Datasetpublic

OpenScientificCodeRegistry/Database

Open Scientific Code Registry (OSCR): the authors' scripts The code published by the authors of open-access neuroscience papers, as found and verified by Open Scientific Code Registry (OSCR). Each file is here exactly as it is at the source, at the verified commit, under the license of its repository. 421,275 unique files (3,782 MB of text) from 8,849 repositories, in 24 Parquet block(s). Only files whose repository's license allows redistribution, confirmed by the repository's… See the full description on the dataset page: https://huggingface.co/datasets/OpenScientificCodeRegistry/Database.

sourceHugging Faceotherupdated 2d agoView on Hugging Face

0likes5.6kdownloads

rootmanifests07github.com__neheller__kits21.json

github.com__neheller__kits21.json192 linesDownload Raw Back to 07

1{2 "format": "oscr-script-manifest/1",3 "repository": "github.com/neheller/kits21",4 "url": "https://github.com/neheller/kits21",5 "host": "github.com",6 "commit": "04728e4b3026922303b0de46de32c890434e157c",7 "license": "MIT",8 "license_confirmed_by": "license file LICENSE",9 "redistribution": "yes",10 "files": [11  {12   "path": "LICENSE",13   "sha256": "32214956d024945a4b7695cfb0a2c1d6ee342963ff72912892ed45c23dd22ad2",14   "language": "License",15   "lines": 21,16   "truncated": false,17   "block": 14,18   "row": 1698119  },20  {21   "path": "README.md",22   "sha256": "b38d07c4ba65a36af9ba2699a4677b4c7c8c8f21514e736bc06267d71361bcd0",23   "language": "Text",24   "lines": 135,25   "truncated": false,26   "block": 16,27   "row": 752628  },29  {30   "path": "examples/submission/dummy_submission/run_inference.py",31   "sha256": "e378d1738462c9c51eff739844b4e9979cd6910ba49696fca2c7e0ceb9a22b25",32   "language": "Python",33   "lines": 121,34   "truncated": false,35   "block": 15,36   "row": 1554837  },38  {39   "path": "examples/submission/nnUNet_submission/run_inference.py",40   "sha256": "f825676c71631d3d231f82d3a8fe8be65d543ec1c203aabc4d550a860cae9ea0",41   "language": "Python",42   "lines": 144,43   "truncated": false,44   "block": 15,45   "row": 1744446  },47  {48   "path": "examples/submission/nnUNet_submission/run_inference_ensembling.py",49   "sha256": "19a381d684fe7dad2576d49123f493547ec4d1d1672eb027282d28c21d12b31b",50   "language": "Python",51   "lines": 181,52   "truncated": false,53   "block": 15,54   "row": 1959555  },56  {57   "path": "kits21/annotation/import.py",58   "sha256": "720116fb57ea2bd229f6c07eb95f9d999a6a3973b3bfaf6543ae5c1010db06c0",59   "language": "Python",60   "lines": 342,61   "truncated": false,62   "block": 15,63   "row": 2305164  },65  {66   "path": "kits21/annotation/postprocessing.py",67   "sha256": "15f2ddc1fe982e24b06896be94991ce494298252a4db494a6f686681a1b2c3dd",68   "language": "Python",69   "lines": 749,70   "truncated": false,71   "block": 15,72   "row": 2581573  },74  {75   "path": "kits21/annotation/sample_segmentations.py",76   "sha256": "c84a415bea386f84f1280e6f0e803054fc9a0ed12ff9723b8e9d24b909eaecb9",77   "language": "Python",78   "lines": 158,79   "truncated": false,80   "block": 15,81   "row": 1966282  },83  {84   "path": "kits21/configuration/labels.py",85   "sha256": "5d5275a8d5a6fa02eac4d2bce496e11a248555fb52ba9f44ef0fea7ffb7374ca",86   "language": "Python",87   "lines": 35,88   "truncated": false,89   "block": 15,90   "row": 865291  },92  {93   "path": "kits21/configuration/paths.py",94   "sha256": "c957dabfce54c560e57a8650a590f6c42a50157e70a5aeab347f0ac5d3047874",95   "language": "Python",96   "lines": 9,97   "truncated": false,98   "block": 15,99   "row": 6663100  },101  {102   "path": "kits21/evaluation/compute_tolerances.py",103   "sha256": "d0f25b85e7bc48c67ae8cd5a1da938c0589fe5407676a72c0e5b510d3580f725",104   "language": "Python",105   "lines": 108,106   "truncated": false,107   "block": 15,108   "row": 16025109  },110  {111   "path": "kits21/evaluation/evaluate_predictions.py",112   "sha256": "3d2fd1c83c7086f7af4b464967f3c22359548f2328a449955e14d78a20bc4a19",113   "language": "Python",114   "lines": 28,115   "truncated": false,116   "block": 15,117   "row": 11506118  },119  {120   "path": "kits21/evaluation/inter_rater_disagreement.py",121   "sha256": "08ede79a958e1c65ab6696d6b3d90d45a24b06712ad68f4716c32856391d0c56",122   "language": "Python",123   "lines": 77,124   "truncated": false,125   "block": 15,126   "row": 13810127  },128  {129   "path": "kits21/evaluation/metrics.py",130   "sha256": "5f041e94e89417a1b30f786ab14184242fcbc61249de3ea30bde7921402b3c0b",131   "language": "Python",132   "lines": 220,133   "truncated": false,134   "block": 15,135   "row": 21930136  },137  {138   "path": "kits21/starter_code/get_imaging.jl",139   "sha256": "205234e379861d2142807ff6f3e18bd23e9c7504433755b0ac8f684b703b9ce5",140   "language": "Julia",141   "lines": 42,142   "truncated": false,143   "block": 14,144   "row": 14017145  },146  {147   "path": "kits21/starter_code/get_imaging.m",148   "sha256": "dd86c9f8744b0894d2ecfce9f8f5ab6571b970a35a775384f6b805f2959dce2b",149   "language": "MATLAB",150   "lines": 11,151   "truncated": false,152   "block": 14,153   "row": 18362154  },155  {156   "path": "kits21/starter_code/get_imaging.py",157   "sha256": "eb0dc1a98a444b3db5a29368ec4bbc5cfddc9751edaee219941a7765cf02dbca",158   "language": "Python",159   "lines": 57,160   "truncated": false,161   "block": 15,162   "row": 9744163  },164  {165   "path": "kits21/starter_code/get_imaging.sh",166   "sha256": "ff95af2970f4cdda36d6efa1272ce0587164b853f9e26d6927acb5f58d42e14b",167   "language": "Shell",168   "lines": 19,169   "truncated": false,170   "block": 16,171   "row": 4977172  },173  {174   "path": "kits21/starter_code/get_imaging_v2.py",175   "sha256": "6cb0ff7aaa0098c54930bbb07b6b1667c64f47ac7018eb68c322255bf7542826",176   "language": "Python",177   "lines": 55,178   "truncated": false,179   "block": 15,180   "row": 9550181  },182  {183   "path": "setup.py",184   "sha256": "a7cf47a8ba4ff45d1a991ef4f146b451d1cbc58715b7d2cad81dd479a6873705",185   "language": "Python",186   "lines": 21,187   "truncated": false,188   "block": 15,189   "row": 6878190  }191 ]192}