{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"gpu","dataSources":[{"sourceId":49349,"databundleVersionId":5447706,"sourceType":"competition"},{"sourceId":7408522,"sourceType":"datasetVersion","datasetId":4308858}],"isInternetEnabled":false,"language":"python","sourceType":"notebook","isGpuEnabled":true}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"### Cloning our project into Kaggle","metadata":{"editable":false}},{"cell_type":"code","source":"!cp /kaggle/input/with-splitting/submission_withsplitting.csv /kaggle/working/submission.csv","metadata":{"execution":{"iopub.status.busy":"2024-01-15T17:44:32.688856Z","iopub.execute_input":"2024-01-15T17:44:32.689780Z","iopub.status.idle":"2024-01-15T17:44:33.635336Z","shell.execute_reply.started":"2024-01-15T17:44:32.689745Z","shell.execute_reply":"2024-01-15T17:44:33.634257Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# %load_ext autoreload\n# %autoreload 2\n\n# %rm -rf ./kp_imc23\n# !git clone --branch kaggle_raphv2_kevin https://github.com/RaphaelHaddad/3D_reconstruction_Tsinghua_2023.git\n\n# %cd \"./3D_reconstruction_Tsinghua_2023/\"\n# %mv * ../\n# %cd ..\n# %rm -r \"3D_reconstruction_Tsinghua_2023\"","metadata":{"execution":{"iopub.status.busy":"2024-01-15T17:38:34.135930Z","iopub.execute_input":"2024-01-15T17:38:34.136629Z","iopub.status.idle":"2024-01-15T17:38:50.694225Z","shell.execute_reply.started":"2024-01-15T17:38:34.136597Z","shell.execute_reply":"2024-01-15T17:38:50.693148Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# !pip install -r requirements.txt","metadata":{"execution":{"iopub.status.idle":"2024-01-15T17:09:52.273829Z","shell.execute_reply.started":"2024-01-15T17:09:39.944227Z","shell.execute_reply":"2024-01-15T17:09:52.272614Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# import os\n# from pipeline import main\n# import gc\n# import time\n\n# os.environ['TRANSFORMERS_CACHE'] = './weights/'\n\n# def get_directory_names(directory_path):\n#     # Get a list of all entries (files and directories) in the specified directory\n#     entries = os.listdir(directory_path)\n#     # Filter only directories\n#     directories = [entry for entry in entries if os.path.isdir(os.path.join(directory_path, entry))]\n#     return directories\n\n# def measure_runtime(func, *args, **kwargs):\n#     start_time = time.time()\n#     func(*args, **kwargs)\n#     end_time = time.time()\n#     runtime_ms = (end_time - start_time) * 1000\n#     return runtime_ms\n\n# # Test if data is available else train\n# mode = \"test\" if len(os.listdir(\"/kaggle/input/image-matching-challenge-2023/test\")) > 1 else \"train\"\n# print(f\"Mode: {mode}\")\n\n# datasets = get_directory_names(f\"/kaggle/input/image-matching-challenge-2023/{mode}\")\n\n# !rm -f \"/kaggle/working/submission.csv\"\n\n# def run_pipeline():\n#     for dataset in datasets:\n#     #for dataset in [\"phototourism\"]:\n#         scenes = get_directory_names(f\"/kaggle/input/image-matching-challenge-2023/{mode}/{dataset}\")\n#         for scene in scenes:\n#         #for scene in [\"trevi_fountain\"]:\n#             gc.collect()\n#             !rm -rf output\n#             out_results = main(\n#                 data_dir=\"/kaggle/input/image-matching-challenge-2023\",\n#                 dataset=dataset,\n#                 scene=scene,\n#                 mode=mode,\n#                 preprocess_matcher=[\"lightglue\"], # \"lightglue\" \"loftr\" \"dkm\"\n#                 num_pairs=30,\n#                 submission_path=\"/kaggle/working/submission.csv\"\n#                 #with_splitting=True\n#             )\n\n# runtime = measure_runtime(run_pipeline)\n# print(f\"Runtime: {runtime / 1000}s / {runtime:.2f}ms\")","metadata":{"execution":{"iopub.status.busy":"2024-01-15T17:31:22.841555Z","iopub.execute_input":"2024-01-15T17:31:22.842301Z","iopub.status.idle":"2024-01-15T17:31:22.904819Z","shell.execute_reply.started":"2024-01-15T17:31:22.842262Z","shell.execute_reply":"2024-01-15T17:31:22.903626Z"},"trusted":true},"execution_count":null,"outputs":[]}]}