{
  "id": 467100,
  "title": "All submitions get submition scoring error",
  "url": "/competitions/blood-vessel-segmentation/discussion/467100",
  "author_name": "",
  "post_date": "2024-01-11T05:55:26.849464500Z",
  "votes": 1,
  "comment_count": 2,
  "views": 0,
  "content": "<p>I have submitted a lot of code these days, but all the results are submission scoring errors. Can someone help me?</p>",
  "messages": [
    {
      "id": "2596490",
      "postDate": "01/11/2024 05:55:26",
      "content": "<p>I have submitted a lot of code these days, but all the results are submission scoring errors. Can someone help me?</p>",
      "rawMarkdown": "I have submitted a lot of code these days, but all the results are submission scoring errors. Can someone help me?",
      "votes": null
    },
    {
      "id": "2597351",
      "postDate": "01/11/2024 16:30:58",
      "content": "<p>You can try this as a dummy submission. I had the same problem and this code should be fine</p>\n<pre><code>TEST_PATH = \ntest_datasets_dirs = {\n    dataset_name: os.path.join(TEST_PATH, dataset_name)\n     dataset_name  test_datasets \n}\n()\n{: , : }\nid_regex = \ntest_datasets_paths = {\n   dataset_name: [\n       {\n           : os.path.join(os.path.join(test_dataset, ), image_id),\n           : \n       }  image_id  (os.listdir(os.path.join(test_dataset, ))) \n   ]  dataset_name, test_dataset  test_datasets_dirs.items()\n}\n(test_datasets_paths)\n{: [{: ,\n   : },\n  {: ,\n   : },\n  {: ,\n   : }],\n : [{: ,\n   : },\n  {: ,\n   : },\n  {: ,\n   : }]}\n dataset_name, test_data  test_datasets_paths.items():\n    idx, batch  (test_data):\n       (dataset_name, idx)\n       rle_predictions = \n       submission_data = {: batch[], : rle_predictions}\n      current_submission = pd.DataFrame(data= submission_data, index=[])\n       submission.append(current_submission)\nsubmission_df = pd.concat(submission)\nsubmission_df.to_csv(, index=)\n(submission)\nkidney_5 \nkidney_5 \nkidney_5 \nkidney_6 \nkidney_6 \nkidney_6 \n[                rle\n  kidney_5_0000   ,                 rle\n  kidney_5_0001   ,                 rle\n  kidney_5_0002   ,                 rle\n  kidney_6_0000   ,                 rle\n  kidney_6_0001   ,                 rle\n  kidney_6_0002   ]\n</code></pre>",
      "rawMarkdown": "You can try this as a dummy submission. I had the same problem and this code should be fine\n\n```\n>>> TEST_PATH = \"/kaggle/input/blood-vessel-segmentation/test\"\n>>> test_datasets_dirs = {\n>>>     dataset_name: os.path.join(TEST_PATH, dataset_name)\n>>>     for dataset_name in test_datasets \n>>> }\n>>> print(f\"{test_datasets_dirs}\")\n{'kidney_5': '/kaggle/input/blood-vessel-segmentation/test/kidney_5', 'kidney_6': '/kaggle/input/blood-vessel-segmentation/test/kidney_6'}\n>>> id_regex = r'[aA-zZ\\.]'\n>>> test_datasets_paths = {\n>>>    dataset_name: [\n>>>        {\n>>>            \"image\": os.path.join(os.path.join(test_dataset, \"images\"), image_id),\n>>>            \"id\": f\"{dataset_name}_{re.sub(id_regex, '', image_id):04}\"\n>>>        } for image_id in sorted(os.listdir(os.path.join(test_dataset, \"images\"))) \n>>>    ] for dataset_name, test_dataset in test_datasets_dirs.items()\n>>> }\n>>> print(test_datasets_paths)\n{'kidney_5': [{'image': '/kaggle/input/blood-vessel-segmentation/test/kidney_5/images/0000.tif',\n   'id': 'kidney_5_0000'},\n  {'image': '/kaggle/input/blood-vessel-segmentation/test/kidney_5/images/0001.tif',\n   'id': 'kidney_5_0001'},\n  {'image': '/kaggle/input/blood-vessel-segmentation/test/kidney_5/images/0002.tif',\n   'id': 'kidney_5_0002'}],\n 'kidney_6': [{'image': '/kaggle/input/blood-vessel-segmentation/test/kidney_6/images/0000.tif',\n   'id': 'kidney_6_0000'},\n  {'image': '/kaggle/input/blood-vessel-segmentation/test/kidney_6/images/0001.tif',\n   'id': 'kidney_6_0001'},\n  {'image': '/kaggle/input/blood-vessel-segmentation/test/kidney_6/images/0002.tif',\n   'id': 'kidney_6_0002'}]}\n>>> for dataset_name, test_data in test_datasets_paths.items():\n>>>    for idx, batch in enumerate(test_data):\n>>>        print(dataset_name, idx)\n>>>        rle_predictions = '1 0'\n>>>        submission_data = {\"id\": batch[\"id\"], \"rle\": rle_predictions}\n>>>       current_submission = pd.DataFrame(data= submission_data, index=[0])\n>>>        submission.append(current_submission)\n>>> submission_df = pd.concat(submission)\n>>> submission_df.to_csv(\"submission.csv\", index=False)\n>>> print(submission)\nkidney_5 0\nkidney_5 1\nkidney_5 2\nkidney_6 0\nkidney_6 1\nkidney_6 2\n[              id  rle\n0  kidney_5_0000  1 0,               id  rle\n0  kidney_5_0001  1 0,               id  rle\n0  kidney_5_0002  1 0,               id  rle\n0  kidney_6_0000  1 0,               id  rle\n0  kidney_6_0001  1 0,               id  rle\n0  kidney_6_0002  1 0]\n```",
      "votes": null
    },
    {
      "id": "2612181",
      "postDate": "01/21/2024 08:44:30",
      "content": "<p>I think you should make all id in the test dataset, 6images are not the whole test set , they just a sample </p>",
      "rawMarkdown": "I think you should make all id in the test dataset, 6images are not the whole test set , they just a sample",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 2597351,
      "author_name": "fmgsf12",
      "author_url": "",
      "post_date": "01/11/2024 16:30:58",
      "content": "<p>You can try this as a dummy submission. I had the same problem and this code should be fine</p>\n<pre><code>TEST_PATH = \ntest_datasets_dirs = {\n    dataset_name: os.path.join(TEST_PATH, dataset_name)\n     dataset_name  test_datasets \n}\n()\n{: , : }\nid_regex = \ntest_datasets_paths = {\n   dataset_name: [\n       {\n           : os.path.join(os.path.join(test_dataset, ), image_id),\n           : \n       }  image_id  (os.listdir(os.path.join(test_dataset, ))) \n   ]  dataset_name, test_dataset  test_datasets_dirs.items()\n}\n(test_datasets_paths)\n{: [{: ,\n   : },\n  {: ,\n   : },\n  {: ,\n   : }],\n : [{: ,\n   : },\n  {: ,\n   : },\n  {: ,\n   : }]}\n dataset_name, test_data  test_datasets_paths.items():\n    idx, batch  (test_data):\n       (dataset_name, idx)\n       rle_predictions = \n       submission_data = {: batch[], : rle_predictions}\n      current_submission = pd.DataFrame(data= submission_data, index=[])\n       submission.append(current_submission)\nsubmission_df = pd.concat(submission)\nsubmission_df.to_csv(, index=)\n(submission)\nkidney_5 \nkidney_5 \nkidney_5 \nkidney_6 \nkidney_6 \nkidney_6 \n[                rle\n  kidney_5_0000   ,                 rle\n  kidney_5_0001   ,                 rle\n  kidney_5_0002   ,                 rle\n  kidney_6_0000   ,                 rle\n  kidney_6_0001   ,                 rle\n  kidney_6_0002   ]\n</code></pre>",
      "votes": null,
      "replies": [
        {
          "id": 2612181,
          "author_name": "athrunzala",
          "author_url": "",
          "post_date": "01/21/2024 08:44:30",
          "content": "<p>I think you should make all id in the test dataset, 6images are not the whole test set , they just a sample </p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "2596490": "I have submitted a lot of code these days, but all the results are submission scoring errors. Can someone help me?",
    "2597351": "You can try this as a dummy submission. I had the same problem and this code should be fine\n\n```\n>>> TEST_PATH = \"/kaggle/input/blood-vessel-segmentation/test\"\n>>> test_datasets_dirs = {\n>>>     dataset_name: os.path.join(TEST_PATH, dataset_name)\n>>>     for dataset_name in test_datasets \n>>> }\n>>> print(f\"{test_datasets_dirs}\")\n{'kidney_5': '/kaggle/input/blood-vessel-segmentation/test/kidney_5', 'kidney_6': '/kaggle/input/blood-vessel-segmentation/test/kidney_6'}\n>>> id_regex = r'[aA-zZ\\.]'\n>>> test_datasets_paths = {\n>>>    dataset_name: [\n>>>        {\n>>>            \"image\": os.path.join(os.path.join(test_dataset, \"images\"), image_id),\n>>>            \"id\": f\"{dataset_name}_{re.sub(id_regex, '', image_id):04}\"\n>>>        } for image_id in sorted(os.listdir(os.path.join(test_dataset, \"images\"))) \n>>>    ] for dataset_name, test_dataset in test_datasets_dirs.items()\n>>> }\n>>> print(test_datasets_paths)\n{'kidney_5': [{'image': '/kaggle/input/blood-vessel-segmentation/test/kidney_5/images/0000.tif',\n   'id': 'kidney_5_0000'},\n  {'image': '/kaggle/input/blood-vessel-segmentation/test/kidney_5/images/0001.tif',\n   'id': 'kidney_5_0001'},\n  {'image': '/kaggle/input/blood-vessel-segmentation/test/kidney_5/images/0002.tif',\n   'id': 'kidney_5_0002'}],\n 'kidney_6': [{'image': '/kaggle/input/blood-vessel-segmentation/test/kidney_6/images/0000.tif',\n   'id': 'kidney_6_0000'},\n  {'image': '/kaggle/input/blood-vessel-segmentation/test/kidney_6/images/0001.tif',\n   'id': 'kidney_6_0001'},\n  {'image': '/kaggle/input/blood-vessel-segmentation/test/kidney_6/images/0002.tif',\n   'id': 'kidney_6_0002'}]}\n>>> for dataset_name, test_data in test_datasets_paths.items():\n>>>    for idx, batch in enumerate(test_data):\n>>>        print(dataset_name, idx)\n>>>        rle_predictions = '1 0'\n>>>        submission_data = {\"id\": batch[\"id\"], \"rle\": rle_predictions}\n>>>       current_submission = pd.DataFrame(data= submission_data, index=[0])\n>>>        submission.append(current_submission)\n>>> submission_df = pd.concat(submission)\n>>> submission_df.to_csv(\"submission.csv\", index=False)\n>>> print(submission)\nkidney_5 0\nkidney_5 1\nkidney_5 2\nkidney_6 0\nkidney_6 1\nkidney_6 2\n[              id  rle\n0  kidney_5_0000  1 0,               id  rle\n0  kidney_5_0001  1 0,               id  rle\n0  kidney_5_0002  1 0,               id  rle\n0  kidney_6_0000  1 0,               id  rle\n0  kidney_6_0001  1 0,               id  rle\n0  kidney_6_0002  1 0]\n```",
    "2612181": "I think you should make all id in the test dataset, 6images are not the whole test set , they just a sample"
  },
  "source": "meta"
}