[
  {
    "path": ".github/workflows/clean_gitkeep.yml",
    "content": "name: Clean unnecessary .gitkeep files\n\non:\n  push:\n    branches:\n      - main\n      - master\n\njobs:\n  clean:\n    runs-on: ubuntu-latest\n\n    steps:\n      - name: Checkout repository\n        uses: actions/checkout@v3\n\n      - name: Remove unnecessary .gitkeep files\n        run: |\n          find . -name '.gitkeep' -print0 | while IFS= read -r -d '' file; do\n            dir=$(dirname \"$file\")\n            if [ \"$(ls -A \"$dir\" | wc -l)\" -gt \"1\" ]; then\n              echo \"Removing $file\"\n              rm \"$file\"\n            fi\n          done\n\n      - name: Commit changes\n        run: |\n          git config --local user.email \"action@github.com\"\n          git config --local user.name \"GitHub Action\"\n          git add -A\n          if [ -n \"$(git status --porcelain)\" ]; then\n            git commit -m \":fire: Remove unnecessary .gitkeep files\"\n            git push\n          else\n            echo \"No changes to commit\"\n          fi\n        env:\n          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}\n"
  },
  {
    "path": ".github/workflows/lint.yml",
    "content": "name: python lint\n\non:\n  pull_request:\n    branches:\n      - main\n    paths:\n      - \"src/**.py\"\n      - \"tests/**.py\"\n      - \"poetry.lock\"\n      - \".github/workflows/lint.yml\"\n\njobs:\n  lint:\n    name: Lint\n    runs-on: ubuntu-latest\n    strategy:\n      fail-fast: false\n      matrix:\n        python-version: [\"3.9\", \"3.10\"]\n\n    steps:\n      - name: Checkout\n        uses: actions/checkout@v2\n\n      - name: Set up Python ${{ matrix.python-version }}\n        uses: actions/setup-python@v2\n        with:\n          python-version: ${{ matrix.python-version }}\n\n      - name: Install Poetry\n        run: |\n          curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python -\n          echo \"$HOME/.poetry/bin\" >> $GITHUB_PATH\n\n      - uses: actions/cache@v2\n        id: venv_cache\n        with:\n          path: .venv\n          key: venv-${{ matrix.python-version }}-${{ hashFiles('**/poetry.lock') }}\n\n      - name: Install Dependencies\n        if: steps.venv_cache.outputs.cache-hit != 'true'\n        run: poetry install\n\n      - name: Python Lint\n        run: poetry run task lint\n\n      - name: Python Test\n        run: poetry run task test\n"
  },
  {
    "path": ".gitignore",
    "content": "# Byte-compiled / optimized / DLL files\n__pycache__/\n*.py[cod]\n*$py.class\n\n# C extensions\n*.so\n\n# Distribution / packaging\n.Python\nbuild/\ndevelop-eggs/\ndist/\ndownloads/\neggs/\n.eggs/\nlib/\nlib64/\nparts/\nsdist/\nvar/\nwheels/\nshare/python-wheels/\n*.egg-info/\n.installed.cfg\n*.egg\nMANIFEST\n\n# PyInstaller\n#  Usually these files are written by a python script from a template\n#  before PyInstaller builds the exe, so as to inject date/other infos into it.\n*.manifest\n*.spec\n\n# Installer logs\npip-log.txt\npip-delete-this-directory.txt\n\n# Unit test / coverage reports\nhtmlcov/\n.tox/\n.nox/\n.coverage\n.coverage.*\n.cache\nnosetests.xml\ncoverage.xml\n*.cover\n*.py,cover\n.hypothesis/\n.pytest_cache/\ncover/\n\n# Translations\n*.mo\n*.pot\n\n# Django stuff:\n*.log\nlocal_settings.py\ndb.sqlite3\ndb.sqlite3-journal\n\n# Flask stuff:\ninstance/\n.webassets-cache\n\n# Scrapy stuff:\n.scrapy\n\n# Sphinx documentation\ndocs/_build/\n\n# PyBuilder\n.pybuilder/\ntarget/\n\n# Jupyter Notebook\n.ipynb_checkpoints\n\n# IPython\nprofile_default/\nipython_config.py\n\n# pyenv\n#   For a library or package, you might want to ignore these files since the code is\n#   intended to run in multiple environments; otherwise, check them in:\n# .python-version\n\n# pipenv\n#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.\n#   However, in case of collaboration, if having platform-specific dependencies or dependencies\n#   having no cross-platform support, pipenv may install dependencies that don't work, or not\n#   install all needed dependencies.\n#Pipfile.lock\n\n# poetry\n#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.\n#   This is especially recommended for binary packages to ensure reproducibility, and is more\n#   commonly ignored for libraries.\n#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control\n#poetry.lock\n\n# pdm\n#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.\n#pdm.lock\n#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it\n#   in version control.\n#   https://pdm.fming.dev/#use-with-ide\n.pdm.toml\n\n# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm\n__pypackages__/\n\n# Celery stuff\ncelerybeat-schedule\ncelerybeat.pid\n\n# SageMath parsed files\n*.sage.py\n\n# Environments\n.env\n.venv\nenv/\nvenv/\nENV/\nenv.bak/\nvenv.bak/\n\n# Spyder project settings\n.spyderproject\n.spyproject\n\n# Rope project settings\n.ropeproject\n\n# mkdocs documentation\n/site\n\n# mypy\n.mypy_cache/\n.dmypy.json\ndmypy.json\n\n# Pyre type checker\n.pyre/\n\n# pytype static type analyzer\n.pytype/\n\n# Cython debug symbols\ncython_debug/\n\n# PyCharm\n#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can\n#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore\n#  and can be added to the global gitignore or merged into this file.  For a more nuclear\n#  option (not recommended) you can uncomment the following to ignore the entire idea folder.\n#.idea/\n"
  },
  {
    "path": ".vscode/extensions.json",
    "content": "{\n  \"recommendations\": [\"ms-python.python\", \"njpwerner.autodocstring\"]\n}\n"
  },
  {
    "path": ".vscode/settings.json",
    "content": "{\n  \"[python]\": {\n    \"editor.defaultFormatter\": \"charliermarsh.ruff\",  // Ruff: it is a fast linter for Python, written in Rust.\n    \"editor.codeActionsOnSave\": {\n        \"source.fixAll.ruff\": \"explicit\",  //  Fix codes when saving\n        \"source.organizeImports.ruff\": \"explicit\",  //  Organize imports order when saving\n    },\n    \"editor.formatOnSave\": true,\n    \"editor.tabSize\": 4,\n  },\n  \"python.defaultInterpreterPath\": \"${workspaceFolder}/.venv/bin/python\",\n  \"autoDocstring.docstringFormat\": \"numpy\",\n  \"makefile.configureOnOpen\": false,\n}\n"
  },
  {
    "path": "LICENSE",
    "content": "MIT License\n\nCopyright (c) 2024 Naoki Chihara\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n"
  },
  {
    "path": "Makefile",
    "content": "PYTHON_VERSION = 3.10\n\n.PHONY: install\ninstall: check_pyenv check_poetry pyenv_setup poetry_setup\n\t@VENV_PATH=$$(poetry env info --path); \\\n\tSITE_PACKAGES_DIR=\"$${VENV_PATH}/lib/python3.10/site-packages\"; \\\n\tPROJECT_ROOT=$$(echo $${VENV_PATH} | rev | cut -d'/' -f2- | rev); \\\n\tVENV_NAME=$$(basename `dirname $${VENV_PATH}`); \\\n\techo $${PROJECT_ROOT} > $${SITE_PACKAGES_DIR}/$${VENV_NAME}.pth\n\n.PHONY: check_pyenv\ncheck_pyenv:\n\t@if ! command -v pyenv &> /dev/null; then \\\n\t\techo \"Error: \"pyenv\" is not installed. please visit https://github.com/pyenv/pyenv#installation in details.\"; \\\n\t\texit 1; \\\n\tfi\n\n.PHONY: check_poetry\ncheck_poetry:\n\t@if ! command -v poetry &> /dev/null; then \\\n\t\techo \"Error: \"pyenv\" is not installed. please visit https://python-poetry.org/docs/#installation in details.\"; \\\n\t\texit 1; \\\n\tfi\n\n.PHONY: pyenv_setup\npyenv_setup:\n\tpyenv install -s $(PYTHON_VERSION)\n\tpyenv global $(PYTHON_VERSION)\n\n.PHONY: poetry_setup\npoetry_setup:\n\tpoetry env use $(PYTHON_VERSION)\n\tpoetry install\n\n.PHONY: run\nrun:\n\tpython src/main.py\n\n.PHONY: pre-commit\npre-commit:\n\tpoetry run pre-commit run --all-files\n\n.PHONY: test\ntest:\n\tpoetry run pytest -s -vv --cov=. --cov-branch --cov-report=html\n"
  },
  {
    "path": "README.md",
    "content": "# image-stitcher\n\n[![Python 3.10](https://img.shields.io/badge/Python-3.10-green.svg)](https://www.python.org/downloads/release/python-390/)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n[![RubyDoc](https://img.shields.io/badge/%F0%9F%93%9AZenn-documentation-informational.svg)](https://zenn.dev/naoki0103/articles/image-stitcher-application)\n<a href=\"https://github.com/C-Naoki/image-stitcher/stargazers\"><img src=\"https://img.shields.io/github/stars/c-naoki/image-stitcher\" alt=\"Stars Badge\"/></a>\n<a href=\"https://github.com/c-naoki/image-stitcher/network/members\"><img src=\"https://img.shields.io/github/forks/c-naoki/image-stitcher\" alt=\"Forks Badge\"/></a>\n\nThis is a python implementation for stitching images by automatically searching for overlap region.\n- [👨‍💻 Usage](#-usage)\n- [🎯 Preview of results](#-preview-of-results)\n- [🧠 Main Idea](#-main-idea)\n- [🙋‍♂️ Support](#️-support)\n- [✉️ Contact](#️-contact)\n\n## 👨‍💻 Usage\n```python\nfrom src.main import main\nfrom src.utils.visualizer import result_visualize\n\nmerged_image, cand = main(\n    image1=image1,              # The first image to be combined\n    image2=image2,              # The second image to be combined\n    min_overlap=(5, 5),         # The minimum overlap region\n    verbose=False,              # Whether to print the log\n)\nresult_visualize(\n    image1=image1,              # The first image to be combined\n    image2=image2,              # The second image to be combined\n    merged_image=merged_image,  # The output image\n    cand=cand,                  # The parameters\n)\n```\n\n\n## 🎯 Preview of results\nThe results using [`CIFAR-10`](https://www.cs.toronto.edu/~kriz/cifar.html) are shown below. I would refer you to [`tutorial.ipynb`](https://github.com/C-Naoki/image-stitcher/blob/main/notebooks/tutorial.ipynb) for detailed results.\n\n<p align=\"center\">\n<img src=\"./docs/assets/input.png\" alt=\"\" align=center />\n<br><br>\n<b>Figure 1.</b> The example of input images. The red area represents an empty region. This application can combine these images while considering their rotation.\n</p>\n\n<p align=\"center\">\n<img src=\"./docs/assets/rotated.png\" alt=\"\" align=center />\n<br><br>\n<b>Figure 2.</b> The preprocessed input images. This rotation process is necessary to accurately combine the images. The green frame represents the overlap region between the input images.\n</p>\n\n<p align=\"center\">\n<img src=\"./docs/assets/result.png\" alt=\"\" align=center />\n<br><br>\n<b>Figure 3.</b> The output image.\n</p>\n\n## 🧠 Main Idea\n<p align=\"center\">\n<img src=\"./docs/assets/case1.png\" width=500 alt=\"\" align=center />\n<br><br>\n<b>Figure 4.</b> The overview of this application in limited case.\n</p>\n\nThis application is designed based on the overlap region's width $w_c$ and height $h_c$. Thanks to this idea, we can simply limit the search space, thus preventing it from capturing overly small, suboptimal overlap region.\n\n<p align=\"center\">\n<img src=\"./docs/assets/case2.png\" width=500 alt=\"\" align=center />\n<br><br>\n<b>Figure 5.</b> The overview of this application.\n</p>\n\nHowever, the above approach is not always applicable, specifically when $\\min(h_1, h_2) < h_c$ or $\\min(w_1, w_2) < w_c$. To address this issue, I change the perspective of $w_c$ and $h_c$ like the above figure. Therefore, this application can handle images of arbitrary sizes.\n\n\n## 🙋‍♂️ Support\n💙 If you like this app, give it a ⭐ and share it with friends!\n\n## ✉️ Contact\n💥 For questions or issues, feel free to open an [issue](https://github.com/C-Naoki/image-stitcher/issues). I appreciate your feedback and look forward to hearing from you!\n"
  },
  {
    "path": "data/__init__.py",
    "content": "from typing import Union\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nfrom matplotlib.patches import Rectangle\nfrom skimage.transform import rotate\nfrom sklearn.datasets import fetch_openml\n\n\ndef load_data(idx: int = 0) -> Union[np.ndarray, pd.Series]:\n    cifar10 = fetch_openml(\"CIFAR_10\")\n\n    data = cifar10[\"data\"]\n    target = cifar10[\"target\"]\n    X = np.array(data).reshape(-1, 3, 32, 32).astype(np.uint8)\n\n    return np.transpose(X[idx], (1, 2, 0)), target\n\n\ndef split_data(\n    image: np.ndarray, slicex: tuple, slicey: tuple, angle: int = 0, plot: bool = False\n) -> Union[np.ndarray, np.ndarray]:\n    if plot:\n        viz_image1 = np.zeros_like(image)\n        viz_image1[:, :, 0] = 255\n        viz_image1[slicey[0], slicex[0], :] = image[slicey[0], slicex[0], :]\n        viz_image2 = np.zeros_like(image)\n        viz_image2[:, :, 0] = 255\n        viz_image2[slicey[1], slicex[1], :] = image[slicey[1], slicex[1], :]\n\n        fig, ax = plt.subplots(1, 3, figsize=(7, 3))\n\n        ax[0].imshow(image)\n        ax[0].set_title(f\"Original {image.shape[1]}x{image.shape[0]}\")\n        ax[0].axis(\"off\")\n\n        ax[1].imshow(viz_image1)\n        ax[1].set_title(f\"First {slicey[0].stop - slicey[0].start}x{slicex[0].stop - slicex[0].start}\")\n        ax[1].axis(\"off\")\n\n        ax[2].imshow(viz_image2)\n        ax[2].set_title(f\"Second {slicey[1].stop - slicey[1].start}x{slicex[1].stop - slicex[1].start}\")\n        ax[2].axis(\"off\")\n\n        rect1 = Rectangle(\n            (max(slicex[0].start, slicex[1].start), max(slicey[0].start, slicey[1].start)),\n            min(slicex[0].stop, slicex[1].stop) - max(slicex[0].start, slicex[1].start) - 1,\n            min(slicey[0].stop, slicey[1].stop) - max(slicey[0].start, slicey[1].start) - 1,\n            linewidth=7,\n            edgecolor=\"g\",\n            facecolor=\"none\",\n        )\n        rect2 = Rectangle(\n            (max(slicex[0].start, slicex[1].start), max(slicey[0].start, slicey[1].start)),\n            min(slicex[0].stop, slicex[1].stop) - max(slicex[0].start, slicex[1].start) - 1,\n            min(slicey[0].stop, slicey[1].stop) - max(slicey[0].start, slicey[1].start) - 1,\n            linewidth=7,\n            edgecolor=\"g\",\n            facecolor=\"none\",\n        )\n\n        ax[1].add_patch(rect1)\n        ax[2].add_patch(rect2)\n\n    image1 = image[slicey[0], slicex[0], :]\n    image2 = image[slicey[1], slicex[1], :]\n\n    rotated_image2 = rotate(image2, angle, resize=True, preserve_range=True).astype(np.uint8)\n\n    return image1, rotated_image2\n"
  },
  {
    "path": "docs/source/conf.py",
    "content": "import os\nimport sys\n\nfrom sphinx_pyproject import SphinxConfig\n\nsys.path.append(\n    os.path.abspath(f\"{os.path.dirname(os.path.abspath(__file__))}/../../\")\n)\n\nconfig = SphinxConfig(\"../../pyproject.toml\", globalns=globals())\n"
  },
  {
    "path": "notebooks/tutorial.ipynb",
    "content": "{\n \"cells\": [\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 1,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"import os\\n\",\n    \"import sys\\n\",\n    \"from pathlib import Path\\n\",\n    \"sys.path.append(os.path.join(Path().resolve(), '..'))\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 2,\n   \"metadata\": {},\n   \"outputs\": [],\n   \"source\": [\n    \"import matplotlib.pyplot as plt\\n\",\n    \"\\n\",\n    \"from data import load_data, split_data\\n\",\n    \"from src.main import main\\n\",\n    \"from src.utils.visualizer import result_visualize\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"## Download test data\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 3,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"image/png\": 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\",\n      \"text/plain\": [\n       \"<Figure size 640x480 with 1 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    }\n   ],\n   \"source\": [\n    \"image, target = load_data(idx=0)\\n\",\n    \"\\n\",\n    \"# preview of image\\n\",\n    \"plt.imshow(image)\\n\",\n    \"plt.title(f'Label: {target[0]}')\\n\",\n    \"plt.show()\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"## Image Sticher\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"### Example 1.\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 4,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"image/png\": \"iVBORw0KGgoAAAANSUhEUgAAAjIAAADJCAYAAAA5BtiqAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy80BEi2AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAucUlEQVR4nO3deXiTVfo+8DtJk7RNulBaoBRbWlZZK7IjBWZkEQFRAUFcyiKuMIwOXqMz31F0ZBxHGRz3hQGEcRkUl3GDgo6AgCLIvnfRspa2dG/TLOf3B79miM8B0lJtX7g/18V16Z03ed8kJ8npmyfPMSmlFIiIiIgMyNzQB0BERERUV5zIEBERkWFxIkNERESGxYkMERERGRYnMkRERGRYnMgQERGRYXEiQ0RERIbFiQwREREZFicyREREZFgXzUTm0UcfhclkqtN1Fy9eDJPJhJycnPo9qDPk5OTAZDJh8eLFP9s+iDjOiBoHk8mERx99tKEP45LQ4BOZ3bt345ZbbkFCQgLsdjtatmyJyZMnY/fu3Q19aA3i6NGjuOWWW9ChQwdEREQgOjoavXv3xpIlS/DT1SRWrFiBm266CSkpKQgPD0eHDh3wwAMPoKioqE77rqysxLRp09ClSxdERUXB6XSie/fuePbZZ+F2uwO2XbNmDaZOnYr27dsjPDwcKSkpmD59Oo4dO1bXu05BqJl06/79/ve//1n2OW/ePHzwwQdBbZubm4u5c+eid+/eaNKkCWJjYzF48GCsXr1au31RURFmzJiBuLg4OBwODBkyBFu3bq3TcXL8GsvOnTsxbtw4JCUlITQ0FAkJCRg6dCiee+65hj60XwxfL/XD1JBrLa1YsQKTJk1CTEwMpk2bhuTkZOTk5GDhwoUoKCjA22+/jeuvvz6o2/J4PPB4PAgNDa31cXi9Xrjdbtjt9jqf1TmfnJwcJCcnY9GiRUhPTz/rdjt27MCsWbMwYMAAJCYmwu12IyMjAx999BEeeughzJs3z79tbGwsWrZsibFjxyIxMRE7d+7Eyy+/jJSUFGzduhVhYWG1OsbCwkKMHDkSaWlpaN26NcxmMzZs2IBly5Zh4sSJePPNN/3b9uzZE4WFhRg/fjzatWuHrKwsPP/88wgPD8e2bdvQokWLWj9GdH6LFy/GlClT8NhjjyE5OTngsi5duqB79+5wuVywWq2wWCz1sk+n04lx48YFdZbn+eefx4MPPoixY8diwIAB8Hg8eOONN7B161b885//xJQpU/zb+nw+DBw4ENu3b8ecOXMQGxuLF198Ebm5udiyZQvatWtXq+Pk+DWODRs2YMiQIUhMTMTtt9+OFi1aIDc3F5s2bUJmZiYOHTrU0Id4wUwmEx555JFznpXh66WeqAZy6NAhFR4erjp27Kjy8vICLjt58qTq2LGjcjgcKjMz85y3U1ZW9nMeZr3Jzs5WANSiRYvqdP1Ro0Yph8OhPB6PP/vyyy/FdkuWLFEA1GuvvVbHI5Xuu+8+BUAdO3bMn3311VfK6/UGbPfVV18pAOoPf/hDve2bAi1atEgBUJs3b76g26nN68bhcKjbb789qG137dqlTp48GZBVVVWpjh07qlatWgXk77zzjgKgli9f7s/y8vJUdHS0mjRpUtDHdz4cv43PyJEjVVxcnDp16pS47MSJE7/8Af0MAKhHHnnknNvw9VI/Guyrpb/97W+oqKjAq6++iri4uIDLYmNj8corr6C8vBxPPfWUP6+pg9mzZw9uvvlmNGnSBFdddVXAZWeqrKzErFmzEBsbi4iICIwZMwZHjhwR313qamRat26NUaNGYf369ejduzdCQ0ORkpKCN954I2AfhYWF+N3vfoeuXbvC6XQiMjIS11xzDbZv315Pj9T/jqeiogLV1dX+bPDgwWK7mjNYe/fu9WePPPIIzGYz1qxZE7DtjBkzYLPZznusrVu3BoCAr6zS0tJgNgcOn7S0NMTExATsm35ZuhqZ9PR0OJ1OZGZmYuTIkYiIiMDkyZMBAAcPHsSNN96IFi1aIDQ0FK1atcLEiRNRXFwM4PRfleXl5ViyZIn/K6xznVHs3LkzYmNjAzK73Y6RI0fi8OHDKC0t9efvvvsumjdvjhtuuMGfxcXFYcKECfjwww/hcrkAcPxejDIzM9G5c2dER0eLy5o1ayayZcuW4corr0RYWBhiYmIwceJE5Obmiu2++eYbjBw5Ek2aNIHD4UC3bt3w7LPPBmzzxRdfYODAgXA4HIiOjsZ1110nnvOaz5NDhw4hPT0d0dHRiIqKwpQpU1BRURGwrcvlwm9/+1vExcX5P2cOHz4c1OPA10v9aLCJzH/+8x+0bt0aAwcO1F5ec7rrk08+EZeNHz8eFRUVmDdvHu64446z7iM9PR3PPfccRo4cib/+9a8ICwvDtddeG/QxHjp0COPGjcPQoUPxzDPPoEmTJkhPTw+o38nKysIHH3yAUaNGYf78+ZgzZw527tyJQYMG4ejRo0Hv66cqKyuRn5+PnJwcLFmyBIsWLUK/fv3O+3XR8ePHASDgxfHHP/4RqampmDZtmv+FsXLlSrz22mv405/+hO7duwfcRnV1NfLz85Gbm4v3338fTz/9NJKSktC2bdtz7rusrAxlZWXihUn1r7i4GPn5+QH/zsXj8WD48OFo1qwZnn76adx4442orq7G8OHDsWnTJsycORMvvPACZsyYgaysLP+b2NKlS2G32zFw4EAsXboUS5cuxZ133lnr4z1+/DjCw8MRHh7uz77//nv06NFDvEH27t0bFRUVOHDgAACO34tRUlIStmzZgl27dp132yeeeAK33XYb2rVrh/nz52P27NlYs2YN0tLSAj5sMzIykJaWhj179uA3v/kNnnnmGQwZMgQff/yxf5vVq1dj+PDhyMvLw6OPPor7778fGzZswIABA7Q/9pgwYQJKS0vxl7/8BRMmTMDixYsxd+7cgG2mT5+OBQsWYNiwYXjyySdhtVpr9Tmjw9dLLTXEaaCioiIFQF133XXn3G7MmDEKgCopKVFKKfXII48oANrTaDWX1diyZYsCoGbPnh2wXXp6ujjlV3O6Pjs7258lJSUpAGrt2rX+LC8vT9ntdvXAAw/4s6qqKnHKLTs7W9ntdvXYY48FZKjFV0t/+ctfFAD/v1//+tfqxx9/PO/1pk2bpiwWizpw4EBAvnPnTmWz2dT06dPVqVOnVEJCgurZs6dyu93iNt56662Afffs2VPt2LHjvPt+/PHHFQC1Zs2aoO4j1V7NWNX9U0o/zm6//XYFQP3+978PuK3vv/9enKrWqc1XSzoHDx5UoaGh6tZbbxW3O3XqVLH9J598ogCozz//3J9x/F5cVq1apSwWi7JYLKpfv37qwQcfVCtXrlTV1dUB2+Xk5CiLxaKeeOKJgHznzp0qJCTEn3s8HpWcnKySkpLE11U+n8//36mpqapZs2aqoKDAn23fvl2ZzWZ12223+bOaz5Ofjs/rr79eNW3a1P//27ZtUwDUPffcE7DdzTffHNRXSzp8vdReg5yRqZklRkREnHO7mstLSkoC8rvuuuu8+/j8888BAPfcc09APnPmzKCPs1OnTgFnjOLi4tChQwdkZWX5M7vd7p8he71eFBQUwOl0okOHDnWuJgeASZMmISMjA2+++SZuvvlmAKfP0pzLm2++iYULF+KBBx4QhV9dunTB3Llz8frrr2P48OHIz8/HkiVLEBISIm5nyJAhyMjIwPLly3HXXXfBarWivLz8nPteu3Yt5s6diwkTJuBXv/pVLe8t1dYLL7yAjIyMgH/nc/fddwf8f1RUFIDTf6399HR5famoqMD48eMRFhaGJ598MuCyyspK2O12cZ2agv0zxzvH78Vl6NCh2LhxI8aMGYPt27fjqaeewvDhw5GQkICPPvrIv92KFSvg8/kwYcKEgLOPLVq0QLt27fDll18COH22Ijs7G7NnzxZfV9WUHBw7dgzbtm1Deno6YmJi/Jd369YNQ4cOxaeffiqO86efNQMHDkRBQYH/M6nmOrNmzQrYbvbs2XV6XPh6qaOGmD3V9oxMcXGxUup/s2TdmYmfnpGZMWOGMpvNYgZaXFwc9BmZESNGiP0MGjRIDR482P//Xq9XzZ8/X7Vt21ZZLJaAme2QIUP8211ose8dd9yhLrvsMlVRUaG9fO3atSo0NFQNHz5cO+tW6vRfLd27d1cA1Lx584Le9xNPPKGcTmdA8deZ9u7dq2JiYlRqaqr/7Bn9PM5X7Hu2MzIhISHizKFSSt1///0KgAoLC1PDhg1Tzz//vCoqKgrYpq5nZDwejxo9erSy2Wzav9pq8xdmze1x/F58XC6X+vbbb9VDDz2kQkNDldVqVbt371ZKKXX33Xef9QwkANWtWzellFJvv/22AqAyMjLOup+NGzcqAGrhwoXistmzZysA/iL4ms+T48ePB2xX8/rLyclRSil15513Bv05cz58vdRdg5yRiYqKQnx8PHbs2HHO7Xbs2IGEhARERkYG5LX9WXFdne3nq+qMX6zPmzcP999/P9LS0rBs2TKsXLkSGRkZ6Ny5M3w+X70dy7hx45Cbm4u1a9eKy7Zv344xY8agS5cuePfdd7WzbuB0Pc/BgwcBnO7hUJt9l5WV4cMPPxSX5ebmYtiwYYiKisKnn3563rNs1DDOPHN4pmeeeQY7duzAww8/7C+O79y5c9DFiudyxx134OOPP8bixYu1f7XFx8dr+1DUZC1btgzIOX4vTjabDb169cK8efPw0ksvwe12Y/ny5QBO/+TYZDLh888/F2cgMzIy8Morr/ysxxbMZ0B94eul7hqs2HfUqFHIzs7G+vXrtZevW7cOOTk5GDVqVJ1uPykpCT6fD9nZ2QF5ffcnePfddzFkyBAsXLgQEydOxLBhw3D11VfXuSnd2dScNqz5NUmNzMxMjBgxAs2aNcOnn34Kp9Opvb7P50N6ejoiIyPx8MMP46233sKKFSsuaN8FBQUYNmwYXC4XVq5cifj4+NreLWoEunbtij/+8Y9Yu3Yt1q1bhyNHjuDll1/2X16X3kpz5szBokWL8Pe//x2TJk3SbpOamoqtW7eKCf8333yD8PBwtG/f3p9x/F4aevbsCeB/H85t2rSBUgrJycm4+uqrxb++ffv6twNwzuLhpKQkAMD+/fvFZfv27UNsbCwcDketjrfmcyYzMzMg1+3jXPh6uTANNpGZM2cOwsLCcOedd6KgoCDgssLCQtx1110IDw/HnDlz6nT7w4cPBwC8+OKLAXl9d420WCxidr58+XIcOXKkTrd38uRJbb5w4UKYTCb06NHDnx0/fhzDhg2D2WzGypUrxc/YzzR//nxs2LABr776Kh5//HH0798fd999d8CvXfLz87V/abz++usA/vcmAwDl5eUYOXIkjhw5gk8//bTWzZio4ZWUlMDj8QRkXbt2hdls9v+UEwAcDketJuZ/+9vf8PTTT+Phhx/Gb37zm7NuN27cOJw4cSLgDTY/Px/Lly/H6NGjA+oBOH4vLl9++aX2uaqpOenQoQMA4IYbboDFYsHcuXPF9kop/2dHjx49kJycjAULFoixWnO9+Ph4pKamYsmSJQHb7Nq1C6tWrcLIkSNrfT+uueYaAMA//vGPgHzBggVB3wZfLxdO/x3EL6Bdu3ZYsmQJJk+ejK5du4rOvvn5+Xjrrbf8M+3auvLKK3HjjTdiwYIFKCgoQN++ffHVV1/5f6JWXx18R40ahcceewxTpkxB//79sXPnTvzrX/9CSkpKnW7viSeewNdff40RI0YgMTERhYWFeO+997B582bMnDkz4CdxI0aMQFZWFh588EGsX78+4OxW8+bNMXToUACne8r83//9H9LT0zF69GgAp3vnpKam4p577sG///1vAKd7Nbz88ssYO3YsUlJSUFpa6v+qbPTo0QGnOydPnoxvv/0WU6dOxd69ewN6CTidTowdO7ZO959+OV988QXuu+8+jB8/Hu3bt4fH48HSpUthsVhw4403+re78sorsXr1asyfPx8tW7ZEcnIy+vTpo73N999/Hw8++CDatWuHyy+/HMuWLQu4fOjQoWjevDmA02/Mffv2xZQpU7Bnzx5/p1Kv1xvwE1eO34vPzJkzUVFRgeuvvx4dO3ZEdXU1NmzYgHfeeQetW7f2d7Rt06YN/vznP+Ohhx5CTk4Oxo4di4iICGRnZ+P999/HjBkz8Lvf/Q5msxkvvfQSRo8ejdTUVEyZMgXx8fHYt28fdu/ejZUrVwI4PWm45ppr0K9fP0ybNg2VlZV47rnnEBUVVad1kVJTUzFp0iS8+OKLKC4uRv/+/bFmzZqgz/zz9VJPGqg2x2/Hjh1q0qRJKj4+XlmtVtWiRQs1adIktXPnTrFtTQHWTzshnnnZmcrLy9W9996rYmJilNPpVGPHjlX79+9XANSTTz7p3+5sxb7XXnut2M+gQYPUoEGD/P9fVVWlHnjgARUfH6/CwsLUgAED1MaNG8V2wRb7rlq1So0aNUq1bNlSWa1WFRERoQYMGKAWLVoU8DNCpdQ5i+Bq9u3xeFSvXr1Uq1atRBHns88+qwCod955Ryml1ObNm9X48eNVYmKistvtyuFwqB49eqj58+eLYraan6fr/iUlJZ3zPlLd1bXY1+FwiG2zsrLU1KlTVZs2bVRoaKiKiYlRQ4YMUatXrw7Ybt++fSotLU2FhYUpAOcs/K15HZ7t30+7URcWFqpp06appk2bqvDwcDVo0KCA+8bxe3H67LPP1NSpU1XHjh2V0+lUNptNtW3bVs2cOVPb2fe9995TV111lXI4HMrhcKiOHTuqe++9V+3fvz9gu/Xr16uhQ4eqiIgI5XA4VLdu3dRzzz0XsM3q1avVgAEDVFhYmIqMjFSjR49We/bsCdjmbJ81us+KyspKNWvWLNW0aVPlcDjU6NGjVW5ublDFvny91I8GXWupIWzbtg1XXHEFli1b5u9uSkRERMbU4Ktf/5x0fVcWLFgAs9mMtLS0BjgiIiIiqk8NViPzS3jqqaewZcsWDBkyBCEhIfjss8/w2WefYcaMGbjssssa+vCIiIjoAl3UXy1lZGRg7ty52LNnD8rKypCYmIhbb70Vf/jDH87aa4WIiIiM46KeyBAREdHF7aKukSEiIqKLGycyREREZFhBF4oktEgWWWWlS2Qet+6bKk1mkusQBdukTred7huyn3YtBfRrZ+jWi6hyuUV2ZrdT/359cr9mi5wf+nzyWHTHHB4eLjKLRT5Nbne1yKxWq8h0x6yrD3JVy9sLC5ftunXr9VRrrqvj88r7GxYu183yeb0iO5GXKbJfCsc+xz5waY59AEA9NQ8lqpMgql94RoaIiIgMixMZIiIiMixOZIiIiMiwOJEhIiIiwwq62FdX1ObxyMI03dzI55PFjcEWPOqKAh0OWYinU1FREdR2ZWVlcr+a+6E7Fl1xo66o0uORj59uu7i4OJHVLFV/pipXlTw+TWGprkDRZrOJrEKznIOuWFJ3e2cuH18jwhkpslOFJSLzeuQ4CA2ThZsNiWOfY/9st3exj30iI+AZGSIiIjIsTmSIiIjIsDiRISIiIsPiRIaIiIgM64KKfQFdx0dZdGfRFAV6NUWQusJIXVGgrsCuqkpTABjkepi67qEhVlkUqCuM1BUAags8NXTX1XVk1d03XcPYapd8jrw+WZTqdsvOrTabfExtmsc5KipKZLrC0pKSYpH5lHxcbCHycTab5XPekDj2OfaBS3PsExkBz8gQERGRYXEiQ0RERIbFiQwREREZFicyREREZFhBF/sqTRFfSIgsiPNqlqvX1kVqMuWT19V14iwvLxeZrhOnjq4IUldUGWyxpG47XcGj7uZ03VxPnTolMrPm+ExeWcgYbCdTq1V2D9UVoOqqKm02ed0mTVqKTFcYaTLJ2ysrk8WSx4/laY6l4XDsB397HPsX19gnMgKekSEiIiLD4kSGiIiIDIsTGSIiIjIsTmSIiIjIsIIu9rXoChS9sksmZB0elFle2aSpeAy22+eFdA/V8Wk6gGq7tGpuT5d53PKYdcWNuiLI6urgChnt9lBNJosRodlvhNMpsg4d24usc5cOIktNTRVZUlJrkYWHh4ns6NFjInvkT38WWXFRkcgaEsc+xz5waY59IiPgGRkiIiIyLE5kiIiIyLA4kSEiIiLD4kSGiIiIDCvoYl+TpgDQp+mwCaXpxKkp7PNpbk/XKdSr24fu+LQFhfL2dNvpiiqVT25nMcv7ZjbJuaBJVxip2c6n6eaqqxgNDZXFjRaLLPqMiJTbDRhwlcjGjBkjsj59eoksNi5GZLriS11n2ZAQObSys3NEdvy47GTqclWLrCFx7HPsA5fm2CcyAp6RISIiIsPiRIaIiIgMixMZIiIiMixOZIiIiMiwgi721TFrCgCVkoWCmtpBbXdTHV0nU13RYrCZrghSWxgJed8iIiKCum5ZWZnIvCq4+xEWZheZM0IWMvbrf6XIxo0bK7IB/QeILK5ZM5Ht2bNXZPv27xFZ3759Raa7H25Nh9dNG78RWUlRqcisIfIxaGw49jn2gUtz7BM1NjwjQ0RERIbFiQwREREZFicyREREZFicyBAREZFhBV3sqytuhK64UVPdqHRFi5bgChQvpLupLoOmq6rHI4/PZrWKTFd86Xa7g9rOarWJLMwhCxkTEpqL7JZbJ4ps8mSZNWkSJTKPRz5+Ho885rAweSwxMbK7qa5rqa477MmTJ0W2UVPwWK0pjHQ6wkXWkDj2OfaBS3PsExkBz8gQERGRYXEiQ0RERIbFiQwREREZFicyREREZFhBF/vqCg91HUCh6VpqMsvMEiILCl3VLs3N6a4rD1tXVKk7Fl3hpubmtEV8pWWyE6fyyQLKiEjZBdXhlJkzIkxkt9w6SWTDR/xKZLrCQ69PzkstluDmqklJyZpU3reKikqR+XxybKxdu05ku3bJbqlWq+xk6nYHV+T6S+HY59gHLs2xT2QEPCNDREREhsWJDBERERkWJzJERERkWJzIEBERkWEFXezrMctNQ0xyHmTSFABCUxhpC5MFgG0u7yqy8soqkf34Q5bIlE8WS5qVPD6zksdngiyWDA2XBZn2UJl16dJJZBNuGi+yMKdTZEXFp0TWto0sPNy7d6/IDmX/ILJOnTqLLCG+hcj0z5FU5aoWmcslCx6PHD4ustdfe0NkFRXyubTZZNGnV8li04bEsc+xD1yaY5/ICHhGhoiIiAyLExkiIiIyLE5kiIiIyLA4kSEiIiLDCrrY9/LUK0WWfShTZNWa7pfWUFns16N3P5HdN+tukVksskPp0iWLRPbZxx+LzFXhFpnbIwsjIyLkwzBkcC+RtUm+TGSdO7UVWdpAWbjZsrUsjKz2yELQ4pJykb359gqRWWxyDmq1y4JMXTFny+bNRVZeJp+3qir5WFVWVYjspZdeEdnWLdtF5tAUfXq98viUrlFtA+LY59gHLs2xT2QEPCNDREREhsWJDBERERkWJzJERERkWJzIEBERkWEFXex7+7TpInvnrX+LbLdmufore/UW2R13ytvr27uHyKwmuax9csIckbWIixXZu/9eLrIm0eEi69wpRWTDrvmVyJJaxYussqRQZBs3rBNZtzJZKNj2cnl/Y2NiRNa/fx+R5eTKDq+a2lAc2L9fZCEWWRhZWS47j5ogu6AueWOxyFas0BRkWmQxp88nKxm9Xvn8OsJl59uGxLHPsQ9cmmOfyAh4RoaIiIgMixMZIiIiMqygv1oiulQ9evQ+kZX1KBNZdRe50OA6u1zgcMeOlSILOxCq2bP8ekP3dURJeIk8vnHy+I6Z5d8th2z7RJaR+1+RhRyTX5cozdclPp88PnueXWTWtTKDZiFOl2bxRrdH9sixaO6b0jx+tl1yv7r7oVMaUiqy4lvlY69ZmxMmk/zuS2k2rDCfDOpYfkltZzX0EdCl7FAQ23AiQ3Qe+R65wjHkwsXarBLyg7jSJT8QIfuvBU93XjUyuKtWa3Zc5pGN6XAhizLrrivLZn4ZshwmeJo6HEQHd9Xg1twGvJATwYaWKUuXiBqVoCcy114zTGShdvnO/d77H4ls/PVjRdarRzeRKa/mry8l//pq2bKFyO66+06RXd6xnci++3atyOKayQK7b7fK7pxff/OdyIYPGyGytqmyk+n2Pd+IrHliksiimsiCzBYto0T2/Auy2FRp3gPTBl8tsuimsrtpeKjc7ycffSD3+/zzInNVyU8qi1neXlWV/BSx2+WZCI+n8b2ZExFR48QaGSIiIjIsTmSIiIjIsDiRISIiIsPiRIaIiIgMK+hi34hw2RHzqv69RBar6TLaoXUrkTlsmp+W+mRhr0fzE8Wq8kqR2WzyrjSJlj/dKCg8IbI+vTuIbOdy2bGzokr+wmOzQxbiJsS3lscXKR+DH4/J4tfcTetF9uLL80WWl5crsok3TRRZ27ay4Nmn+QnFqozVIvvnwn+KrKxU/qzXYpE/afVpCrejmjQRmVdT2FtZ2VA/aSEiIqPhGRkiIiIyLPaRIboAIaYQtHSePttW7ZY/Q7eFyJeYxRJc87Zgm4/oGqu5XPJsX2mpbN7mCJctFMrLZR8Zn+Y0nj1U/nTe6ZStDDxe+bhYQ+QZXt3P7ouLi0Tm1dye0+mUx6f5ab/JLBv76doClGj263bLM8b65jIyM2ue8zOfX1+EB5CH1qidOfYBjn+A4/9s2bnGf32MfU5kiC5AS2crrLrhWwDAvoPZ4nLd16rNm8qvPL1Ks6ig5g3a65XbeTRvMN99s0lkb7+9UGQjR6SJ7MMgv1bt0XuQyMZeO0lkx07+KLKUpI4iy/1Bfu17IV+rXnFlP5GFOaNFtmH9BpG98sY/RJaVJXuM6r5WhZIfUuf7WrXo9qPwRV9I18Ff3pljH+D4Bzj+AdR6/NfH2OdXS0RERGRYQZ+RMWnWUIly2ETWo4ssLrXb5XzJa5LFoCYlzy+FmOQ+vErTAbhKng48nLVTZF07XCay5CTZidcZ+bXI7DgosvKTe0X27r/fFdnlV/SRx3f4e5G9+cYbIot0ysfg3vt+K7KklPYi82lmxxu+3SKyTz7/VGTHj+eJzG6Xf035tGvuyCzEIp/fas1aOtoWxY2U2WTyvw449jn2z5adf+wHu4hB43Hm2Ac4/gGO/7Nl5x7/Fz72eUaGiIiIDIsTGSIiIjIsTmSIiIjIsDiRISIiIsMKutjXqukHAM3P42whsqjHB1m8aTHL2zOb5O/PXZWa3/RXy+6yoSHyJ3itEjRdhjsnigyh8qdhLdp0FlnZUfkTscjopiJrmiT3sW+/LBbbuH6tyLp2k8Vn/fr0FlnCZXIfHiULw77/fofIvtsif263Z/cueXse+XxYLbLvAiyyuMvtlt2XT506Ja+q6Wtg0oyDxspkMvnHPMc+xz5Qt7GveStt9M4c+wDHP8DxD9R+/NfH2OcZGSIiIjIsTmSIiIjIsDiRISIiIsPiRIaIiIgMK+hiX7OmKBOQRVa6rn7QRFUeeV2Xq0JkJ4/9IDLlKRZZk+hokbXv3EVkJ0plsdjGbbLYqdllsgtkSqvWIouIlIuE7cjcL7JvN28VWffuqSJLTZVZ84R4kbk98qnbsvk7kZ04LtflOLh3t8iK8gtEZkG4yDTrlSEsXG6nNGunaBcd09T1RmueSyPg2OfYBy5s7BsZxz/HP9Aw459nZIiIiMiwOJEhIiIiw+JEhoiIiAyLExkiIiIyrKCLfb2aSp9gO7Aqn2zd98Ph4yKz2OWy47nH5HY7N68R2U0TbxFZs8vk0uYnM7NF5nIdFlnTONnxsWlknMg2bpSdEg/+cEhkbVJSRGbRdEtuFi+LuzyQhdb79slukWXlpSLLzjwgsixNp0mLZijonl/dU+7x6oq+ZUdPq1U+v6FhoZrraioEG7FzvQ449jn2gfOP/UpTIQzY3Pe8nwEc/xz/wLnHf32MfZ6RISIiIsPiRIaIiIgMixMZIiIiMixOZIiIiMiwgi72rdZ05tMtve7RbOfxyuLNKk11z5pVX4ksJT5aZJ269ZFXtkWK6Iejculwr9cusqQEWYzl8sgukJu+/Vpkh4/JYjFbiFzuvKrCJbK+ffqLrFyz3ZETeSIzWeRjX1Agi+O2bd0sMle5fI7sNnnMPpMs8HaEO0WmlCzuqnLJfVitcql5V5W8v6VuWbjWmKn/vw49xz7HPlC3sV8zhozmzOPm+Of4B2o//utj7POMDBERERkWJzJERERkWEF/tUREUm7pj+i5pDsA/SlSpemQ4PbI07GVlVUis/4g/84waW7PflSeMvcpefrZp+np4dEci27Rt2pbtbxuomYVOc1ZYl3/iYzc90RmNsv76/HK49PtpLqJPL6K8fIrAq/m/labyoPaR6VZLlgIzXPu0z1+Jvl16ZlXVZG6+9m4nTn2AY7/01eWEcf/ucd/fYx9TmSILoDH50F2cdbPc+OaBWMvaLsLoet7JntcBa3MU1L3K+vIvmGALJ3QUgjujdSrW8o5SMasgDm3n3XsAxz/tXGJj/+gJzJF5ZUiC7XJqyu3LFgqLpezbYtmmnokO1NkFSWxIuvdu6vI9uTIJctd1fLZLS6W96NSUwCVlb1PZCfz8kWWn3dSZHHN5PLu48bfLDKPVz4G23fsEFlM06Yi0y3Rvm7NKpGdPC6LxUI1BWk+TYdGq67rrqZ4z6Pp+qz7q8ZVLR977QjXXJeIiEiHNTJERERkWJzIEBERkWFxIkNERESGxYkMERERGVbQxb7lZbJg1+R0aLaUHfwKC2RB7Iljcrnzy1NkkeyatZtEtnOnLIjtdLns0Hh5x04ic7tkhfax48dEVl4h7+/+A7IA+Iruch+jR48QWVm5/CncqSL5s7fIiCiRHTksj2/dF1+I7MC+/fL2nJrSdc3PEENtsrDXrSlmr6yWxdzWEFlUbTbLzOeTRbwmzc8BTCbOr4mIKDj8xCAiIiLDYh8ZovNoU9jQR0DUcC5zJolMf9ZUnunVNWDzaFo9eNyahm6V8uwvNPu1adqA2DRr++iW9PF4ZOsIr+bMscslz9DbbXIfDke4yDQ3pz07rWsoqGuIV1VZIY+vSra2CPbMtknXsU9D9/jprqtrvaG9rvZggjoUgRMZovM49I+GPgK6pD3bsLv/z8i1InNqywrkp9WRH4+ITFdWkPOD/Np+zZbvReYzy4mCtqwgRX7lX60pK8jVfG2fX1ggsu+3ficybVlBP11ZgdyvrqygSjNxO6HpU7Zu3Wci27xJLroZEWRZgd0mOyPrygo8HjnL0JUVVFXLLr66rsr6sgLNTGaBjH6KXy0RERGRYQV9RiZMUwxaXiZnkN/vPiCyqmJ5bj4xXjcbk22bTx6Rt1dSIk/plebLZdvLT8lZr80uZ5CHsnJEFp/YQWQ9+3QT2dBfDxbZieNyRnqyUHbYDXfIZdEzM+WxVFbI6XGnzleIrDBf7sNilo9zYb6c5YeGyue3qlgWKEPJx8+lKQDWzbZ1M3+vplOwbs0RImoYfO/nez+ARv3ez08MIiIiMixOZIiIiMiwOJEhIiIiw+JEhoiIiAwr6GLfAwcPimz9+vUiW7tZ03W3fbLIjhyVRVufrVwtssysH0VWXix/+3/syGGRHc2Vx+yulkVgUU3jRHbVr+XP6Dp1kvfjaK7cr9sli52q3fKYt23YIDJPtZxbjh9/s8iiIsJE9kOO/FnjD1nyMajW9GwwawrDlLbXgTw+bcdeza/olAqui6/dLovPiKhh8L2f7/1A437v5xkZIiIiMixOZIiIiMiwOJEhIiIiw+JEhoiIiAwr6GLfpW//S2TfrP1SZBZnjMh8kEVW3+2S+3Cb5JoZ4TGys2Fp6R6RlVecEFnlj7LboW5hrqQUuSia1S63O3pMdp/0emXhVXHJcZFt+W6byMrL5OJf48aPl8fXOl5k1VWyo+IVPXqJ7NgxudaJW7MQmV2zToqO7vELlmYtMe0icF6PbkMiagh87+d7P9C43/t5RoaIiIgMixMZIiIiMixOZIiIiMiwOJEhIiIiwwq62Pe/K98Xmdsrl+ZunRAlsuI82aERMbK4KzKxi8jCQuXS4dFhsujIVSSXiy8rkZ0Xm7eUHRqH/HqMyMwWed/KSmXh2qm8fJF9vU4WwhUVyaXmZ8y4Q2R9essl2l2uSpHFxUaI7JZbbhKZN0TejzffWCIyVMrHT1fb5VOyWMxkkhvabLJDo8+r6SCp2UllZZXcMRE1CL73870faNzv/TwjQ0RERIbFiQwREREZFicyREREZFicyBAREZFhBV3sGx4muxh26DZQZKdOycKmH7IzReYod4usmVkWCdnKikTWNLaFvL32nURmN8sCrdReV4ksJKq1yErL5HVzc3JEtm3zFpFVVcoCrVtukcuxXzWgn8jsdvmUOB1y2XuLZun1SKd8jpLatBVZRJNmIjuRJ7tAmixyH2bN1FdXGOb1yMIwQBbvWSwyu5AOkkRUv/jez/d+oHG/9/OMDBERERkWJzJERERkWJzIEBERkWFxIkNERESGFXSx76Qp94isadPLRPbqC8+KrLRULlnudR2S252Sy7HHhMkuhuZ27UXmsjcRWWJiH5F5QpuLrKRcLtGee+CgyL7dtElklRWyuGv69OkiGzZ8mMhsVlnsZLPL4i6Y5NLmXp9HbqbpstgqPlZkcXExIsvL1BRe+XSdHOXcV1eg5fXJYw6xyOFms8n7y2JfosaD7/187z+9j8b73s8zMkRERGRYnMgQERGRYXEiQ0RERIbFiQwREREZVtDFvr36DxbZtu/3yRu0hYssumWiyE7l5Yrs6KmTIiuvlgVVoaXxIotpahVZsUtmlmLZVTI7e6/Idn2zQWSlZWUiu+3220XW/6q+IisrKxVZVGSkyMy69okaHpPsvGgJkVliguzk2DRGFscp6JZZ1+1ZhlarfJx119V1cnR75PPBYl+ixoPv/Xzvr9nypxrLez/PyBAREZFhcSJDREREhsWJDBERERkWJzJERERkWEEX+1a5ZDfBvQdzRFZUKbv6RUbJjopWq1x2vPjYYZHllxSLLPp4vsgSO8oukBaLPObdO+TS63u2fScyb4Xc7/TpU0U26vrr5HV1BUvyYYHbLYuddJVSVpssqPJqbk+3k2Yx0SLreLnsjvl1htyH26vrIKnbr6TbLlJT4FZRLjt/uqs1jwsRNQi+9/O9H2jc7/08I0NERESGxYkMERERGRYnMkRERGRYnMgQERGRYQVd7Pvx52tFtuWAXI7dHCU7L1YWZssdm2Wnv1ZtOoos78QRkcU2lfuwajoHZmbuF9mBHbK4q/DojyK7Z+a9Iht/000i0xZFaZZAdzhkgZs1RD78oZql3C2ajo8WzbLtZiWPBZpj6dczVWQZrWUHzoN7dgV1LLr5sM3uFJmryiUyj0ces0+zDDwRNQy+9/O9/2zH0lje+3lGhoiIiAyLExkiIiIyLE5kiIiIyLA4kSEiIiLDCrrYt9wjN23RuovIjh6WS7QX5B0VmeuU7J4Y19whspiEbiKrVrK4a99+uRx7SZ4s5CrKl8cydvz1IrvuBpkpTcdCe6hdZLqiqDC7Zll5TQvEEM11Tdrt5GNgMsnnyOuTBVVdOsnCugfm3C+yvz/1V5Fl7tsjsogouTR8Sbns0GjSFHLplq7X3V8iahh87+d7P9C43/t5RoaIiIgMixMZIiIiMixOZIiIiMiwOJEhIiIiwwq62PeKnn1Etuq/20XmqpIFRpHNZOfApild5XaRsiNgqE12OywuLRLZ4Sx5LJX5suDrmuFDRTZ56gyRtWrVUmRejyxismi6StrtsghMV8Jk1hQ26TobulyyK6I1RO7XptlvmEM+plVe2Rky5wdZqHfy5EmRRTeRxV0OzT6KSgtFZtYsU6/r7qh7TImoYfC9n+/9QON+7+cZGSIiIjIsTmSIiIjIsDiRISIiIsPiRIaIiIgMy6SUpgqHiIiIyAB4RoaIiIgMixMZIiIiMixOZIiIiMiwOJEhIiIiw+JEhoiIiAyLExkiIiIyLE5kiIiIyLA4kSEiIiLD4kSGiIiIDOv/ARtZKmaSBji7AAAAAElFTkSuQmCC\",\n      \"text/plain\": [\n       \"<Figure size 700x300 with 3 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    }\n   ],\n   \"source\": [\n    \"image1, image2 = split_data(\\n\",\n    \"    image=image,\\n\",\n    \"    slicex=(slice(0, 32), slice(0, 32)),\\n\",\n    \"    slicey=(slice(0, 20), slice(12, 32)),\\n\",\n    \"    angle=90,\\n\",\n    \"    plot=True,\\n\",\n    \")\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 5,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"\\n\",\n      \"==== BEST RESULT ====\\n\",\n      \"Best MSE: 1.3111979166666667\\n\",\n      \"Best rotation: 270\\n\",\n      \"image1's shape: (20, 32)\\n\",\n      \"image2's shape: (20, 32)\\n\",\n      \"shared image's top-left in image1: Coordinate(x=0, y=12)\\n\",\n      \"shared image's bottom-right in image1: Coordinate(x=32, y=20)\\n\",\n      \"shared image's top-left in (rotated) image2: Coordinate(x=0, y=0)\\n\",\n      \"shared image's bottom-right in (rotated) image2: Coordinate(x=32, y=8)\\n\",\n      \"shared image's height: 8\\n\",\n      \"shared image's width: 32\\n\"\n     ]\n    },\n    {\n     \"data\": {\n      \"image/png\": 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\",\n      \"text/plain\": [\n       \"<Figure size 600x300 with 2 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"image/png\": 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\",\n      \"text/plain\": [\n       \"<Figure size 600x300 with 2 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"image/png\": 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\",\n      \"text/plain\": [\n       \"<Figure size 300x300 with 1 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    }\n   ],\n   \"source\": [\n    \"merged_image, cand = main(image1, image2, min_overlap=(8, 8), verbose=False)\\n\",\n    \"result_visualize(image1, image2, merged_image, cand)\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"### Example 2.\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 6,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"image/png\": \"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\",\n      \"text/plain\": [\n       \"<Figure size 700x300 with 3 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    }\n   ],\n   \"source\": [\n    \"image1, image2 = split_data(\\n\",\n    \"    image=image,\\n\",\n    \"    slicex=(slice(0, 25), slice(7, 32)),\\n\",\n    \"    slicey=(slice(0, 25), slice(7, 32)),\\n\",\n    \"    angle=90,\\n\",\n    \"    plot=True,\\n\",\n    \")\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 7,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"\\n\",\n      \"==== BEST RESULT ====\\n\",\n      \"Best MSE: 1.2119341563786008\\n\",\n      \"Best rotation: 270\\n\",\n      \"image1's shape: (25, 25)\\n\",\n      \"image2's shape: (25, 25)\\n\",\n      \"shared image's top-left in image1: Coordinate(x=7, y=7)\\n\",\n      \"shared image's bottom-right in image1: Coordinate(x=25, y=25)\\n\",\n      \"shared image's top-left in (rotated) image2: Coordinate(x=0, y=0)\\n\",\n      \"shared image's bottom-right in (rotated) image2: Coordinate(x=18, y=18)\\n\",\n      \"shared image's height: 18\\n\",\n      \"shared image's width: 18\\n\"\n     ]\n    },\n    {\n     \"data\": {\n      \"image/png\": 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\",\n      \"text/plain\": [\n       \"<Figure size 600x300 with 2 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"image/png\": 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\",\n      \"text/plain\": [\n       \"<Figure size 600x300 with 2 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"image/png\": 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\",\n      \"text/plain\": [\n       \"<Figure size 300x300 with 1 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    }\n   ],\n   \"source\": [\n    \"merged_image, cand = main(image1, image2, min_overlap=(8, 8), verbose=False)\\n\",\n    \"result_visualize(image1, image2, merged_image, cand)\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"### Example 3.\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 8,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"image/png\": \"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\",\n      \"text/plain\": [\n       \"<Figure size 700x300 with 3 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    }\n   ],\n   \"source\": [\n    \"image1, image2 = split_data(\\n\",\n    \"    image=image,\\n\",\n    \"    slicex=(slice(12, 30), slice(0, 32)),\\n\",\n    \"    slicey=(slice(0, 25), slice(7, 32)),\\n\",\n    \"    angle=90,\\n\",\n    \"    plot=True,\\n\",\n    \")\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 9,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"\\n\",\n      \"==== BEST RESULT ====\\n\",\n      \"Best MSE: 1.3549382716049383\\n\",\n      \"Best rotation: 270\\n\",\n      \"image1's shape: (25, 18)\\n\",\n      \"image2's shape: (25, 32)\\n\",\n      \"shared image's top-left in image1: Coordinate(x=0, y=7)\\n\",\n      \"shared image's bottom-right in image1: Coordinate(x=18, y=25)\\n\",\n      \"shared image's top-left in (rotated) image2: Coordinate(x=12, y=0)\\n\",\n      \"shared image's bottom-right in (rotated) image2: Coordinate(x=30, y=18)\\n\",\n      \"shared image's height: 18\\n\",\n      \"shared image's width: 20\\n\"\n     ]\n    },\n    {\n     \"data\": {\n      \"image/png\": 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\",\n      \"text/plain\": [\n       \"<Figure size 600x300 with 2 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"image/png\": 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\",\n      \"text/plain\": [\n       \"<Figure size 600x300 with 2 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"image/png\": 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\",\n      \"text/plain\": [\n       \"<Figure size 300x300 with 1 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    }\n   ],\n   \"source\": [\n    \"merged_image, cand = main(image1, image2, min_overlap=(8, 8), verbose=False)\\n\",\n    \"result_visualize(image1, image2, merged_image, cand)\"\n   ]\n  },\n  {\n   \"cell_type\": \"markdown\",\n   \"metadata\": {},\n   \"source\": [\n    \"### Example 4.\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 10,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"data\": {\n      \"image/png\": 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\",\n      \"text/plain\": [\n       \"<Figure size 700x300 with 3 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    }\n   ],\n   \"source\": [\n    \"image1, image2 = split_data(\\n\",\n    \"    image=image,\\n\",\n    \"    slicex=(slice(7, 25), slice(0, 32)),\\n\",\n    \"    slicey=(slice(7, 25), slice(4, 28)),\\n\",\n    \"    angle=0,\\n\",\n    \"    plot=True,\\n\",\n    \")\"\n   ]\n  },\n  {\n   \"cell_type\": \"code\",\n   \"execution_count\": 11,\n   \"metadata\": {},\n   \"outputs\": [\n    {\n     \"name\": \"stdout\",\n     \"output_type\": \"stream\",\n     \"text\": [\n      \"\\n\",\n      \"==== BEST RESULT ====\\n\",\n      \"Best MSE: 0.0\\n\",\n      \"Best rotation: 0\\n\",\n      \"image1's shape: (18, 18)\\n\",\n      \"image2's shape: (24, 32)\\n\",\n      \"shared image's top-left in image1: Coordinate(x=0, y=0)\\n\",\n      \"shared image's bottom-right in image1: Coordinate(x=18, y=18)\\n\",\n      \"shared image's top-left in (rotated) image2: Coordinate(x=7, y=3)\\n\",\n      \"shared image's bottom-right in (rotated) image2: Coordinate(x=25, y=21)\\n\",\n      \"shared image's height: 21\\n\",\n      \"shared image's width: 25\\n\"\n     ]\n    },\n    {\n     \"data\": {\n      \"image/png\": 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\",\n      \"text/plain\": [\n       \"<Figure size 600x300 with 2 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"image/png\": 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\",\n      \"text/plain\": [\n       \"<Figure size 600x300 with 2 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    },\n    {\n     \"data\": {\n      \"image/png\": 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\",\n      \"text/plain\": [\n       \"<Figure size 300x300 with 1 Axes>\"\n      ]\n     },\n     \"metadata\": {},\n     \"output_type\": \"display_data\"\n    }\n   ],\n   \"source\": [\n    \"merged_image, cand = main(image1, image2, min_overlap=(8, 8), verbose=False)\\n\",\n    \"result_visualize(image1, image2, merged_image, cand)\"\n   ]\n  }\n ],\n \"metadata\": {\n  \"kernelspec\": {\n   \"display_name\": \".venv\",\n   \"language\": \"python\",\n   \"name\": \"python3\"\n  },\n  \"language_info\": {\n   \"codemirror_mode\": {\n    \"name\": \"ipython\",\n    \"version\": 3\n   },\n   \"file_extension\": \".py\",\n   \"mimetype\": \"text/x-python\",\n   \"name\": \"python\",\n   \"nbconvert_exporter\": \"python\",\n   \"pygments_lexer\": \"ipython3\",\n   \"version\": \"3.10.14\"\n  },\n  \"orig_nbformat\": 4\n },\n \"nbformat\": 4,\n \"nbformat_minor\": 2\n}\n"
  },
  {
    "path": "poetry.toml",
    "content": "[virtualenvs]\nin-project = true\npath = \".venv\"\n"
  },
  {
    "path": "pyproject.toml",
    "content": "[tool.poetry]\nname = \"image-stitcher\"\nversion = \"0.1.0\"\ndescription = \"\"\nauthors = [\"naoki <u429561d@ecs.osaka-u.ac.jp>\"]\nreadme = \"README.md\"\npackage-mode = false\n\n[tool.poetry.group.dev.dependencies]\nruff = \"^0.4.9\"\n\n[project]\nname = \"image-stitcher\"\nversion = \"0.1.0\"\ndescription = \"Personal Python Template\"\nreadme = \"README.md\"\n\n[tool.poetry.dependencies]\npython = \">=3.10,<3.11\"\nnumpy = \"^1.24.3\"\npandas = \"^2.0.2\"\nmatplotlib = \"^3.7.1\"\nscikit-learn = \"^1.2.2\"\njupyter = \"^1.0.0\"\nipykernel = \"^6.23.2\"\nseaborn = \"^0.12.2\"\ntqdm = \"^4.65.0\"\npygithub = \"^1.58.2\"\n\nscikit-image = \"^0.24.0\"\n[tool.poetry.dev-dependencies]\npre-commit = \"^2.18.1\"\ntaskipy = \"^1.10.1\"\nmypy = \"^0.990\"\npep8-naming = \"^0.12.1\"\npytest = \"^7.1.1\"\npytest-mock = \"^3.7.0\"\npytest-cov = \"^3.0.0\"\nSphinx = \"^4.5.0\"\nsphinx-rtd-theme = \"^1.0.0\"\nsphinx-pyproject = \"^0.1.0\"\n\n[tool.ruff]\ntarget-version = \"py39\"\nline-length = 119\n\n[tool.ruff.lint]\nselect = [\"E\", \"W\", \"F\", \"C\"]\nfixable = [\"ALL\"]\n\n[tool.ruff.format]\nquote-style = \"double\"\n\n[tool.mypy]\nshow_error_context = true\nshow_column_numbers = true\nignore_missing_imports = true\ndisallow_untyped_defs = true\nno_implicit_optional = true\nwarn_return_any = true\nwarn_unused_ignores = true\nwarn_redundant_casts = true\n\n[tool.sphinx-pyproject]\nproject = \"image-stitcher\"\ncopyright = \"2023, naoki\"\nlanguage = \"en\"\npackage_root = \"image-stitcher\"\nhtml_theme = \"sphinx_rtd_theme\"\ntodo_include_todos = true\ntemplates_path = [\"_templates\"]\nhtml_static_path = [\"_static\"]\nextensions = [\n  \"sphinx.ext.autodoc\",\n  \"sphinx.ext.viewcode\",\n  \"sphinx.ext.todo\",\n  \"sphinx.ext.napoleon\",\n]\n"
  },
  {
    "path": "src/__init__.py",
    "content": ""
  },
  {
    "path": "src/main.py",
    "content": "import dataclasses\n\nimport numpy as np\nfrom skimage.metrics import mean_squared_error\nfrom skimage.transform import rotate\n\n\n@dataclasses.dataclass\nclass Coordinate:\n    x: int\n    y: int\n\n\ndef main(image1, image2, min_overlap=(5, 5), verbose=False):\n    h1, w1, _ = image1.shape\n    h2, w2, _ = image2.shape\n    min_h, min_w = min_overlap\n    core_x1 = [0, w1]\n    core_y1 = [0, h1]\n\n    cand = init_candparam()\n    for angle in [0, 90, 180, 270]:\n        # 画像を回転\n        _image2 = rotate(image2, angle, resize=True, preserve_range=True).astype(np.uint8)\n        h2, w2, _ = _image2.shape\n        core_x2 = [0, w2]\n        core_y2 = [0, h2]\n        for hc in range(min_h, max(h1, h2) + 1):\n            for wc in range(min_w, max(w1, w2) + 1):\n                for ix in range(2):\n                    for iy in range(2):\n                        topleft1 = Coordinate(\n                            min(core_x1[ix] + (-1) ** ix * max(wc - w2, 0), core_x1[ix] + (-1) ** ix * min(wc, w1)),\n                            min(core_y1[iy] + (-1) ** iy * max(hc - h2, 0), core_y1[iy] + (-1) ** iy * min(hc, h1)),\n                        )\n                        bottomright1 = Coordinate(\n                            max(core_x1[ix] + (-1) ** ix * max(wc - w2, 0), core_x1[ix] + (-1) ** ix * min(wc, w1)),\n                            max(core_y1[iy] + (-1) ** iy * max(hc - h2, 0), core_y1[iy] + (-1) ** iy * min(hc, h1)),\n                        )\n                        overlap1 = image1[topleft1.y : bottomright1.y, topleft1.x : bottomright1.x, :]\n                        if verbose:\n                            print(f\"image1's top-left: {topleft1}\")\n                            print(f\"image1's bottom-right: {bottomright1}\")\n                        topleft2 = Coordinate(\n                            min(\n                                core_x2[ix ^ 1] + (-1) ** (ix ^ 1) * max(wc - w1, 0),\n                                core_x2[ix ^ 1] + (-1) ** (ix ^ 1) * min(wc, w2),\n                            ),\n                            min(\n                                core_y2[iy ^ 1] + (-1) ** (iy ^ 1) * max(hc - h1, 0),\n                                core_y2[iy ^ 1] + (-1) ** (iy ^ 1) * min(hc, h2),\n                            ),\n                        )\n                        bottomright2 = Coordinate(\n                            max(\n                                core_x2[ix ^ 1] + (-1) ** (ix ^ 1) * max(wc - w1, 0),\n                                core_x2[ix ^ 1] + (-1) ** (ix ^ 1) * min(wc, w2),\n                            ),\n                            max(\n                                core_y2[iy ^ 1] + (-1) ** (iy ^ 1) * max(hc - h1, 0),\n                                core_y2[iy ^ 1] + (-1) ** (iy ^ 1) * min(hc, h2),\n                            ),\n                        )\n                        overlap2 = _image2[topleft2.y : bottomright2.y, topleft2.x : bottomright2.x, :]\n                        if verbose:\n                            print(f\"image2's top-left: {topleft2}\")\n                            print(f\"image2's bottom-right: {bottomright2}\")\n                        mse = mean_squared_error(overlap1, overlap2)\n                        if mse < cand[\"best_mse\"]:\n                            cand[\"best_mse\"] = mse\n                            cand[\"best_rotation\"] = angle\n                            cand[\"topleft1\"] = topleft1\n                            cand[\"topleft2\"] = topleft2\n                            cand[\"bottomright1\"] = bottomright1\n                            cand[\"bottomright2\"] = bottomright2\n                            cand[\"height\"] = hc\n                            cand[\"width\"] = wc\n\n    revised_image2 = rotate(image2, cand[\"best_rotation\"], resize=True, preserve_range=True).astype(np.uint8)\n    h2, w2, _ = revised_image2.shape\n    hc, wc = cand[\"height\"], cand[\"width\"]\n    merged_image = np.zeros((h1 + h2 - cand[\"height\"], w1 + w2 - cand[\"width\"], 3), dtype=np.uint8)\n    merged_image = np.zeros(\n        (max(h1, h2) + max(min(h1, h2) - cand[\"height\"], 0), max(w1, w2) + max(min(w1, w2) - cand[\"width\"], 0), 3),\n        dtype=np.uint8,\n    )\n    merged_image[:, :, 0] = 255\n    hm, wm, _ = merged_image.shape\n\n    print(\"\\n==== BEST RESULT ====\")\n    print(f'Best MSE: {cand[\"best_mse\"]}')\n    print(f'Best rotation: {cand[\"best_rotation\"]}')\n    print(f\"image1's shape: ({h1}, {w1})\")\n    print(f\"image2's shape: ({h2}, {w2})\")\n    print(f'shared image\\'s top-left in image1: {cand[\"topleft1\"]}')\n    print(f'shared image\\'s bottom-right in image1: {cand[\"bottomright1\"]}')\n    print(f'shared image\\'s top-left in (rotated) image2: {cand[\"topleft2\"]}')\n    print(f'shared image\\'s bottom-right in (rotated) image2: {cand[\"bottomright2\"]}')\n    print(f\"shared image's height: {hc}\")\n    print(f\"shared image's width: {wc}\")\n\n    left1 = 1 if cand[\"topleft1\"].x == 0 else 0\n    left2 = 1 if cand[\"topleft2\"].x == 0 else 0\n    top1 = 1 if cand[\"topleft1\"].y == 0 else 0\n    top2 = 1 if cand[\"topleft2\"].y == 0 else 0\n    merged_image[(h2 - hc) * top1 : h1 + (h2 - hc) * top1, (w2 - wc) * left1 : w1 + (w2 - wc) * left1, :] = image1\n    merged_image[(h1 - hc) * top2 : h2 + (h1 - hc) * top2, (w1 - wc) * left2 : w2 + (w1 - wc) * left2, :] = (\n        revised_image2\n    )\n\n    return merged_image, cand\n\n\ndef init_candparam():\n    return {\n        \"best_mse\": float(\"inf\"),\n        \"best_rotation\": None,\n        \"topleft1\": None,\n        \"topleft2\": None,\n        \"bottomright1\": None,\n        \"bottomright2\": None,\n        \"height\": None,\n        \"width\": None,\n    }\n"
  },
  {
    "path": "src/utils/__init__.py",
    "content": ""
  },
  {
    "path": "src/utils/visualizer.py",
    "content": "import matplotlib.pyplot as plt\nimport numpy as np\nfrom matplotlib.patches import Rectangle\nfrom skimage.transform import rotate\n\n\ndef result_visualize(image1, image2, merged_image, cand):\n    fig, ax = plt.subplots(1, 2, figsize=(6, 3))\n    h1, w1, _ = image1.shape\n    h2, w2, _ = image2.shape\n    hm, wm, _ = merged_image.shape\n\n    revised_image1 = np.zeros_like(merged_image)\n    revised_image1[:, :, :] = 255\n    revised_image1[(hm - h1) // 2 : (hm + h1) // 2, (wm - w1) // 2 : (wm + w1) // 2] = image1\n    revised_image2 = np.zeros_like(merged_image)\n    revised_image2[:, :, :] = 255\n    revised_image2[(hm - h2) // 2 : (hm + h2) // 2, (wm - w2) // 2 : (wm + w2) // 2] = image2\n\n    ax[0].imshow(revised_image1)\n    ax[0].set_title(\"Image1\")\n\n    ax[1].imshow(revised_image2)\n    ax[1].set_title(\"Image2\")\n\n    fig.suptitle(\"Input Images\")\n    fig.align_labels()\n    fig.tight_layout()\n\n    fig, ax = plt.subplots(1, 2, figsize=(6, 3))\n\n    rotated_image2 = rotate(image2, cand[\"best_rotation\"], resize=True, preserve_range=True).astype(np.uint8)\n    h2, w2, _ = rotated_image2.shape\n    revised_image2 = np.zeros_like(merged_image)\n    revised_image2[:, :, :] = 255\n    revised_image2[(hm - h2) // 2 : (hm + h2) // 2, (wm - w2) // 2 : (wm + w2) // 2] = rotated_image2\n\n    hc = min(cand[\"height\"], h1, h2)\n    wc = min(cand[\"width\"], w1, w2)\n    rect1 = Rectangle(\n        (cand[\"topleft1\"].x + (wm - w1) // 2, cand[\"topleft1\"].y + (hm - h1) // 2),\n        wc - 1,\n        hc - 1,\n        linewidth=7,\n        edgecolor=\"g\",\n        facecolor=\"none\",\n    )\n    rect2 = Rectangle(\n        (cand[\"topleft2\"].x + (wm - w2) // 2, cand[\"topleft2\"].y + (hm - h2) // 2),\n        wc - 1,\n        hc - 1,\n        linewidth=7,\n        edgecolor=\"g\",\n        facecolor=\"none\",\n    )\n\n    ax[0].add_patch(rect1)\n    ax[1].add_patch(rect2)\n\n    ax[0].imshow(revised_image1)\n    ax[0].set_title(\"Image1\")\n\n    ax[1].imshow(revised_image2)\n    ax[1].set_title(\"Image2\")\n\n    fig.suptitle(f\"Rotated Input Images ({cand['best_rotation']}°)\")\n    fig.align_labels()\n    fig.tight_layout()\n\n    fig, ax = plt.subplots(1, 1, figsize=(3, 3))\n\n    ax.imshow(merged_image)\n    ax.set_title(\"Merged Image\")\n\n    fig.align_labels()\n    fig.tight_layout()\n\n    plt.show()\n"
  }
]