{"metadata":{"kernelspec":{"name":"python3","display_name":"Python 3","language":"python"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.10.13"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":71885,"databundleVersionId":8143495,"sourceType":"competition"}],"dockerImageVersionId":30684,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"from pathlib import Path\n\nimport cv2\nfrom matplotlib import pyplot as plt","metadata":{"execution":{"iopub.status.busy":"2024-04-13T12:45:55.389605Z","iopub.execute_input":"2024-04-13T12:45:55.390230Z","iopub.status.idle":"2024-04-13T12:45:55.669694Z","shell.execute_reply.started":"2024-04-13T12:45:55.390198Z","shell.execute_reply":"2024-04-13T12:45:55.668868Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"subfolders = [f for f in Path(\"/kaggle/input/image-matching-challenge-2024/train\").iterdir() if f.is_dir()]","metadata":{"execution":{"iopub.status.busy":"2024-04-13T12:45:55.671598Z","iopub.execute_input":"2024-04-13T12:45:55.672265Z","iopub.status.idle":"2024-04-13T12:45:55.682236Z","shell.execute_reply.started":"2024-04-13T12:45:55.672227Z","shell.execute_reply":"2024-04-13T12:45:55.681352Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"subfolders","metadata":{"execution":{"iopub.status.busy":"2024-04-13T12:45:55.685081Z","iopub.execute_input":"2024-04-13T12:45:55.685424Z","iopub.status.idle":"2024-04-13T12:45:55.692839Z","shell.execute_reply.started":"2024-04-13T12:45:55.685399Z","shell.execute_reply":"2024-04-13T12:45:55.691575Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### transp_obj_glass_cylinder","metadata":{}},{"cell_type":"code","source":"folder = subfolders[0]\nprint(folder.name)\nfolder_path = folder / \"images\"\nimages = list(folder_path.glob(\"*\"))\nimages.sort()\n\nnum = len(images)\ncolumn_num = 5\nrow_num = (num + column_num - 1) // column_num\n\nnow_row = 0\nfor each_row in range(row_num):\n    fig, axs = plt.subplots(1, column_num, figsize=(20, 10))\n\n    for i, image_path in enumerate(images[:num][now_row : now_row + column_num]):\n        image = cv2.imread(str(image_path))\n        image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n\n        ax = axs[i]\n        ax.imshow(image_rgb)\n        ax.axis(\"off\")\n\n    for j in range(i + 1, column_num):\n        fig.delaxes(axs[j])\n\n    plt.show()\n\n    now_row += column_num","metadata":{"execution":{"iopub.status.busy":"2024-04-13T12:45:55.694604Z","iopub.execute_input":"2024-04-13T12:45:55.695210Z","iopub.status.idle":"2024-04-13T12:46:04.320380Z","shell.execute_reply.started":"2024-04-13T12:45:55.695182Z","shell.execute_reply":"2024-04-13T12:46:04.317381Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### church","metadata":{}},{"cell_type":"code","source":"folder = subfolders[1]\nprint(folder.name)\nfolder_path = folder / \"images\"\nimages = list(folder_path.glob(\"*\"))\nimages.sort()\n\nnum = len(images)\ncolumn_num = 5\nrow_num = (num + column_num - 1) // column_num\n\nnow_row = 0\nfor each_row in range(row_num):\n    fig, axs = plt.subplots(1, column_num, figsize=(20, 10))\n\n    for i, image_path in enumerate(images[:num][now_row : now_row + column_num]):\n        image = cv2.imread(str(image_path))\n        image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n\n        ax = axs[i]\n        ax.imshow(image_rgb)\n        ax.axis(\"off\")\n\n    for j in range(i + 1, column_num):\n        fig.delaxes(axs[j])\n\n    plt.show()\n\n    now_row += column_num","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### lizard","metadata":{}},{"cell_type":"code","source":"folder = subfolders[2]\nprint(folder.name)\nfolder_path = folder / \"images\"\nimages = list(folder_path.glob(\"*\"))\nimages.sort()\n\nnum = len(images)\ncolumn_num = 5\nrow_num = (num + column_num - 1) // column_num\n\nnow_row = 0\nfor each_row in range(row_num):\n    fig, axs = plt.subplots(1, column_num, figsize=(20, 10))\n\n    for i, image_path in enumerate(images[:num][now_row : now_row + column_num]):\n        image = cv2.imread(str(image_path))\n        image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n\n        ax = axs[i]\n        ax.imshow(image_rgb)\n        ax.axis(\"off\")\n\n    for j in range(i + 1, column_num):\n        fig.delaxes(axs[j])\n\n    plt.show()\n\n    now_row += column_num","metadata":{"execution":{"iopub.status.busy":"2024-04-13T12:48:10.825762Z","iopub.execute_input":"2024-04-13T12:48:10.826241Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### pond","metadata":{}},{"cell_type":"code","source":"folder = subfolders[3]\nprint(folder.name)\nfolder_path = folder / \"images\"\nimages = list(folder_path.glob(\"*\"))\nimages.sort()\n\nnum = len(images)\ncolumn_num = 5\nrow_num = (num + column_num - 1) // column_num\n\nnow_row = 0\nfor each_row in range(row_num):\n    fig, axs = plt.subplots(1, column_num, figsize=(20, 10))\n\n    for i, image_path in enumerate(images[:num][now_row : now_row + column_num]):\n        image = cv2.imread(str(image_path))\n        image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n\n        ax = axs[i]\n        ax.imshow(image_rgb)\n        ax.axis(\"off\")\n\n    for j in range(i + 1, column_num):\n        fig.delaxes(axs[j])\n\n    plt.show()\n\n    now_row += column_num","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### dioscuri","metadata":{}},{"cell_type":"code","source":"folder = subfolders[4]\nprint(folder.name)\nfolder_path = folder / \"images\"\nimages = list(folder_path.glob(\"*\"))\nimages.sort()\n\nnum = len(images)\ncolumn_num = 5\nrow_num = (num + column_num - 1) // column_num\n\nnow_row = 0\nfor each_row in range(row_num):\n    fig, axs = plt.subplots(1, column_num, figsize=(20, 10))\n\n    for i, image_path in enumerate(images[:num][now_row : now_row + column_num]):\n        image = cv2.imread(str(image_path))\n        image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n\n        ax = axs[i]\n        ax.imshow(image_rgb)\n        ax.axis(\"off\")\n\n    for j in range(i + 1, column_num):\n        fig.delaxes(axs[j])\n\n    plt.show()\n\n    now_row += column_num","metadata":{"execution":{"iopub.status.busy":"2024-04-13T12:00:44.554056Z","iopub.execute_input":"2024-04-13T12:00:44.554442Z","iopub.status.idle":"2024-04-13T12:00:46.457251Z","shell.execute_reply.started":"2024-04-13T12:00:44.554410Z","shell.execute_reply":"2024-04-13T12:00:46.455275Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### multi-temporal-temple-baalshamin","metadata":{}},{"cell_type":"code","source":"folder = subfolders[5]\nprint(folder.name)\nfolder_path = folder / \"images\"\nimages = list(folder_path.glob(\"*\"))\nimages.sort()\n\nnum = len(images)\ncolumn_num = 5\nrow_num = (num + column_num - 1) // column_num\n\nnow_row = 0\nfor each_row in range(row_num):\n    fig, axs = plt.subplots(1, column_num, figsize=(20, 10))\n\n    for i, image_path in enumerate(images[:num][now_row : now_row + column_num]):\n        image = cv2.imread(str(image_path))\n        image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n\n        ax = axs[i]\n        ax.imshow(image_rgb)\n        ax.axis(\"off\")\n\n    for j in range(i + 1, column_num):\n        fig.delaxes(axs[j])\n\n    plt.show()\n\n    now_row += column_num","metadata":{"execution":{"iopub.status.busy":"2024-04-13T12:00:29.647275Z","iopub.execute_input":"2024-04-13T12:00:29.647661Z","iopub.status.idle":"2024-04-13T12:00:42.707713Z","shell.execute_reply.started":"2024-04-13T12:00:29.647632Z","shell.execute_reply":"2024-04-13T12:00:42.705756Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### transp_obj_glass_cup","metadata":{}},{"cell_type":"code","source":"folder = subfolders[6]\nprint(folder.name)\nfolder_path = folder / \"images\"\nimages = list(folder_path.glob(\"*\"))\nimages.sort()\n\nnum = len(images)\ncolumn_num = 5\nrow_num = (num + column_num - 1) // column_num\n\nnow_row = 0\nfor each_row in range(row_num):\n    fig, axs = plt.subplots(1, column_num, figsize=(20, 10))\n\n    for i, image_path in enumerate(images[:num][now_row : now_row + column_num]):\n        image = cv2.imread(str(image_path))\n        image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n\n        ax = axs[i]\n        ax.imshow(image_rgb)\n        ax.axis(\"off\")\n\n    for j in range(i + 1, column_num):\n        fig.delaxes(axs[j])\n\n    plt.show()\n\n    now_row += column_num","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### test","metadata":{}},{"cell_type":"code","source":"subfolders = [f for f in Path(\"/kaggle/input/image-matching-challenge-2024/test\").iterdir() if f.is_dir()]","metadata":{"execution":{"iopub.status.busy":"2024-04-13T11:58:00.974992Z","iopub.execute_input":"2024-04-13T11:58:00.975652Z","iopub.status.idle":"2024-04-13T11:58:00.991154Z","shell.execute_reply.started":"2024-04-13T11:58:00.975616Z","shell.execute_reply":"2024-04-13T11:58:00.990002Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"subfolders","metadata":{"execution":{"iopub.status.busy":"2024-04-13T11:58:10.636910Z","iopub.execute_input":"2024-04-13T11:58:10.637538Z","iopub.status.idle":"2024-04-13T11:58:10.642333Z","shell.execute_reply.started":"2024-04-13T11:58:10.637483Z","shell.execute_reply":"2024-04-13T11:58:10.641604Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"folder = subfolders[0]\nprint(folder.name)\nfolder_path = folder / \"images\"\nimages = list(folder_path.glob(\"*\"))\nimages.sort()\n\nnum = len(images)\ncolumn_num = 5\nrow_num = (num + column_num - 1) // column_num\n\nnow_row = 0\nfor each_row in range(row_num):\n    fig, axs = plt.subplots(1, column_num, figsize=(20, 10))\n\n    for i, image_path in enumerate(images[:num][now_row : now_row + column_num]):\n        image = cv2.imread(str(image_path))\n        image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n\n        ax = axs[i]\n        ax.imshow(image_rgb)\n        ax.axis(\"off\")\n\n    for j in range(i + 1, column_num):\n        fig.delaxes(axs[j])\n\n    plt.show()\n\n    now_row += column_num","metadata":{"execution":{"iopub.status.busy":"2024-04-13T11:58:18.211617Z","iopub.execute_input":"2024-04-13T11:58:18.212222Z","iopub.status.idle":"2024-04-13T11:58:28.989401Z","shell.execute_reply.started":"2024-04-13T11:58:18.212181Z","shell.execute_reply":"2024-04-13T11:58:28.988278Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}