![\"\"](\"https://i.postimg.cc/MKw8HPWQ/faster-eval-why-error-Kaggle-5-24-2021-3-59-11-PM.png\")
\nif there is an Index Error: there won't be an h variable which you are checking in
if h in res1. hence get into error and the whole-cell failsI made 6 submissions, but I get an error. I don't know where to look for her anymore. Can anyone suggest how to find and fix it?
", "messages": [ { "id": "1320652", "postDate": "05/24/2021 08:16:54", "content": "I made 6 submissions, but I get an error. I don't know where to look for her anymore. Can anyone suggest how to find and fix it?
", "rawMarkdown": "I made 6 submissions, but I get an error. I don't know where to look for her anymore. Can anyone suggest how to find and fix it?", "votes": null }, { "id": "1320658", "postDate": "05/24/2021 08:23:53", "content": "You had 5 submission successful or all of the them were failed
", "rawMarkdown": "You had 5 submission successful or all of the them were failed", "votes": null }, { "id": "1320699", "postDate": "05/24/2021 08:51:40", "content": "Successful - Submission Scoring Error
", "rawMarkdown": "Successful - Submission Scoring Error", "votes": null }, { "id": "1320750", "postDate": "05/24/2021 09:59:00", "content": "Okay:
\nThere is a couple of things i would ask you to check in your code:
Is your notebook using the x-ray cached dataset of @xhlulu or are you doing caching in your notebook. I mean you should do the same code as @xhlulu did in the notebook?. Or if you are a PyTorch user. Are you decoding the Dicom file in the Dataset Class
Are you giving the submission file in the same way as mention on the evaluation page. I mean like this
Id,PredictionString\n2b95d54e4be65_study,negative 1 0 0 1 1\n2b95d54e4be66_study,typical 1 0 0 1 1\n2b95d54e4be67_study,indeterminate 1 0 0 1 1 atypical 1 0 0 1 1\n2b95d54e4be68_image,none 1 0 0 1 1\n2b95d54e4be69_image,opacity 0.5 100 100 200 200 opacity 0.7 10 10 20 20\netc.\n!!!!! Sorry for the lots of questions !!!!
", "rawMarkdown": "Okay:\nThere is a couple of things i would ask you to check in your code:\n\n- Is your notebook using the x-ray cached dataset of @xhlulu or are you doing caching in your notebook. I mean you should do the same code as @xhlulu did in the notebook?. Or if you are a PyTorch user. Are you decoding the Dicom file in the Dataset Class\n\n- Are you giving the submission file in the same way as mention on the evaluation page. I mean like this\n```\nId,PredictionString\n2b95d54e4be65_study,negative 1 0 0 1 1\n2b95d54e4be66_study,typical 1 0 0 1 1\n2b95d54e4be67_study,indeterminate 1 0 0 1 1 atypical 1 0 0 1 1\n2b95d54e4be68_image,none 1 0 0 1 1\n2b95d54e4be69_image,opacity 0.5 100 100 200 200 opacity 0.7 10 10 20 20\netc.\n```\n - or if there are any values getting into error. I mean the conf values fails in the way and having a NaN in the submission file\n\n\n!!!!! Sorry for the lots of questions !!!!", "votes": null }, { "id": "1320761", "postDate": "05/24/2021 10:04:00", "content": "I had trouble understanding the code.
\nI don't know whether I am right or wrong. I never worked in a CSV writer library. Anyway, I think there might be someone who could help you more than me. I found a possible bug(not Sure it causes any errors)
\nif there is an Index Error: there won't be an h variable which you are checking in if h in res1. hence get into error and the whole-cell fails
I don't know whether the code has trouble in mapping the study level image names and image-level image names. as you do in the code.
\ncan you try doing one more thing out here?
\n![\"\"](\"https://i.postimg.cc/sDWvd0TG/faster-eval-why-error-Kaggle-5-24-2021-4-03-20-PM.png\")
df1 = pd.read_csv('./submission_study.csv')\ndf2 = pd.read_csv('./submission_image.csv')\ndf3 = pd.concat([df1, df2], ignore_index=True)\ndf_jpg = df_jpg.drop(['PredictionString'],axis = 1)\nfinal_df = pd.merge(df3,df_jpg,on = 'id').reset_index(drop = True)\nfinal_df.to_csv('./submission.csv', index=False)\nthe exception is more of a precaution in case an empty string is received. checked your code and got 6 extra lines of study - isn't that a problem?
", "rawMarkdown": "the exception is more of a precaution in case an empty string is received. checked your code and got 6 extra lines of study - isn't that a problem?", "votes": null }, { "id": "1320932", "postDate": "05/24/2021 12:28:47", "content": "try submitting it
", "rawMarkdown": "try submitting it", "votes": null }, { "id": "1321031", "postDate": "05/24/2021 13:41:14", "content": "unfortunately error. do not contact the support service with this question?
", "rawMarkdown": "unfortunately error. do not contact the support service with this question?", "votes": null }, { "id": "1321062", "postDate": "05/24/2021 13:54:21", "content": "Nevertheless thank you
", "rawMarkdown": "Nevertheless thank you", "votes": null }, { "id": "1324902", "postDate": "05/27/2021 10:30:55", "content": "started writing the file using pandas - the error was gone. most likely there was an error somewhere in the code related to writing the submission file
", "rawMarkdown": "started writing the file using pandas - the error was gone. most likely there was an error somewhere in the code related to writing the submission file", "votes": null }, { "id": "1387455", "postDate": "07/14/2021 07:43:18", "content": "I am getting this same \"Submission Scoring Error\" and I am not able to fix it. It is not happening when I directly rename the sample_submission.csv file to submission.csv file. However, when I try to concat image level and study level data frames, I get the error. Here is my code:
\ncls_df = pd.read_csv(\"../input/siim-covid-subs/sample_submission_study_level.csv\")\ndet_df = pd.read_csv(\"../input/siim-covid-subs/sample_submission_image_level.csv\")\ndf = cls_df.append(det_df).reset_index(drop=True)\n# df = pd.read_csv(\"../input/siim-covid19-detection/sample_submission.csv\")\ndf.to_csv(\"/kaggle/working/submission.csv\", index=False)\n# print(df.head)\nprint('Done writing submission.csv!')\nthe reason for submission scoring error is because the kaggle submission system cannot find the private rows in it. the sample_submission while submitting wont be in same shape which we can see in public
", "rawMarkdown": "the reason for submission scoring error is because the kaggle submission system cannot find the private rows in it. the sample_submission while submitting wont be in same shape which we can see in public", "votes": null }, { "id": "1387506", "postDate": "07/14/2021 08:36:10", "content": "Thanks @morizin but how do I fix it? Do we have to iterate the sample_submission file in our inference for loop? I have been strugging with this for 1 week now!
", "rawMarkdown": "Thanks @morizin but how do I fix it? Do we have to iterate the sample_submission file in our inference for loop? I have been strugging with this for 1 week now!", "votes": null }, { "id": "1387519", "postDate": "07/14/2021 08:46:21", "content": "load the sample submission. and merge you combined csv_file(study and image level)
\nyou can do as follow
import pandas as pd\n\nfast_sub_study = pd.read_csv('../input/siim-subs-for-fast-sub/sub1_study.csv')\nfast_sub_image = pd.read_csv('../input/siim-subs-for-fast-sub/sub1_image.csv')\n\nsample_submission = pd.read_csv('../input/siim-covid19-detection/sample_submission.csv')\nstudy_sample = sample_submission[sample_submission.id.str.contains('study')]\\\n .drop(['PredictionString'],axis = 1).reset_index(drop = True)\nimage_sample = sample_submission[sample_submission.id.str.contains('image')]\\\n .drop(['PredictionString'],axis = 1).reset_index(drop = True)\n\nstudy_submission = fast_sub_study[fast_sub_study.id.str.contains('study')].reset_index(drop = True)\nimage_submission = fast_sub_image[fast_sub_image.id.str.contains('image')].reset_index(drop = True)\n\npd.concat([study_sample.merge(study_submission, on = 'id', how = 'outer').fillna('negative 1 0 0 1 1'),\\\n image_sample.merge(image_submission, on = 'id', how = 'outer').fillna('none 1 0 0 1 1')])\\\n .reset_index(drop = True).to_csv('submission.csv', index = False)\nthats too long. but works . never tried to look for an optimized one
", "rawMarkdown": "load the sample submission. and merge you combined csv_file(study and image level)\nyou can do as follow\n```\nimport pandas as pd\n\nfast_sub_study = pd.read_csv('../input/siim-subs-for-fast-sub/sub1_study.csv')\nfast_sub_image = pd.read_csv('../input/siim-subs-for-fast-sub/sub1_image.csv')\n\nsample_submission = pd.read_csv('../input/siim-covid19-detection/sample_submission.csv')\nstudy_sample = sample_submission[sample_submission.id.str.contains('study')]\\\n .drop(['PredictionString'],axis = 1).reset_index(drop = True)\nimage_sample = sample_submission[sample_submission.id.str.contains('image')]\\\n .drop(['PredictionString'],axis = 1).reset_index(drop = True)\n\nstudy_submission = fast_sub_study[fast_sub_study.id.str.contains('study')].reset_index(drop = True)\nimage_submission = fast_sub_image[fast_sub_image.id.str.contains('image')].reset_index(drop = True)\n\npd.concat([study_sample.merge(study_submission, on = 'id', how = 'outer').fillna('negative 1 0 0 1 1'),\\\n image_sample.merge(image_submission, on = 'id', how = 'outer').fillna('none 1 0 0 1 1')])\\\n .reset_index(drop = True).to_csv('submission.csv', index = False)\n```\nthats too long. but works . never tried to look for an optimized one", "votes": null } ], "comments": [ { "id": 1320658, "author_name": "morizin", "author_url": "", "post_date": "05/24/2021 08:23:53", "content": "You had 5 submission successful or all of the them were failed
", "votes": null, "replies": [ { "id": 1320699, "author_name": "zaakciiru", "author_url": "", "post_date": "05/24/2021 08:51:40", "content": "Successful - Submission Scoring Error
", "votes": null, "replies": [] }, { "id": 1320750, "author_name": "morizin", "author_url": "", "post_date": "05/24/2021 09:59:00", "content": "Okay:
\nThere is a couple of things i would ask you to check in your code:
Is your notebook using the x-ray cached dataset of @xhlulu or are you doing caching in your notebook. I mean you should do the same code as @xhlulu did in the notebook?. Or if you are a PyTorch user. Are you decoding the Dicom file in the Dataset Class
Are you giving the submission file in the same way as mention on the evaluation page. I mean like this
Id,PredictionString\n2b95d54e4be65_study,negative 1 0 0 1 1\n2b95d54e4be66_study,typical 1 0 0 1 1\n2b95d54e4be67_study,indeterminate 1 0 0 1 1 atypical 1 0 0 1 1\n2b95d54e4be68_image,none 1 0 0 1 1\n2b95d54e4be69_image,opacity 0.5 100 100 200 200 opacity 0.7 10 10 20 20\netc.\n!!!!! Sorry for the lots of questions !!!!
", "votes": null, "replies": [] }, { "id": 1320761, "author_name": "zaakciiru", "author_url": "", "post_date": "05/24/2021 10:04:00", "content": "I had trouble understanding the code.
\nI don't know whether I am right or wrong. I never worked in a CSV writer library. Anyway, I think there might be someone who could help you more than me. I found a possible bug(not Sure it causes any errors)
\nif there is an Index Error: there won't be an h variable which you are checking in if h in res1. hence get into error and the whole-cell fails
I don't know whether the code has trouble in mapping the study level image names and image-level image names. as you do in the code.
\ncan you try doing one more thing out here?
\n
df1 = pd.read_csv('./submission_study.csv')\ndf2 = pd.read_csv('./submission_image.csv')\ndf3 = pd.concat([df1, df2], ignore_index=True)\ndf_jpg = df_jpg.drop(['PredictionString'],axis = 1)\nfinal_df = pd.merge(df3,df_jpg,on = 'id').reset_index(drop = True)\nfinal_df.to_csv('./submission.csv', index=False)\nthe exception is more of a precaution in case an empty string is received. checked your code and got 6 extra lines of study - isn't that a problem?
", "votes": null, "replies": [] }, { "id": 1320932, "author_name": "morizin", "author_url": "", "post_date": "05/24/2021 12:28:47", "content": "try submitting it
", "votes": null, "replies": [] }, { "id": 1321031, "author_name": "zaakciiru", "author_url": "", "post_date": "05/24/2021 13:41:14", "content": "unfortunately error. do not contact the support service with this question?
", "votes": null, "replies": [] } ] }, { "id": 1321062, "author_name": "zaakciiru", "author_url": "", "post_date": "05/24/2021 13:54:21", "content": "Nevertheless thank you
", "votes": null, "replies": [] }, { "id": 1324902, "author_name": "zaakciiru", "author_url": "", "post_date": "05/27/2021 10:30:55", "content": "started writing the file using pandas - the error was gone. most likely there was an error somewhere in the code related to writing the submission file
", "votes": null, "replies": [] }, { "id": 1387455, "author_name": "kalpanki", "author_url": "", "post_date": "07/14/2021 07:43:18", "content": "I am getting this same \"Submission Scoring Error\" and I am not able to fix it. It is not happening when I directly rename the sample_submission.csv file to submission.csv file. However, when I try to concat image level and study level data frames, I get the error. Here is my code:
\ncls_df = pd.read_csv(\"../input/siim-covid-subs/sample_submission_study_level.csv\")\ndet_df = pd.read_csv(\"../input/siim-covid-subs/sample_submission_image_level.csv\")\ndf = cls_df.append(det_df).reset_index(drop=True)\n# df = pd.read_csv(\"../input/siim-covid19-detection/sample_submission.csv\")\ndf.to_csv(\"/kaggle/working/submission.csv\", index=False)\n# print(df.head)\nprint('Done writing submission.csv!')\nthe reason for submission scoring error is because the kaggle submission system cannot find the private rows in it. the sample_submission while submitting wont be in same shape which we can see in public
", "votes": null, "replies": [] }, { "id": 1387506, "author_name": "kalpanki", "author_url": "", "post_date": "07/14/2021 08:36:10", "content": "Thanks @morizin but how do I fix it? Do we have to iterate the sample_submission file in our inference for loop? I have been strugging with this for 1 week now!
", "votes": null, "replies": [] }, { "id": 1387519, "author_name": "morizin", "author_url": "", "post_date": "07/14/2021 08:46:21", "content": "load the sample submission. and merge you combined csv_file(study and image level)
\nyou can do as follow
import pandas as pd\n\nfast_sub_study = pd.read_csv('../input/siim-subs-for-fast-sub/sub1_study.csv')\nfast_sub_image = pd.read_csv('../input/siim-subs-for-fast-sub/sub1_image.csv')\n\nsample_submission = pd.read_csv('../input/siim-covid19-detection/sample_submission.csv')\nstudy_sample = sample_submission[sample_submission.id.str.contains('study')]\\\n .drop(['PredictionString'],axis = 1).reset_index(drop = True)\nimage_sample = sample_submission[sample_submission.id.str.contains('image')]\\\n .drop(['PredictionString'],axis = 1).reset_index(drop = True)\n\nstudy_submission = fast_sub_study[fast_sub_study.id.str.contains('study')].reset_index(drop = True)\nimage_submission = fast_sub_image[fast_sub_image.id.str.contains('image')].reset_index(drop = True)\n\npd.concat([study_sample.merge(study_submission, on = 'id', how = 'outer').fillna('negative 1 0 0 1 1'),\\\n image_sample.merge(image_submission, on = 'id', how = 'outer').fillna('none 1 0 0 1 1')])\\\n .reset_index(drop = True).to_csv('submission.csv', index = False)\nthats too long. but works . never tried to look for an optimized one
", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "1320652": "I made 6 submissions, but I get an error. I don't know where to look for her anymore. Can anyone suggest how to find and fix it?", "1320658": "You had 5 submission successful or all of the them were failed", "1320699": "Successful - Submission Scoring Error", "1320750": "Okay:\nThere is a couple of things i would ask you to check in your code:\n\n- Is your notebook using the x-ray cached dataset of @xhlulu or are you doing caching in your notebook. I mean you should do the same code as @xhlulu did in the notebook?. Or if you are a PyTorch user. Are you decoding the Dicom file in the Dataset Class\n\n- Are you giving the submission file in the same way as mention on the evaluation page. I mean like this\n```\nId,PredictionString\n2b95d54e4be65_study,negative 1 0 0 1 1\n2b95d54e4be66_study,typical 1 0 0 1 1\n2b95d54e4be67_study,indeterminate 1 0 0 1 1 atypical 1 0 0 1 1\n2b95d54e4be68_image,none 1 0 0 1 1\n2b95d54e4be69_image,opacity 0.5 100 100 200 200 opacity 0.7 10 10 20 20\netc.\n```\n - or if there are any values getting into error. I mean the conf values fails in the way and having a NaN in the submission file\n\n\n!!!!! Sorry for the lots of questions !!!!", "1320761": "1. converted files separately and converted in the sending code\n2. I am using pytorch\n3. file of sending in the format of the competition.\n4. https: //www.kaggle.com/zaakciiru/faster-eval-why-error\nthank you", "1320811": "I had trouble understanding the code. \nI don't know whether I am right or wrong. I never worked in a CSV writer library. Anyway, I think there might be someone who could help you more than me. I found a possible bug(not Sure it causes any errors)\n\n\nif there is an Index Error: there won't be an h variable which you are checking in `if h in res1`. hence get into error and the whole-cell fails\n\nI don't know whether the code has trouble in mapping the study level image names and image-level image names. as you do in the code.\n\ncan you try doing one more thing out here?\n\n\n```\n\ndf1 = pd.read_csv('./submission_study.csv')\ndf2 = pd.read_csv('./submission_image.csv')\ndf3 = pd.concat([df1, df2], ignore_index=True)\ndf_jpg = df_jpg.drop(['PredictionString'],axis = 1)\nfinal_df = pd.merge(df3,df_jpg,on = 'id').reset_index(drop = True)\nfinal_df.to_csv('./submission.csv', index=False)\n\n```", "1320915": "the exception is more of a precaution in case an empty string is received. checked your code and got 6 extra lines of study - isn't that a problem?", "1320932": "try submitting it", "1321031": "unfortunately error. do not contact the support service with this question?", "1321062": "Nevertheless thank you", "1324902": "started writing the file using pandas - the error was gone. most likely there was an error somewhere in the code related to writing the submission file", "1387455": "I am getting this same \"Submission Scoring Error\" and I am not able to fix it. It is not happening when I directly rename the sample_submission.csv file to submission.csv file. However, when I try to concat image level and study level data frames, I get the error. Here is my code:\n\n```\ncls_df = pd.read_csv(\"../input/siim-covid-subs/sample_submission_study_level.csv\")\ndet_df = pd.read_csv(\"../input/siim-covid-subs/sample_submission_image_level.csv\")\ndf = cls_df.append(det_df).reset_index(drop=True)\n# df = pd.read_csv(\"../input/siim-covid19-detection/sample_submission.csv\")\ndf.to_csv(\"/kaggle/working/submission.csv\", index=False)\n# print(df.head)\nprint('Done writing submission.csv!')\n```", "1387473": "the reason for submission scoring error is because the kaggle submission system cannot find the private rows in it. the sample_submission while submitting wont be in same shape which we can see in public", "1387506": "Thanks @morizin but how do I fix it? Do we have to iterate the sample_submission file in our inference for loop? I have been strugging with this for 1 week now!", "1387519": "load the sample submission. and merge you combined csv_file(study and image level)\nyou can do as follow\n```\nimport pandas as pd\n\nfast_sub_study = pd.read_csv('../input/siim-subs-for-fast-sub/sub1_study.csv')\nfast_sub_image = pd.read_csv('../input/siim-subs-for-fast-sub/sub1_image.csv')\n\nsample_submission = pd.read_csv('../input/siim-covid19-detection/sample_submission.csv')\nstudy_sample = sample_submission[sample_submission.id.str.contains('study')]\\\n .drop(['PredictionString'],axis = 1).reset_index(drop = True)\nimage_sample = sample_submission[sample_submission.id.str.contains('image')]\\\n .drop(['PredictionString'],axis = 1).reset_index(drop = True)\n\nstudy_submission = fast_sub_study[fast_sub_study.id.str.contains('study')].reset_index(drop = True)\nimage_submission = fast_sub_image[fast_sub_image.id.str.contains('image')].reset_index(drop = True)\n\npd.concat([study_sample.merge(study_submission, on = 'id', how = 'outer').fillna('negative 1 0 0 1 1'),\\\n image_sample.merge(image_submission, on = 'id', how = 'outer').fillna('none 1 0 0 1 1')])\\\n .reset_index(drop = True).to_csv('submission.csv', index = False)\n```\nthats too long. but works . never tried to look for an optimized one" }, "source": "meta" }