Hello!
\nWelcome to I’m Something of a Painter Myself!
\nWe are super excited to have you participate in our first-ever generative getting started competition. Your task is to generate Monet-esque images, whether from scratch or by transforming photos. To learn more, check out our competition description.
\nAs a Getting Started Competition, there are no prizes, deadlines, nor private leaderboards. This competition will run indefinitely and will be a resource to become more familiar with these concepts:
\nTo get started, we have created a CycleGAN tutorial on the data, but please feel free to experiment with other architectures as well. You are welcome to add in additional datasets to help with the training of your model; just remember that submissions of actual Monet paintings and transformations of such paintings are not allowed.
\nGood luck and have fun learning to paint (using computer vision, that is)!
\nRemember: Kaggle is for everyone. Whether you're teaming up or sharing tips in the competition forum, we expect everyone to follow our Kaggle community guidelines.
", "messages": [ { "id": 989491, "postDate": "2020-08-28T20:44:21.450Z", "content": "Hello!
\nWelcome to I’m Something of a Painter Myself!
\nWe are super excited to have you participate in our first-ever generative getting started competition. Your task is to generate Monet-esque images, whether from scratch or by transforming photos. To learn more, check out our competition description.
\nAs a Getting Started Competition, there are no prizes, deadlines, nor private leaderboards. This competition will run indefinitely and will be a resource to become more familiar with these concepts:
\nTo get started, we have created a CycleGAN tutorial on the data, but please feel free to experiment with other architectures as well. You are welcome to add in additional datasets to help with the training of your model; just remember that submissions of actual Monet paintings and transformations of such paintings are not allowed.
\nGood luck and have fun learning to paint (using computer vision, that is)!
\nRemember: Kaggle is for everyone. Whether you're teaming up or sharing tips in the competition forum, we expect everyone to follow our Kaggle community guidelines.
", "rawMarkdown": "Hello!\n \nWelcome to I’m Something of a Painter Myself!\n \nWe are super excited to have you participate in our first-ever generative getting started competition. Your task is to generate Monet-esque images, whether from scratch or by transforming photos. To learn more, check out our [competition description](https://www.kaggle.com/c/gan-getting-started/overview).\n \nAs a [Getting Started Competition](https://www.kaggle.com/c/gan-getting-started/overview/frequently-asked-questions), there are no prizes, deadlines, nor private leaderboards. This competition will run indefinitely and will be a resource to become more familiar with these concepts:\n \n- Computer vision\n- Generative models\n- Tensor Processing Units (TPUs)\n- TFRecords format for TensorFlow \n \nTo get started, we have created a [CycleGAN tutorial](https://www.kaggle.com/amyjang/monet-cyclegan-tutorial) on the data, but please feel free to experiment with other architectures as well. You are welcome to add in additional datasets to help with the training of your model; just remember that submissions of actual Monet paintings and transformations of such paintings are not allowed.\n \nGood luck and have fun learning to paint (using computer vision, that is)!\n \n**Remember:** Kaggle is for everyone. Whether you're teaming up or sharing tips in the competition forum, we expect everyone to follow our [Kaggle community guidelines](https://www.kaggle.com/community-guidelines).", "votes": 53 }, { "id": 1107689, "postDate": "2020-12-09T21:43:06.560Z", "content": "Hi! I appreciate this competition, but it's not very clear from description how is the final score computed.
\nFor me, it looks like there is some \"evaluation network\" that has internal inception layer that is used to compute FID for the pair of generated and real images. But is there any information about this Inception network? Like, what is the full architecture of this network or how was it trained?
\nAlso, let's say I submit 7k generated images and there are ~300 real images. Does it compute 7000x300 FID scores and then average them?
\nThanks in advance for the clarification.
This is really a fun competition as a beginner I am truly excited to learn about GANs. Though a small request to the Kaggle team if they can make medals for this competition for further motivation. Thank you!!
\nWhat do fellow kagglers think?
Does anyone encounter problems with submitting submission file? I submitted different image sizes 128x128 and 256x256 and both received an error that the file is too big or too small. it was zipped 7k+ png files. Anyone can help?
", "rawMarkdown": "Does anyone encounter problems with submitting submission file? I submitted different image sizes 128x128 and 256x256 and both received an error that the file is too big or too small. it was zipped 7k+ png files. Anyone can help?" }, { "id": 3224529, "postDate": "2025-06-15T03:11:59.560Z", "content": "Hello everyone! I'm joining the 'I’m Something of a Painter Myself' competition. Honestly, I'm not sure if I have any artistic talent myself, but I'm really looking forward to creating new 'masterpieces' with the power of AI!
", "rawMarkdown": "Hello everyone! I'm joining the 'I’m Something of a Painter Myself' competition. Honestly, I'm not sure if I have any artistic talent myself, but I'm really looking forward to creating new 'masterpieces' with the power of AI!" }, { "id": 3181781, "postDate": "2025-04-18T10:18:24.950Z", "content": "someone please explain me as a beginner what should I do to get started in competitions. please please
", "rawMarkdown": "someone please explain me as a beginner what should I do to get started in competitions. please please", "replies": [ { "id": 3440999, "postDate": "2026-04-13T11:13:23.677Z", "content": "Hii! Check out my notebook https://www.kaggle.com/code/franekwodarczyk/impression-gan
", "rawMarkdown": "Hii! Check out my notebook https://www.kaggle.com/code/franekwodarczyk/impression-gan" } ] }, { "id": 3144685, "postDate": "2025-03-08T17:39:34.920Z", "content": "Hello everyone, I am starting to discover this challenge and was wondering if the order of images in both directories matters.Thanks
", "rawMarkdown": "Hello everyone, I am starting to discover this challenge and was wondering if the order of images in both directories matters.Thanks" }, { "id": 3022755, "postDate": "2024-10-19T22:20:09.367Z", "content": "Hello, I participated in this competition.
\nI used a GPU to calculate for several hours in Kaggle Notebook.
\nAs a result, I was able to create a painting similar to Monet.
\nThank you for providing such a fun competition.
GOOD, cannot wait to submit it
", "rawMarkdown": "GOOD, cannot wait to submit it" }, { "id": 2794747, "postDate": "2024-05-05T13:37:37.507Z", "content": "Interesting!
", "rawMarkdown": "Interesting!" }, { "id": 2693910, "postDate": "2024-03-12T18:47:02.450Z", "content": "Interesting! Feel lucky to be able to take part
", "rawMarkdown": "Interesting! Feel lucky to be able to take part" }, { "id": 2497820, "postDate": "2023-10-24T23:20:19.030Z", "content": "Hi! Looking for a team to work on competitions. Please reach out to me if you are looking for one. I am intermediate level in python and beginner level in machine learning.
", "rawMarkdown": "Hi! Looking for a team to work on competitions. Please reach out to me if you are looking for one. I am intermediate level in python and beginner level in machine learning.", "replies": [ { "id": 2884969, "postDate": "2024-06-22T20:41:30.177Z", "content": "Hello, if you are looking for another person. I am good in python and machine learning but beginner in DL
", "rawMarkdown": "Hello, if you are looking for another person. I am good in python and machine learning but beginner in DL" } ] }, { "id": 2165511, "postDate": "2023-03-02T08:48:56.797Z", "content": "This is my Second competition but actually, it would be the fist challenge for me to do about vision networks.
", "rawMarkdown": "This is my Second competition but actually, it would be the fist challenge for me to do about vision networks." }, { "id": 2031401, "postDate": "2022-11-16T03:54:06.733Z", "content": "Let's try to use diffusion model like novel ai !
", "rawMarkdown": "Let's try to use diffusion model like novel ai !" }, { "id": 1807746, "postDate": "2022-06-01T09:39:12.997Z", "content": "@amyjang Hi, thanks for this competition!
\nI'm trying to use the starter code in Colab and I* changed* the monet/photo_tfrec inputs for the monet/photo_jpeg, but I get the following errors below. Of course it works fine otherwise with the tfrecs.
\nCan anyone explain why this happens or how to use this on all of the images ano not just the tfrecs ?
\nexample_monet = next(iter(monet_ds))\nexample_photo = next(iter(photo_ds))\nThe error says: DataLossError: corrupted record at 0 [Op:IteratorGetNext]
\nThen, trying to fit the model I get something similar:
\n2 root error(s) found.\n (0) DATA_LOSS: corrupted record at 0\n [[{{node IteratorGetNext}}]]\n [[IteratorGetNext/_2]]\n (1) DATA_LOSS: corrupted record at 0\n [[{{node IteratorGetNext}}]]\n0 successful operations.\n0 derived errors ignored. [Op:__inference_train_function_57323]
For me, as novice, it was an interesting competition, from understanding simple GAN to CycleGAN with all useful notebooks and then thinking about improvements was educating and fun!
\nThanks a lot!
Totally agree with you . good start to delve onto as a beginner
", "rawMarkdown": "Totally agree with you . good start to delve onto as a beginner" } ] }, { "id": 1713549, "postDate": "2022-03-06T06:13:42.253Z", "content": "hi, it's cool
", "rawMarkdown": "hi, it's cool" }, { "id": 1535770, "postDate": "2021-10-06T07:33:34.507Z", "content": "looks good to me
", "rawMarkdown": "looks good to me" }, { "id": 1436359, "postDate": "2021-08-03T15:04:51.897Z", "content": "hi this is cool!
", "rawMarkdown": "hi this is cool!" }, { "id": 1420614, "postDate": "2021-08-03T03:24:33.400Z", "content": "Hi, thank you vey much for this kind of resources. These are very helpful for practitioners and for professionals who are seeking new challenges.
", "rawMarkdown": "Hi, thank you vey much for this kind of resources. These are very helpful for practitioners and for professionals who are seeking new challenges." }, { "id": 1276057, "postDate": "2021-04-17T03:52:58.537Z", "content": "This is really fantastic! What a beautiful mix of classical art and modern machine beauty.
", "rawMarkdown": "This is really fantastic! What a beautiful mix of classical art and modern machine beauty." }, { "id": 1079030, "postDate": "2020-11-15T14:50:19.987Z", "content": "Nice, I am currently completing this challenge but I am challenging myself by not following the template directly.
", "rawMarkdown": "Nice, I am currently completing this challenge but I am challenging myself by not following the template directly." }, { "id": 992019, "postDate": "2020-08-30T20:14:02.080Z", "content": "Thanks for your wonderful notebook !!!!!
", "rawMarkdown": "Thanks for your wonderful notebook !!!!!" }, { "id": 990205, "postDate": "2020-08-29T12:36:54.577Z", "content": "Thanks a lot for this competition! I was learning about GAN! And this came up! Really nice! And thanks a lot.
", "rawMarkdown": "Thanks a lot for this competition! I was learning about GAN! And this came up! Really nice! And thanks a lot." }, { "id": 989573, "postDate": "2020-08-28T23:41:53.073Z", "content": "This is Awesome. I'm definatley looking forward to this.
", "rawMarkdown": "This is Awesome. I'm definatley looking forward to this." }, { "id": 2946634, "postDate": "2024-08-04T14:54:05.693Z", "content": "intersting
", "rawMarkdown": "intersting", "isDeleted": true }, { "id": 999040, "postDate": "2020-09-05T09:41:15.373Z", "rawMarkdown": "", "isDeleted": true }, { "id": 3052783, "postDate": "2024-11-22T20:35:11.280Z", "content": "Interesting!
", "rawMarkdown": "Interesting!" }, { "id": 2154974, "postDate": "2023-02-22T11:07:51.677Z", "content": "Thank you!
", "rawMarkdown": "Thank you!" }, { "id": 2142109, "postDate": "2023-02-13T10:23:46.933Z", "content": "It's great, thank you
", "rawMarkdown": "It's great, thank you" }, { "id": 1935278, "postDate": "2022-09-12T01:59:38.560Z", "content": "Thanks! That is good for me!
", "rawMarkdown": "Thanks! That is good for me!" }, { "id": 1697994, "postDate": "2022-02-20T03:40:48.650Z", "content": "Thanks! It is good for me!
", "rawMarkdown": "Thanks! It is good for me!" }, { "id": 1629029, "postDate": "2021-12-25T15:31:18.497Z", "content": "hi, thanks
\nGANs are interesting 👍
Thanks ! So cool !
", "rawMarkdown": "Thanks ! So cool !" }, { "id": 1417591, "postDate": "2021-08-03T00:27:57.837Z", "content": "Thanks!! I am animated!
", "rawMarkdown": "Thanks!! I am animated!\n" }, { "id": 1395647, "postDate": "2021-07-21T12:23:41.447Z", "content": "Thanks a lot !!!
", "rawMarkdown": "Thanks a lot !!!" }, { "id": 1108849, "postDate": "2020-12-11T04:26:14.917Z", "content": "Thanks for your useful notebooks!
", "rawMarkdown": "Thanks for your useful notebooks!" }, { "id": 1046459, "postDate": "2020-10-11T17:13:52.177Z", "content": "Great notebook - thanks!
", "rawMarkdown": "Great notebook - thanks!" } ], "comments": [ { "id": 1107689, "author_name": "Ilya Komarov", "author_url": "", "post_date": "2020-12-09T21:43:06.560000", "content": "Hi! I appreciate this competition, but it's not very clear from description how is the final score computed.
\nFor me, it looks like there is some \"evaluation network\" that has internal inception layer that is used to compute FID for the pair of generated and real images. But is there any information about this Inception network? Like, what is the full architecture of this network or how was it trained?
\nAlso, let's say I submit 7k generated images and there are ~300 real images. Does it compute 7000x300 FID scores and then average them?
\nThanks in advance for the clarification.
This is really a fun competition as a beginner I am truly excited to learn about GANs. Though a small request to the Kaggle team if they can make medals for this competition for further motivation. Thank you!!
\nWhat do fellow kagglers think?
Does anyone encounter problems with submitting submission file? I submitted different image sizes 128x128 and 256x256 and both received an error that the file is too big or too small. it was zipped 7k+ png files. Anyone can help?
", "votes": 0, "replies": [] }, { "id": 3224529, "author_name": "tanakata", "author_url": "", "post_date": "2025-06-15T03:11:59.560000", "content": "Hello everyone! I'm joining the 'I’m Something of a Painter Myself' competition. Honestly, I'm not sure if I have any artistic talent myself, but I'm really looking forward to creating new 'masterpieces' with the power of AI!
", "votes": 0, "replies": [] }, { "id": 3181781, "author_name": "Madhulika Kemwal", "author_url": "", "post_date": "2025-04-18T10:18:24.950000", "content": "someone please explain me as a beginner what should I do to get started in competitions. please please
", "votes": 0, "replies": [ { "id": 3440999, "author_name": "Franek Włodarczyk", "author_url": "", "post_date": "2026-04-13T11:13:23.677000", "content": "Hii! Check out my notebook https://www.kaggle.com/code/franekwodarczyk/impression-gan
", "votes": 0, "replies": [] } ] }, { "id": 3144685, "author_name": "neseh1", "author_url": "", "post_date": "2025-03-08T17:39:34.920000", "content": "Hello everyone, I am starting to discover this challenge and was wondering if the order of images in both directories matters.Thanks
", "votes": 0, "replies": [] }, { "id": 3022755, "author_name": "Akira Hanada", "author_url": "", "post_date": "2024-10-19T22:20:09.367000", "content": "Hello, I participated in this competition.
\nI used a GPU to calculate for several hours in Kaggle Notebook.
\nAs a result, I was able to create a painting similar to Monet.
\nThank you for providing such a fun competition.
GOOD, cannot wait to submit it
", "votes": 0, "replies": [] }, { "id": 2794747, "author_name": "Rodolfo Wenceslau", "author_url": "", "post_date": "2024-05-05T13:37:37.507000", "content": "Interesting!
", "votes": 0, "replies": [] }, { "id": 2693910, "author_name": "jesthy_l", "author_url": "", "post_date": "2024-03-12T18:47:02.450000", "content": "Interesting! Feel lucky to be able to take part
", "votes": 0, "replies": [] }, { "id": 2497820, "author_name": "Suchitra Nayak", "author_url": "", "post_date": "2023-10-24T23:20:19.030000", "content": "Hi! Looking for a team to work on competitions. Please reach out to me if you are looking for one. I am intermediate level in python and beginner level in machine learning.
", "votes": 0, "replies": [ { "id": 2884969, "author_name": "AbhishekKarn", "author_url": "", "post_date": "2024-06-22T20:41:30.177000", "content": "Hello, if you are looking for another person. I am good in python and machine learning but beginner in DL
", "votes": 0, "replies": [] } ] }, { "id": 2165511, "author_name": "Leo_202311", "author_url": "", "post_date": "2023-03-02T08:48:56.797000", "content": "This is my Second competition but actually, it would be the fist challenge for me to do about vision networks.
", "votes": 0, "replies": [] }, { "id": 2031401, "author_name": "codingo", "author_url": "", "post_date": "2022-11-16T03:54:06.733000", "content": "Let's try to use diffusion model like novel ai !
", "votes": 0, "replies": [] }, { "id": 1807746, "author_name": "Gman00", "author_url": "", "post_date": "2022-06-01T09:39:12.997000", "content": "@amyjang Hi, thanks for this competition!
\nI'm trying to use the starter code in Colab and I* changed* the monet/photo_tfrec inputs for the monet/photo_jpeg, but I get the following errors below. Of course it works fine otherwise with the tfrecs.
\nCan anyone explain why this happens or how to use this on all of the images ano not just the tfrecs ?
\nexample_monet = next(iter(monet_ds))\nexample_photo = next(iter(photo_ds))\nThe error says: DataLossError: corrupted record at 0 [Op:IteratorGetNext]
\nThen, trying to fit the model I get something similar:
\n2 root error(s) found.\n (0) DATA_LOSS: corrupted record at 0\n [[{{node IteratorGetNext}}]]\n [[IteratorGetNext/_2]]\n (1) DATA_LOSS: corrupted record at 0\n [[{{node IteratorGetNext}}]]\n0 successful operations.\n0 derived errors ignored. [Op:__inference_train_function_57323]
For me, as novice, it was an interesting competition, from understanding simple GAN to CycleGAN with all useful notebooks and then thinking about improvements was educating and fun!
\nThanks a lot!
Totally agree with you . good start to delve onto as a beginner
", "votes": 0, "replies": [] } ] }, { "id": 1713549, "author_name": "wu chao qi", "author_url": "", "post_date": "2022-03-06T06:13:42.253000", "content": "hi, it's cool
", "votes": 0, "replies": [] }, { "id": 1535770, "author_name": "Halil Kasapoglu", "author_url": "", "post_date": "2021-10-06T07:33:34.507000", "content": "looks good to me
", "votes": 0, "replies": [] }, { "id": 1436359, "author_name": "Amin Ghandi", "author_url": "", "post_date": "2021-08-03T15:04:51.897000", "content": "hi this is cool!
", "votes": 0, "replies": [] }, { "id": 1420614, "author_name": "Juan Alberto Solis Castro", "author_url": "", "post_date": "2021-08-03T03:24:33.400000", "content": "Hi, thank you vey much for this kind of resources. These are very helpful for practitioners and for professionals who are seeking new challenges.
", "votes": 0, "replies": [] }, { "id": 1276057, "author_name": "FailTrain", "author_url": "", "post_date": "2021-04-17T03:52:58.537000", "content": "This is really fantastic! What a beautiful mix of classical art and modern machine beauty.
", "votes": 0, "replies": [] }, { "id": 1079030, "author_name": "AlexanderWhelan", "author_url": "", "post_date": "2020-11-15T14:50:19.987000", "content": "Nice, I am currently completing this challenge but I am challenging myself by not following the template directly.
", "votes": 0, "replies": [] }, { "id": 992019, "author_name": "Manh Lab", "author_url": "", "post_date": "2020-08-30T20:14:02.080000", "content": "Thanks for your wonderful notebook !!!!!
", "votes": 0, "replies": [] }, { "id": 990205, "author_name": "soham mukherjee", "author_url": "", "post_date": "2020-08-29T12:36:54.577000", "content": "Thanks a lot for this competition! I was learning about GAN! And this came up! Really nice! And thanks a lot.
", "votes": 0, "replies": [] }, { "id": 989573, "author_name": "William Green", "author_url": "", "post_date": "2020-08-28T23:41:53.073000", "content": "This is Awesome. I'm definatley looking forward to this.
", "votes": 0, "replies": [] }, { "id": 2946634, "author_name": "", "author_url": "", "post_date": "2024-08-04T14:54:05.693000", "content": "intersting
", "votes": 0, "replies": [] }, { "id": 999040, "author_name": "", "author_url": "", "post_date": "2020-09-05T09:41:15.373000", "content": "", "votes": 0, "replies": [] }, { "id": 3052783, "author_name": "Fabio Schirmann", "author_url": "", "post_date": "2024-11-22T20:35:11.280000", "content": "Interesting!
", "votes": 0, "replies": [] }, { "id": 2154974, "author_name": "Jadeee Yu", "author_url": "", "post_date": "2023-02-22T11:07:51.677000", "content": "Thank you!
", "votes": 0, "replies": [] }, { "id": 2142109, "author_name": "Anna Kodash", "author_url": "", "post_date": "2023-02-13T10:23:46.933000", "content": "It's great, thank you
", "votes": 0, "replies": [] }, { "id": 1935278, "author_name": "", "author_url": "", "post_date": "2022-09-12T01:59:38.560000", "content": "", "votes": 0, "replies": [] }, { "id": 1697994, "author_name": "", "author_url": "", "post_date": "2022-02-20T03:40:48.650000", "content": "", "votes": 0, "replies": [] }, { "id": 1629029, "author_name": "", "author_url": "", "post_date": "2021-12-25T15:31:18.497000", "content": "", "votes": 0, "replies": [] }, { "id": 1565005, "author_name": "", "author_url": "", "post_date": "2021-10-29T22:22:27.957000", "content": "", "votes": 0, "replies": [] }, { "id": 1417591, "author_name": "", "author_url": "", "post_date": "2021-08-03T00:27:57.837000", "content": "", "votes": 0, "replies": [] }, { "id": 1395647, "author_name": "", "author_url": "", "post_date": "2021-07-21T12:23:41.447000", "content": "", "votes": 0, "replies": [] }, { "id": 1108849, "author_name": "", "author_url": "", "post_date": "2020-12-11T04:26:14.917000", "content": "", "votes": 0, "replies": [] }, { "id": 1046459, "author_name": "", "author_url": "", "post_date": "2020-10-11T17:13:52.177000", "content": "", "votes": 0, "replies": [] } ], "raw_markdown_by_id": { "989491": "Hello!\n \nWelcome to I’m Something of a Painter Myself!\n \nWe are super excited to have you participate in our first-ever generative getting started competition. Your task is to generate Monet-esque images, whether from scratch or by transforming photos. To learn more, check out our [competition description](https://www.kaggle.com/c/gan-getting-started/overview).\n \nAs a [Getting Started Competition](https://www.kaggle.com/c/gan-getting-started/overview/frequently-asked-questions), there are no prizes, deadlines, nor private leaderboards. This competition will run indefinitely and will be a resource to become more familiar with these concepts:\n \n- Computer vision\n- Generative models\n- Tensor Processing Units (TPUs)\n- TFRecords format for TensorFlow \n \nTo get started, we have created a [CycleGAN tutorial](https://www.kaggle.com/amyjang/monet-cyclegan-tutorial) on the data, but please feel free to experiment with other architectures as well. You are welcome to add in additional datasets to help with the training of your model; just remember that submissions of actual Monet paintings and transformations of such paintings are not allowed.\n \nGood luck and have fun learning to paint (using computer vision, that is)!\n \n**Remember:** Kaggle is for everyone. Whether you're teaming up or sharing tips in the competition forum, we expect everyone to follow our [Kaggle community guidelines](https://www.kaggle.com/community-guidelines).", "1107689": "Hi! I appreciate this competition, but it's not very clear from description how is the final score computed. \nFor me, it looks like there is some \"evaluation network\" that has internal inception layer that is used to compute FID for the pair of generated and real images. But is there any information about this Inception network? Like, what is the full architecture of this network or how was it trained? \nAlso, let's say I submit 7k generated images and there are ~300 real images. Does it compute 7000x300 FID scores and then average them?\nThanks in advance for the clarification.", "990670": "This is really a fun competition as a beginner I am truly excited to learn about GANs. Though a small request to the Kaggle team if they can make medals for this competition for further motivation. Thank you!!\nWhat do fellow kagglers think?", "3440998": "Does anyone encounter problems with submitting submission file? I submitted different image sizes 128x128 and 256x256 and both received an error that the file is too big or too small. it was zipped 7k+ png files. Anyone can help?", "3224529": "Hello everyone! I'm joining the 'I’m Something of a Painter Myself' competition. Honestly, I'm not sure if I have any artistic talent myself, but I'm really looking forward to creating new 'masterpieces' with the power of AI!", "3181781": "someone please explain me as a beginner what should I do to get started in competitions. please please", "3144685": "Hello everyone, I am starting to discover this challenge and was wondering if the order of images in both directories matters.Thanks", "3022755": "Hello, I participated in this competition.\nI used a GPU to calculate for several hours in Kaggle Notebook.\nAs a result, I was able to create a painting similar to Monet. \nThank you for providing such a fun competition.", "2993086": "GOOD, cannot wait to submit it", "2794747": "Interesting!", "2693910": "Interesting! Feel lucky to be able to take part", "2497820": "Hi! Looking for a team to work on competitions. Please reach out to me if you are looking for one. I am intermediate level in python and beginner level in machine learning.", "2165511": "This is my Second competition but actually, it would be the fist challenge for me to do about vision networks.", "2031401": "Let's try to use diffusion model like novel ai !", "1807746": "@amyjang Hi, thanks for this competition!\n\nI'm trying to use the starter code in Colab and I* changed* the monet/**photo_tfrec** inputs for the monet/**photo_jpeg**, but I get the following errors below. Of course it works fine otherwise with the tfrecs.\n\nCan anyone explain why this happens or how to use this on all of the images ano not just the tfrecs ?\n\n```\nexample_monet = next(iter(monet_ds))\nexample_photo = next(iter(photo_ds))\n```\nThe error says: **DataLossError: corrupted record at 0 [Op:IteratorGetNext]**\n\nThen, trying to fit the model I get something similar:\n\n`2 root error(s) found.\n (0) DATA_LOSS: corrupted record at 0\n\t [[{{node IteratorGetNext}}]]\n\t [[IteratorGetNext/_2]]\n (1) DATA_LOSS: corrupted record at 0\n\t [[{{node IteratorGetNext}}]]\n0 successful operations.\n0 derived errors ignored. [Op:__inference_train_function_57323]`\n", "1801278": "For me, as novice, it was an interesting competition, from understanding simple GAN to CycleGAN with all useful notebooks and then thinking about improvements was educating and fun!\nThanks a lot!\n", "1713549": "hi, it's cool", "1535770": "looks good to me", "1436359": "hi this is cool!", "1420614": "Hi, thank you vey much for this kind of resources. These are very helpful for practitioners and for professionals who are seeking new challenges.", "1276057": "This is really fantastic! What a beautiful mix of classical art and modern machine beauty.", "1079030": "Nice, I am currently completing this challenge but I am challenging myself by not following the template directly.", "992019": "Thanks for your wonderful notebook !!!!!", "990205": "Thanks a lot for this competition! I was learning about GAN! And this came up! Really nice! And thanks a lot.", "989573": "This is Awesome. I'm definatley looking forward to this.", "2946634": "intersting", "999040": "", "3052783": "Interesting!", "2154974": "Thank you!", "2142109": "It's great, thank you", "1935278": "Thanks! That is good for me!", "1697994": "Thanks! It is good for me!", "1629029": "hi, thanks\nGANs are interesting 👍", "1565005": "Thanks ! So cool !", "1417591": "Thanks!! I am animated!\n", "1395647": "Thanks a lot !!!", "1108849": "Thanks for your useful notebooks!", "1046459": "Great notebook - thanks!" } }