean_signed_mm\": r[\"xy_mean_signed_mm\"],\n \"z_mean_signed_mm\": r[\"z_mean_signed_mm\"],\n \"anisotropy_ratio\": r[\"ratio\"],\n \"n_points\": r[\"n_points\"],\n })\ndf_exp3 = pd.DataFrame(rows_exp3)\n\n# --- Write CSVs ---\nOUTPUT_DIR.mkdir(parents=True, exist_ok=True)\npath_exp1 = OUTPUT_DIR / \"exp1_parameter_errors.csv\"\npath_exp2 = OUTPUT_DIR / \"exp2_depth_generalization.csv\"\npath_spatial = OUTPUT_DIR / \"exp2_spatial_errors.csv\"\npath_exp3 = OUTPUT_DIR / \"exp3_xy_vs_z_anisotropy.csv\"\ndf_exp1.to_csv(path_exp1, index=False)\ndf_exp2.to_csv(path_exp2, index=False)\ndf_spatial.to_csv(path_spatial, index=False)\ndf_exp3.to_csv(path_exp3, index=False)\n\nprint(f\"Wrote {path_exp1} ({len(df_exp1)} rows)\")\nprint(f\"Wrote {path_exp2} ({len(df_exp2)} rows)\")\nprint(f\"Wrote {path_spatial} ({len(df_spatial)} rows)\")\nprint(f\"Wrote {path_exp3} ({len(df_exp3)} rows)\")" }, { "cell_type": "markdown", "id": "cell-summary-heading", "metadata": {}, "source": [ "## Summary\n", "\n", "Three experiments, one calibration:\n", "\n", "| Experiment | What we tested | Key finding |\n", "|------------|---------------|-------------|\n", "| 1 — Parameter Fidelity | Same data, two models | Non-refractive absorbs refraction into focal length and position bias |\n", "| 2 — Depth Generalization | Same calibration, sweep test depth | Non-refractive error grows with depth; refractive stays flat |\n", "| 3 — XY vs Z Anisotropy | Decompose error by direction | Z error dominates XY for both models; non-refractive amplifies the gap |\n", "\n", "**When is refractive calibration essential?**\n", "- Camera-to-water distance is significant (>= 0.3 m)\n", "- Measurement depth varies across sessions or within a session\n", "- High 3D accuracy is required (< 5 mm)\n", "- You need stable calibration across depth ranges\n", "\n", "**When might pinhole be acceptable?**\n", "- Cameras are very close to the water surface (< 0.1 m)\n", "- Only 2D detection or tracking is needed (no 3D reconstruction)\n", "- Accuracy requirements are very relaxed (> 20 mm)\n", "- Data collection depth is constant and pre-known\n", "\n", "---\n", "\n", "**Further reading:**\n", "- [Full pipeline tutorial](01_full_pipeline.ipynb) — calibrate a rig end-to-end\n", "- [Theory documentation](../guide/refractive_geometry.md) — refractive geometry model and Snell's law derivation\n", "- [Optimizer guide](../guide/optimizer.md) — tuning the Stage 3 bundle adjustment" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.12.12" } }, "nbformat": 4, "nbformat_minor": 5 }