{ "id": 290016, "title": "πŸ”₯πŸ”₯Kaggle Starter Notebooks for Object Detection", "url": "/competitions/tensorflow-great-barrier-reef/discussion/290016", "author_name": "Tensor Girl", "post_date": "2021-11-22T19:56:16.231000", "votes": 152, "comment_count": 31, "views": 0, "content": "

Hello everyone ,
\nI have compiled useful kaggle starter notebook on various object detection architecture for easy reference .
\nTensorflow Object Detection API
\nhttps://www.kaggle.com/sreevishnudamodaran/vbd-efficientdet-tf2-object-detection-api
\nhttps://www.kaggle.com/mistag/train-vinbigdata-tf-object-detection-api
\nEfficientDet
\nhttps://www.kaggle.com/shonenkov/training-efficientdet
\nhttps://www.kaggle.com/shonenkov/inference-efficientdet
\nhttps://www.kaggle.com/ateplyuk/gwd-starter-efficientdet-keras-train
\nFasterRCNN
\nhttps://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-train
\nhttps://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-inference
\nYolov5
\nhttps://www.kaggle.com/orkatz2/yolov5-train
\nhttps://www.kaggle.com/nvnnghia/yolov5-pseudo-labeling
\nDETR
\nhttps://www.kaggle.com/tanulsingh077/end-to-end-object-detection-with-transformers-detr
\nHope you found it useful

", "messages": [ { "id": 1592024, "postDate": "2021-11-22T19:56:16.233Z", "content": "

Hello everyone ,
\nI have compiled useful kaggle starter notebook on various object detection architecture for easy reference .
\nTensorflow Object Detection API
\nhttps://www.kaggle.com/sreevishnudamodaran/vbd-efficientdet-tf2-object-detection-api
\nhttps://www.kaggle.com/mistag/train-vinbigdata-tf-object-detection-api
\nEfficientDet
\nhttps://www.kaggle.com/shonenkov/training-efficientdet
\nhttps://www.kaggle.com/shonenkov/inference-efficientdet
\nhttps://www.kaggle.com/ateplyuk/gwd-starter-efficientdet-keras-train
\nFasterRCNN
\nhttps://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-train
\nhttps://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-inference
\nYolov5
\nhttps://www.kaggle.com/orkatz2/yolov5-train
\nhttps://www.kaggle.com/nvnnghia/yolov5-pseudo-labeling
\nDETR
\nhttps://www.kaggle.com/tanulsingh077/end-to-end-object-detection-with-transformers-detr
\nHope you found it useful

", "rawMarkdown": "\nHello everyone ,\n\nI have compiled useful kaggle starter notebook on various object detection architecture for easy reference .\n\n**Tensorflow Object Detection API**\n\nhttps://www.kaggle.com/sreevishnudamodaran/vbd-efficientdet-tf2-object-detection-api\n\nhttps://www.kaggle.com/mistag/train-vinbigdata-tf-object-detection-api\n\n\n\n**EfficientDet**\n\nhttps://www.kaggle.com/shonenkov/training-efficientdet\n\nhttps://www.kaggle.com/shonenkov/inference-efficientdet\n\nhttps://www.kaggle.com/ateplyuk/gwd-starter-efficientdet-keras-train\n\n\n\n**FasterRCNN**\n\nhttps://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-train\n\nhttps://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-inference\n\n\n\n**Yolov5**\n\nhttps://www.kaggle.com/orkatz2/yolov5-train\n\nhttps://www.kaggle.com/nvnnghia/yolov5-pseudo-labeling\n\n\n\n**DETR**\n\nhttps://www.kaggle.com/tanulsingh077/end-to-end-object-detection-with-transformers-detr\n\nHope you found it useful", "votes": 152 }, { "id": 2185597, "postDate": "2023-03-17T07:19:12.720Z", "content": "

Your contribution to the discussion has been really helpful @usharengaraju

", "rawMarkdown": "Your contribution to the discussion has been really helpful @usharengaraju ", "votes": 2 }, { "id": 1600461, "postDate": "2021-11-30T12:48:52.017Z", "content": "

Hi Tensor Girl @usharengaraju I wanted to be on your list … so …. implemented YOLOX full pipeline for Kaggle users. Hope it you like it - https://www.kaggle.com/remekkinas/yolox-full-training-pipeline-for-cots-dataset

", "rawMarkdown": "Hi Tensor Girl @usharengaraju I wanted to be on your list ... so .... implemented YOLOX full pipeline for Kaggle users. Hope it you like it - https://www.kaggle.com/remekkinas/yolox-full-training-pipeline-for-cots-dataset", "votes": 4, "replies": [ { "id": 1603174, "postDate": "2021-12-02T11:36:39.883Z", "content": "

Now inference part of YOLOX on Kaggle …. launched :) https://www.kaggle.com/remekkinas/yolox-inference-on-kaggle-for-cots

", "rawMarkdown": "Now inference part of YOLOX on Kaggle .... launched :) https://www.kaggle.com/remekkinas/yolox-inference-on-kaggle-for-cots", "votes": 2 } ] }, { "id": 1657141, "postDate": "2022-01-20T00:16:35.133Z", "content": "

Thank you for the listing and sharing the kernels!!

", "rawMarkdown": "Thank you for the listing and sharing the kernels!!", "votes": 1 }, { "id": 1638938, "postDate": "2022-01-05T07:18:28.047Z", "content": "

Thanks for sharing. I wanted something like this

", "rawMarkdown": "Thanks for sharing. I wanted something like this", "votes": 1 }, { "id": 1636378, "postDate": "2022-01-02T20:11:18.607Z", "content": "

Thanks for sharing. I think, you can add kernels with Detectron2 and mmdetection)

", "rawMarkdown": "Thanks for sharing. I think, you can add kernels with Detectron2 and mmdetection)", "votes": 1 }, { "id": 1631901, "postDate": "2021-12-28T22:15:42.487Z", "content": "

@usharengaraju now you can add next one implementation to your collection: YoloR https://www.kaggle.com/remekkinas/yolor-p6-w6-one-more-yolo-on-kaggle-train πŸ‘πŸ˜„πŸ˜πŸ˜ƒ

", "rawMarkdown": "@usharengaraju now you can add next one implementation to your collection: YoloR https://www.kaggle.com/remekkinas/yolor-p6-w6-one-more-yolo-on-kaggle-train πŸ‘πŸ˜„πŸ˜πŸ˜ƒ", "votes": 1 }, { "id": 1595486, "postDate": "2021-11-25T18:09:43.330Z", "content": "

Shall I put up a kernel for converting xml/jpg labels to tf records and
\ngeneral idea of how to tune faster-rcnn ?

", "rawMarkdown": "Shall I put up a kernel for converting xml/jpg labels to tf records and\ngeneral idea of how to tune faster-rcnn ?", "votes": 1 }, { "id": 1593098, "postDate": "2021-11-23T16:28:21.457Z", "content": "

Great, that's very helpful.

", "rawMarkdown": "Great, that's very helpful.", "votes": 1 }, { "id": 1606358, "postDate": "2021-12-05T00:20:08.457Z", "content": "

Unfortunately, the only problem in this competition is the lack of hardware, but in any case, thank you

", "rawMarkdown": "Unfortunately, the only problem in this competition is the lack of hardware, but in any case, thank you", "votes": 2, "replies": [ { "id": 1606360, "postDate": "2021-12-05T00:22:34.077Z", "content": "

The more we move forward to get better, the worse it just gets

", "rawMarkdown": "The more we move forward to get better, the worse it just gets", "votes": 3 } ] }, { "id": 1602107, "postDate": "2021-12-01T19:19:55.420Z", "content": "

Definitely useful, thank you for putting it together.

", "rawMarkdown": "Definitely useful, thank you for putting it together.", "votes": 2 }, { "id": 1594003, "postDate": "2021-11-24T13:10:35.803Z", "content": "

Large diversity of Object Detector models .Thanks for your sharings @usharengaraju

", "rawMarkdown": "Large diversity of Object Detector models .Thanks for your sharings @usharengaraju ", "votes": 2 }, { "id": 1893968, "postDate": "2022-08-11T07:36:35.013Z", "content": "

Test Different models on this innovative Object Detection Dataset. This dataset contains around 5000 training images of Construction workers and 250 images for your inference. Dataset Link:Here

", "rawMarkdown": "Test Different models on this innovative Object Detection Dataset. This dataset contains around 5000 training images of Construction workers and 250 images for your inference. Dataset Link:[Here](https://www.kaggle.com/datasets/rahulgolder/hardhat-data)" }, { "id": 1630833, "postDate": "2021-12-27T18:36:30.363Z", "rawMarkdown": "", "votes": 1, "isDeleted": true }, { "id": 1592395, "postDate": "2021-11-23T04:36:32.357Z", "rawMarkdown": "", "votes": 1, "isDeleted": true }, { "id": 1667955, "postDate": "2022-01-29T06:08:03.597Z", "content": "

super helpful, thank you!

", "rawMarkdown": "super helpful, thank you!", "votes": 1 }, { "id": 1652656, "postDate": "2022-01-16T21:00:00.913Z", "content": "

Thank you!

", "rawMarkdown": "Thank you!", "votes": 1 }, { "id": 1646812, "postDate": "2022-01-12T03:56:18.030Z", "content": "

Very helpful. Thank you for sharing!

", "rawMarkdown": "Very helpful. Thank you for sharing!", "votes": 1 }, { "id": 1645759, "postDate": "2022-01-11T07:28:06.283Z", "content": "

Thanks for sharing.

", "rawMarkdown": "Thanks for sharing.", "votes": 1 }, { "id": 1605582, "postDate": "2021-12-04T11:25:42.917Z", "content": "

Thanks for sharing

", "rawMarkdown": "Thanks for sharing", "votes": 1 }, { "id": 1605303, "postDate": "2021-12-04T06:06:50.783Z", "content": "

Thanks for sharing @usharengaraju

", "rawMarkdown": "Thanks for sharing @usharengaraju ", "votes": 1 }, { "id": 1599091, "postDate": "2021-11-29T06:03:30.447Z", "content": "

Thank you !!

", "rawMarkdown": "Thank you !!", "votes": 1 }, { "id": 1597196, "postDate": "2021-11-27T10:01:31.127Z", "content": "

Thanks for sharing

", "rawMarkdown": "Thanks for sharing\n\n", "votes": 1 }, { "id": 1593982, "postDate": "2021-11-24T12:50:59.557Z", "content": "

Thanks for sharing.

", "rawMarkdown": "Thanks for sharing.", "votes": 1 }, { "id": 1593960, "postDate": "2021-11-24T12:25:42.557Z", "content": "

thanks a lot

", "rawMarkdown": "thanks a lot", "votes": 1 }, { "id": 1593946, "postDate": "2021-11-24T12:16:18.177Z", "content": "

Thanks for sharing :)

", "rawMarkdown": "Thanks for sharing :)", "votes": 1 }, { "id": 1593580, "postDate": "2021-11-24T04:36:29.970Z", "content": "

Thanks for sharing

", "rawMarkdown": "Thanks for sharing", "votes": 1 }, { "id": 1593305, "postDate": "2021-11-23T18:56:57.013Z", "content": "

Awesome !! Thanks !! :)

", "rawMarkdown": "Awesome !! Thanks !! :)", "votes": 1 }, { "id": 1593216, "postDate": "2021-11-23T17:58:19.407Z", "content": "

Thanks for sharing

", "rawMarkdown": "Thanks for sharing", "votes": 1 }, { "id": 1594079, "postDate": "2021-11-24T14:20:16.307Z", "content": "

Thanks for sharing

", "rawMarkdown": "Thanks for sharing", "votes": 2 } ], "comments": [ { "id": 2185597, "author_name": "Yeakub Sadlil", "author_url": "", "post_date": "2023-03-17T07:19:12.720000", "content": "

Your contribution to the discussion has been really helpful @usharengaraju

", "votes": 2, "replies": [] }, { "id": 1600461, "author_name": "Remek Kinas", "author_url": "", "post_date": "2021-11-30T12:48:52.017000", "content": "

Hi Tensor Girl @usharengaraju I wanted to be on your list … so …. implemented YOLOX full pipeline for Kaggle users. Hope it you like it - https://www.kaggle.com/remekkinas/yolox-full-training-pipeline-for-cots-dataset

", "votes": 4, "replies": [ { "id": 1603174, "author_name": "Remek Kinas", "author_url": "", "post_date": "2021-12-02T11:36:39.883000", "content": "

Now inference part of YOLOX on Kaggle …. launched :) https://www.kaggle.com/remekkinas/yolox-inference-on-kaggle-for-cots

", "votes": 2, "replies": [] } ] }, { "id": 1657141, "author_name": "Eugene J. Ryu", "author_url": "", "post_date": "2022-01-20T00:16:35.133000", "content": "

Thank you for the listing and sharing the kernels!!

", "votes": 1, "replies": [] }, { "id": 1638938, "author_name": "Koshikawa54", "author_url": "", "post_date": "2022-01-05T07:18:28.047000", "content": "

Thanks for sharing. I wanted something like this

", "votes": 1, "replies": [] }, { "id": 1636378, "author_name": "Timur", "author_url": "", "post_date": "2022-01-02T20:11:18.607000", "content": "

Thanks for sharing. I think, you can add kernels with Detectron2 and mmdetection)

", "votes": 1, "replies": [] }, { "id": 1631901, "author_name": "Remek Kinas", "author_url": "", "post_date": "2021-12-28T22:15:42.487000", "content": "

@usharengaraju now you can add next one implementation to your collection: YoloR https://www.kaggle.com/remekkinas/yolor-p6-w6-one-more-yolo-on-kaggle-train πŸ‘πŸ˜„πŸ˜πŸ˜ƒ

", "votes": 1, "replies": [] }, { "id": 1595486, "author_name": "Adwitiya Trivedi", "author_url": "", "post_date": "2021-11-25T18:09:43.330000", "content": "

Shall I put up a kernel for converting xml/jpg labels to tf records and
\ngeneral idea of how to tune faster-rcnn ?

", "votes": 1, "replies": [] }, { "id": 1593098, "author_name": "Lonnie", "author_url": "", "post_date": "2021-11-23T16:28:21.457000", "content": "

Great, that's very helpful.

", "votes": 1, "replies": [] }, { "id": 1606358, "author_name": "Mahdi_asdzd", "author_url": "", "post_date": "2021-12-05T00:20:08.457000", "content": "

Unfortunately, the only problem in this competition is the lack of hardware, but in any case, thank you

", "votes": 2, "replies": [ { "id": 1606360, "author_name": "Mahdi_asdzd", "author_url": "", "post_date": "2021-12-05T00:22:34.077000", "content": "

The more we move forward to get better, the worse it just gets

", "votes": 3, "replies": [] } ] }, { "id": 1602107, "author_name": "ElenaEB", "author_url": "", "post_date": "2021-12-01T19:19:55.420000", "content": "

Definitely useful, thank you for putting it together.

", "votes": 2, "replies": [] }, { "id": 1594003, "author_name": "Mathurin Ache", "author_url": "", "post_date": "2021-11-24T13:10:35.803000", "content": "

Large diversity of Object Detector models .Thanks for your sharings @usharengaraju

", "votes": 2, "replies": [] }, { "id": 1893968, "author_name": "Rahul Golder", "author_url": "", "post_date": "2022-08-11T07:36:35.013000", "content": "

Test Different models on this innovative Object Detection Dataset. This dataset contains around 5000 training images of Construction workers and 250 images for your inference. Dataset Link:Here

", "votes": 0, "replies": [] }, { "id": 1630833, "author_name": "", "author_url": "", "post_date": "2021-12-27T18:36:30.363000", "content": "", "votes": 1, "replies": [] }, { "id": 1592395, "author_name": "", "author_url": "", "post_date": "2021-11-23T04:36:32.357000", "content": "", "votes": 1, "replies": [] }, { "id": 1667955, "author_name": "Hiroyuki Onishi", "author_url": "", "post_date": "2022-01-29T06:08:03.597000", "content": "

super helpful, thank you!

", "votes": 1, "replies": [] }, { "id": 1652656, "author_name": "Ata Cengiz", "author_url": "", "post_date": "2022-01-16T21:00:00.913000", "content": "

Thank you!

", "votes": 1, "replies": [] }, { "id": 1646812, "author_name": "Shamil Jamion", "author_url": "", "post_date": "2022-01-12T03:56:18.030000", "content": "

Very helpful. Thank you for sharing!

", "votes": 1, "replies": [] }, { "id": 1645759, "author_name": "Yan Houng Tan", "author_url": "", "post_date": "2022-01-11T07:28:06.283000", "content": "

Thanks for sharing.

", "votes": 1, "replies": [] }, { "id": 1605582, "author_name": "Kamal Das", "author_url": "", "post_date": "2021-12-04T11:25:42.917000", "content": "

Thanks for sharing

", "votes": 1, "replies": [] }, { "id": 1605303, "author_name": "Muhammad Sameer", "author_url": "", "post_date": "2021-12-04T06:06:50.783000", "content": "

Thanks for sharing @usharengaraju

", "votes": 1, "replies": [] }, { "id": 1599091, "author_name": "Saumil Agrawal", "author_url": "", "post_date": "2021-11-29T06:03:30.447000", "content": "

Thank you !!

", "votes": 1, "replies": [] }, { "id": 1597196, "author_name": "Abdelrady .M", "author_url": "", "post_date": "2021-11-27T10:01:31.127000", "content": "

Thanks for sharing

", "votes": 1, "replies": [] }, { "id": 1593982, "author_name": "Minu Genty", "author_url": "", "post_date": "2021-11-24T12:50:59.557000", "content": "

Thanks for sharing.

", "votes": 1, "replies": [] }, { "id": 1593960, "author_name": "Oğuzhan Eroğlu", "author_url": "", "post_date": "2021-11-24T12:25:42.557000", "content": "

thanks a lot

", "votes": 1, "replies": [] }, { "id": 1593946, "author_name": "Parv Yadav", "author_url": "", "post_date": "2021-11-24T12:16:18.177000", "content": "

Thanks for sharing :)

", "votes": 1, "replies": [] }, { "id": 1593580, "author_name": "sakuragi", "author_url": "", "post_date": "2021-11-24T04:36:29.970000", "content": "

Thanks for sharing

", "votes": 1, "replies": [] }, { "id": 1593305, "author_name": "Ludovico Cuoghi", "author_url": "", "post_date": "2021-11-23T18:56:57.013000", "content": "

Awesome !! Thanks !! :)

", "votes": 1, "replies": [] }, { "id": 1593216, "author_name": "Dhinahar P", "author_url": "", "post_date": "2021-11-23T17:58:19.407000", "content": "

Thanks for sharing

", "votes": 1, "replies": [] }, { "id": 1594079, "author_name": "Noman Ahmed", "author_url": "", "post_date": "2021-11-24T14:20:16.307000", "content": "

Thanks for sharing

", "votes": 2, "replies": [] } ], "raw_markdown_by_id": { "1592024": "\nHello everyone ,\n\nI have compiled useful kaggle starter notebook on various object detection architecture for easy reference .\n\n**Tensorflow Object Detection API**\n\nhttps://www.kaggle.com/sreevishnudamodaran/vbd-efficientdet-tf2-object-detection-api\n\nhttps://www.kaggle.com/mistag/train-vinbigdata-tf-object-detection-api\n\n\n\n**EfficientDet**\n\nhttps://www.kaggle.com/shonenkov/training-efficientdet\n\nhttps://www.kaggle.com/shonenkov/inference-efficientdet\n\nhttps://www.kaggle.com/ateplyuk/gwd-starter-efficientdet-keras-train\n\n\n\n**FasterRCNN**\n\nhttps://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-train\n\nhttps://www.kaggle.com/pestipeti/pytorch-starter-fasterrcnn-inference\n\n\n\n**Yolov5**\n\nhttps://www.kaggle.com/orkatz2/yolov5-train\n\nhttps://www.kaggle.com/nvnnghia/yolov5-pseudo-labeling\n\n\n\n**DETR**\n\nhttps://www.kaggle.com/tanulsingh077/end-to-end-object-detection-with-transformers-detr\n\nHope you found it useful", "2185597": "Your contribution to the discussion has been really helpful @usharengaraju ", "1600461": "Hi Tensor Girl @usharengaraju I wanted to be on your list ... so .... implemented YOLOX full pipeline for Kaggle users. Hope it you like it - https://www.kaggle.com/remekkinas/yolox-full-training-pipeline-for-cots-dataset", "1657141": "Thank you for the listing and sharing the kernels!!", "1638938": "Thanks for sharing. I wanted something like this", "1636378": "Thanks for sharing. I think, you can add kernels with Detectron2 and mmdetection)", "1631901": "@usharengaraju now you can add next one implementation to your collection: YoloR https://www.kaggle.com/remekkinas/yolor-p6-w6-one-more-yolo-on-kaggle-train πŸ‘πŸ˜„πŸ˜πŸ˜ƒ", "1595486": "Shall I put up a kernel for converting xml/jpg labels to tf records and\ngeneral idea of how to tune faster-rcnn ?", "1593098": "Great, that's very helpful.", "1606358": "Unfortunately, the only problem in this competition is the lack of hardware, but in any case, thank you", "1602107": "Definitely useful, thank you for putting it together.", "1594003": "Large diversity of Object Detector models .Thanks for your sharings @usharengaraju ", "1893968": "Test Different models on this innovative Object Detection Dataset. This dataset contains around 5000 training images of Construction workers and 250 images for your inference. Dataset Link:[Here](https://www.kaggle.com/datasets/rahulgolder/hardhat-data)", "1630833": "", "1592395": "", "1667955": "super helpful, thank you!", "1652656": "Thank you!", "1646812": "Very helpful. Thank you for sharing!", "1645759": "Thanks for sharing.", "1605582": "Thanks for sharing", "1605303": "Thanks for sharing @usharengaraju ", "1599091": "Thank you !!", "1597196": "Thanks for sharing\n\n", "1593982": "Thanks for sharing.", "1593960": "thanks a lot", "1593946": "Thanks for sharing :)", "1593580": "Thanks for sharing", "1593305": "Awesome !! Thanks !! :)", "1593216": "Thanks for sharing", "1594079": "Thanks for sharing" } }