{ "id": 208364, "title": "Submission Scoring Error", "url": "/competitions/hubmap-kidney-segmentation/discussion/208364", "author_name": "", "post_date": "2021-01-03T05:12:53.602751Z", "votes": 2, "comment_count": 4, "views": 0, "content": "

Hello, below is the submission file I made. After performing the RLE, the restore was confirmed as normal.

\n

However, score measurements are not allowed in the kaggle.

\n

Can I know the reason why?

\n

Thank you.

\n

\"\"

", "messages": [ { "id": "1136467", "postDate": "01/03/2021 05:12:53", "content": "

Hello, below is the submission file I made. After performing the RLE, the restore was confirmed as normal.

\n

However, score measurements are not allowed in the kaggle.

\n

Can I know the reason why?

\n

Thank you.

\n

\"\"

", "rawMarkdown": "Hello, below is the submission file I made. After performing the RLE, the restore was confirmed as normal.\n\nHowever, score measurements are not allowed in the kaggle.\n\nCan I know the reason why?\n\nThank you.\n\n![](https://i.imgur.com/JVCdUXX.png)", "votes": null }, { "id": "1136505", "postDate": "01/03/2021 06:37:24", "content": "

Did you check your predicted mask?
\nI trained my model by 0~1 scale image, but I use 0~255 scale images to inference by mistake.
\nThe inference made strange masks and score measurements weren't allowed in Submission. Check your input image's scale.

", "rawMarkdown": "Did you check your predicted mask?\nI trained my model by 0~1 scale image, but I use 0~255 scale images to inference by mistake.\nThe inference made strange masks and score measurements weren't allowed in Submission. Check your input image's scale.", "votes": null }, { "id": "1136605", "postDate": "01/03/2021 08:39:57", "content": "

Yes, I checked and there's no problem.
\nI compared here's submission.csv and my submission.csv.
\nBut I can't still found any difference.

", "rawMarkdown": "Yes, I checked and there's no problem.\nI compared [here](https://www.kaggle.com/sumitjha19/densenet121unet-inference/data)'s submission.csv and my [submission.csv](https://www.dropbox.com/s/tqn8be1503dka01/submission2.csv?dl=0). \nBut I can't still found any difference.", "votes": null }, { "id": "1136912", "postDate": "01/03/2021 14:28:23", "content": "

🤔🤔 I restored the submission.csv. but I couldn't found problems.
\nThe last thing to guess is you predict only public images, not private images.
\nbut If you made your code same here's, the guess is probably wrong.

", "rawMarkdown": "🤔🤔 I restored the submission.csv. but I couldn't found problems. \nThe last thing to guess is you predict only public images, not private images.\nbut If you made your code same [here](https://www.kaggle.com/sumitjha19/densenet121unet-inference/data)'s, the guess is probably wrong.", "votes": null }, { "id": "1145679", "postDate": "01/09/2021 09:38:50", "content": "

I faced a similar issue

", "rawMarkdown": "I faced a similar issue", "votes": null } ], "comments": [ { "id": 1136505, "author_name": "curiosity806", "author_url": "", "post_date": "01/03/2021 06:37:24", "content": "

Did you check your predicted mask?
\nI trained my model by 0~1 scale image, but I use 0~255 scale images to inference by mistake.
\nThe inference made strange masks and score measurements weren't allowed in Submission. Check your input image's scale.

", "votes": null, "replies": [ { "id": 1136605, "author_name": "springnode", "author_url": "", "post_date": "01/03/2021 08:39:57", "content": "

Yes, I checked and there's no problem.
\nI compared here's submission.csv and my submission.csv.
\nBut I can't still found any difference.

", "votes": null, "replies": [] }, { "id": 1136912, "author_name": "curiosity806", "author_url": "", "post_date": "01/03/2021 14:28:23", "content": "

🤔🤔 I restored the submission.csv. but I couldn't found problems.
\nThe last thing to guess is you predict only public images, not private images.
\nbut If you made your code same here's, the guess is probably wrong.

", "votes": null, "replies": [] } ] }, { "id": 1145679, "author_name": "jonbjones", "author_url": "", "post_date": "01/09/2021 09:38:50", "content": "

I faced a similar issue

", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "1136467": "Hello, below is the submission file I made. After performing the RLE, the restore was confirmed as normal.\n\nHowever, score measurements are not allowed in the kaggle.\n\nCan I know the reason why?\n\nThank you.\n\n![](https://i.imgur.com/JVCdUXX.png)", "1136505": "Did you check your predicted mask?\nI trained my model by 0~1 scale image, but I use 0~255 scale images to inference by mistake.\nThe inference made strange masks and score measurements weren't allowed in Submission. Check your input image's scale.", "1136605": "Yes, I checked and there's no problem.\nI compared [here](https://www.kaggle.com/sumitjha19/densenet121unet-inference/data)'s submission.csv and my [submission.csv](https://www.dropbox.com/s/tqn8be1503dka01/submission2.csv?dl=0). \nBut I can't still found any difference.", "1136912": "🤔🤔 I restored the submission.csv. but I couldn't found problems. \nThe last thing to guess is you predict only public images, not private images.\nbut If you made your code same [here](https://www.kaggle.com/sumitjha19/densenet121unet-inference/data)'s, the guess is probably wrong.", "1145679": "I faced a similar issue" }, "source": "meta" }